The DOI matches its Crossref record; 11 of the 12 references it cites were found in a registry or an index; none of the 20 sources its claims cite is checked for support yet.
Structure-mapping: A theoretical framework for analogy
Open accessAbstract
A theory of analogy must describe how the meaning of an analogy is derived from the meanings of its parts. In the structure-mapping theory, the interpretation rules are characterized as implicit rules for mapping knowledge about a base domain into a target domain. Two important features of the theory are (a) the rules depend only on syntactic properties of the knowledge representation, and not on the specific content of the domains; and (b) the theoretical framework allows analogies to be distinguished cleanly from literal similarity statements, applications of abstractions, and other kinds of comparisons. Two mapping principles are described: (a) Relations between objects, rather than attributes of objects, are mapped from base to target; and (b) The particular relations mapped are determined by systematicity, as defined by the existence of higher-order relations.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This paper presents structure-mapping as a framework for how analogies are interpreted, arguing that analogical mapping transfers relations between objects rather than object attributes, and that relations belonging to interconnected higher-order systems are preferred. It distinguishes analogy from literal similarity, abstraction, and mere appearance matches, and cites prior empirical work as support.
Key findings
- Analogy maps relational predicates from base to target while discarding object attributes; for example, the atom/solar-system analogy maps relations such as revolving around, attraction, and relative mass, but not attributes such as color or temperature.
- The systematicity principle holds that a predicate is more likely to be mapped if it belongs to a mutually interconnected system of relations, especially higher-order causal or constraint structures; this explains why a relation like “more massive than” is preserved while a formally similar relation like “hotter than” is not.
- The framework separates comparison types by predicate overlap: literal similarity maps many attributes and many relations; analogy maps few attributes and many relations; abstraction maps few attributes and many relations with abstract base objects; mere appearance maps attributes but not relations; anomaly maps neither.
- Empirical support is cited from prior studies: subjects’ interpretations of analogical comparisons were predominantly relational, and aptness ratings correlated with the amount of relational information produced; no numeric values are reported in this paper.
Methods
- Theoretical paper: knowledge is represented as propositional networks with syntactic predicate types—attributes take one argument, relations take two or more, and predicates can be first-order or higher-order.
- Worked examples (Rutherford atom/solar system, heat/water, arithmetic analogy) are used to derive mapping rules and a taxonomy of domain comparisons.
- Empirical support is summarized from prior studies in which subjects wrote interpretations of analogical comparisons and naive judges rated assertions as attribute-based or relation-based; developmental and science-learning studies are also cited.
Limitations
- The paper states a simplifying assumption that the hearer begins with object correspondences and then maps relations; it notes that actual processing order is variable and that object correspondences may be settled only before relational mapping is finished.
- The paper assumes predicates are carried across as identical matches and notes that treating predicates as merely similar risks an infinite regress.
- Evident from the text: empirical support is brief and relies on cited studies rather than new experiments or statistics; the paper is primarily theoretical and does not report detailed sample sizes or quantitative results.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
62 Own interpretation · 13 Not checked yet · 2 Own result · 1 No basis given
In the paper
“Further, a correlation of aptness ratings and relationality ratings revealed that subjects rated as most apt those analogies for which they wrote the greatest amount of relational information.”
What the sources say
- Not checked yetcites Gentner, 1980b
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Such a “degree of overlap” approach seems reasonably correct for literal similarity comparisons.”
What the sources say
- Not checked yetcites Tversky (1977)
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One symptom of this systematicity is that changing one of these relations affects the others.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We could accomplish this by postulating that analogies select for dynamic causal knowledge, or more generally, for appropriate abstractions.Either of these would be a mistake: The former course limits the scope of analogy unreasonably,”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There is research supporting the structure-mapping approach.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, if we assume the systematicity principle, then the set of overlapping predicates is likely to include higher-order relations such as CAUSE and IMPLIES.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By the systematicity principle, to the extent that people recognize (however vaguely) that the system of predicates connected with central forces is the deepest, most interconnected mappable system for this analogy, they will favor relations that belong to that system in their interpretations.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Partial knowledge of a system is often sufficient for a person to gauge its interconnectedness.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further, the rules are such as to distinguish analogy from other kinds of domain comparisons, such as abstraction or literal similarity.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The same interdependencies hold for the atom, if we make the appropriate node substitutions:”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These object correspondences are used to generate the candidate set of inferences in the target domain.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 21
- It may state two separate claims as one. 8
- The quote only partly states this claim. 1
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“An informal observation is that the earliest comparisons are chiefly literalsimilarity matches, followed by analogies, followed by general laws.”
hedgedcorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“His first comparisons were similarity matches, e.g., water coming through a constricted hose.Later, he produced analogies such as a train speeding up or slowing down, and balls banging into the walls and transferring momentum.Finally, he arrived at a general statement of the Bernoulli principle, that velocity increases and pressure decreases in a constriction.”
plaincorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“The results indicated a strong focus on relational information in interpreting analogies.Relational information predominates over attributional information in analogy interpretations, but not in object descriptions generated by the same sub-”
What the sources say
- Not checked yetcites Gentner, 1980b
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The systematicity principle offers a way to satisfy both requirements.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Part of our understanding about analogy is that it conveys a system of connected knowledge, not a mere assortment of independent facts.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Intuitively, the second scenario is more interesting than the first: (1) conveys merely a static spatial description, while (2) conveys a dynamic causal description.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“2. Try to preserve relations between objects: Nbi, WI --> ML, t,),”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“3. (The Systematicity Principle) To decide which relations are preserved, choose systems of relations:”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“These kinds of representations can deal well with object attributes, but are extremely limited in their ability to express relations between objects, and especially higher-order relations.”
What the sources say
- Not checked yetcites Ortony, 1979
- Not checked yetcites Rumelhart & Abrahamson, 1973
- Not checked yetcites Tourangeau & Sternberg, 1981
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These equations embody higher-order relations that connect the lowerorder relations (1) through (4) into a mutually constraining structure.”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is why MORE MASSIVE THAN is preserved while HOTTER THAN is not: Only MORE MASSIVE THAN participates in the central-force system of predicates.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Predicates from B are carried across6 to T, using the node substitutions dictated by the”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Potential analogies are less likely to be noticed, since they require accessing the data base via relational matches; object matches are of no use.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The central idea is that an analogy is an assertion that a relational structure that normally applies in one domain can be applied in another domain.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The strucfure-mapping theory describes the implicit interpretation rules of analogy.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The strength of an analogical match does not seem to depend on the overall degree of featural overlap; not all features are equally relevant to the interpretation.Only certain kinds of mismatches count for or against analogies.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(2) An analogy is a comparison in which relational predicates, but few or no object attributes, can be mapped from base to target.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“(1) A literul similurity statement is a comparison in which a large number of predicates is mapped from base to target, relative to the number of nonmapped predicates (e.g., Tversky, 1977).The mapped predicates include both object-attributes and relational predicates.”
What the sources say
- Not checked yetcites Tversky, 1977
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These rules have the desirable property that they depend only on syntactic properties of the knowledge representation, and not on the specific content of the domain.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Dynamic causal information [e.g., (2)] will usually be represented in a more deeply embedded structure than simple stative information [e.g., (l)].”
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Such a system can be represented by an interconnected predicate structure in which higher-order predicates enforce connections among lower-order predicates.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the structuremapping theory, a simple but powerful distinction is made among predicate types that allows us to state which ones will be mapped.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“1.Discard attributes of objects: A(b,)I -•t -> LWJ”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Wbstraction differs from analogy and the other comparisons i n having few abject-attributes i n the bose domain as well as few object-attributes i n the target domain.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further, this theoretical framework allows us to state the differences between analogies and literal similarity statements, abstractions and other kinds of comparisons.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and the latter course is both vague, in that “appropriateness” is difficult to define explicitly, and incorrect, in that analogies can also convey inappro-e”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Most explanatory analogies are l-1 mappings, in which m = n.However, there are exceptions (Gentner, 1982).”
What the sources say
- Not checked yetcites Gentner, 1982
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“indeed the number of mappable relations may have no clear upper bound.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The analogy maps the object nodes of B onto the object nodes of T: M: bi --> t,”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Many such metaphors involve conventional vehicles, such as “giraffe” above, or conventional dimensional matches, such as “a deep/shallow idea”.[Glucksberg, Gildea, & Bookin, 1982;Lakoff & Johnson, 19801).”
What the sources say
- Not checked yetcites Glucksberg, Gildea, & Bookin, 1982
- Not checked yetcites Lakoff & Johnson, 19801
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The authors state this as an assumption.
Predicates are carried across as identical matches, and similarity can be restated as identity among some number of component predicates.
“The assumption that predicates are brought across as idenficul matches is crucial to the clarity of this discussion.”
“I will assume instead that similarity can be restated as identity among some number of component predicates.”
The authors state this as an assumption.
Partial knowledge of a system is often sufficient for a person to gauge its interconnectedness.
“I make the assumption here that partial knowledge of the system is often sufficient to allow a person to gauge its interconnectedness.”
The authors state this as an assumption.
In comprehending an analogy, the hearer begins with object correspondences and then maps relations across.
“Yn this discussion I have made the simplifying assumption that, in comprehension of analogy, the hearer starts with the object correspondences and then maps across the relations.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Higher-level forms of relational reasoning, such as analogy and inference, involve mapping correspondences and creating higher-order relations between schemas (i.e., relations between relations; Gentner, 1983;Holyoak, 2012).”
From Mental Time Travel? A Neurocognitive Model of Event Simulation. (2020) · cites this paper as Gentner, 1983
Citations
Cites
Schema induction and analogical transfer
Gick, M. L., & Holyoak, K. J. (1983) · Cognitive Psychology · doi:10.1016/0010-0285(83)90002-6 · Cited by 3,010 · cited 1×
“Gick and Holyoak have also emphasized the relationship between analogical matching and the formation of general schemas in an interesting series of studies of transfer in problem-solving (Gick & Holyoak, 1980, 1983; Holyoak, in press).”
BackgroundGick, M. L., & Holyoak, K. J. (1980) · Cognitive Psychology · doi:10.1016/0010-0285(80)90013-4 · Cited by 2,552 · cited 4×
“Gick and Holyoak have also emphasized the relationship between analogical matching and the formation of general schemas in an interesting series of studies of transfer in problemsolving (Gick & Holyoak, 1980, 1983; Holyoak, in press). Other researchers have explored specific instances of relational mapping. VanLehn an…”
BackgroundInfluentialModels and Analogies in Science
Ardley, G. (1965) · Philosophical Studies · doi:10.5840/philstudies19651438 · Cited by 1,770
Flowing Waters or Teeming Crowds: Mental Models of Electricity
Dedre Gentner, C., & Gentner, D. R. (2014) · Psychology Press eBooks · doi:10.4324/9781315802725-10 · Cited by 699
Self-citationOrtony, A. (1979) · Psychological Review · doi:10.1037/0033-295x.86.3.161 · Cited by 687
On understanding nonliteral speech: Can people ignore metaphors?
Glucksberg, S., Gildea, P. M., & Bookin, H. B. (1982) · Journal of Verbal Learning and Verbal Behavior · doi:10.1016/s0022-5371(82)90467-4 · Cited by 426
A model for analogical reasoning
Rumelhart, D. E., & Abrahamson, A. A. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90023-6 · Cited by 260
Are Scientific Analogies Metaphors
Gentner, D. (1981) · Defense Technical Information Center (DTIC) · Cited by 248
Self-citationImages and models, similes and metaphors
Miller, G. A. (1993) · Cambridge University Press eBooks · doi:10.1017/cbo9781139173865.019 · Cited by 238
Moore, J. J. A., & Newell, A. (2018) · Figshare · doi:10.1184/r1/6606152 · Cited by 117
Research works printed but not linked: 7
- Rumelhart, D. E., &Norman. D. A. Analogical processes in learning. In J. R. Anderson (Ed.), Cognirive skills and fheir acquisifion. Hillsdale, NJ: Lawrence Erlbaum Associates, 1981.
- Schustack, M. W.. & Anderson. J. R. Effects of analogy to prior knowledge on memory for new information. Journal of Verbal Learning and Verbal Behavior, 1979, 18, 565-583.
- Steels. L. An applicaiive view of object oriented programming (MIT A.I. Memo No. 15). Cambridge, MA: Massachusetts Institute of Technology, March 1982.
- Stevens, A., Collins, A., & Goldin, S. E. Misconceptions in student's understanding. Journal o/Man-Machine Sfudies. 1979, II. 145-156.
- Tourangeau, R., & Sternberg, R. J. Aptness in metaphor. Cogniriue Psychology, 1981, 13, 27-55.
- Tversky, A. Features of similarity. Psychological Review, 1977, 84, 327-352.
- Winston, P. H. Learning and reasoning by analogy. CACM, 1980. 23, No. 12. Winston, P. H. Learning new principles from precedenrs and exercises. (MIT Artificial Intelli- gence Memo No. 632). Cambridge, MA: Massachusetts Institute of Technology, May 1981.
Cited by
Sorted by citations
Items 201–300 of 884
Context, cortex, and associations: a connectionist developmental approach to verbal analogies
Kollias, P., & McClelland, J. L. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00857 · Cited by 19
Comparison and Explanation of Multiple Strategies
Star, J. R., Rittle‐Johnson, B., & Durkin, K. L. (2016) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/2372732216655543 · Cited by 17
A broad view of cognitive linguistics
Kövecses, Z. (2005) · Acta Linguistica Hungarica · doi:10.1556/aling.52.2005.2-3.2 · Cited by 18
Cánovas, C. P., Valenzuela, J., & Santiago, J. (2015) · Psychology of Aesthetics Creativity and the Arts · doi:10.1037/aca0000024 · Cited by 18
Moody, D. L. (2003) · Informing Science The International Journal of an Emerging Transdiscipline · doi:10.28945/512 · Cited by 18
Rocha, K., Lussier, C. M., & Atit, K. (2022) · Cognitive Research Principles and Implications · doi:10.1186/s41235-022-00377-7 · Cited by 19
Nature as relationship partner: an old frame revisited
Antal, M., & Drews, S. (2015) · Environmental Education Research · doi:10.1080/13504622.2014.971715 · Cited by 19
The Affective Dimension of Analogy
Harrison, A. G. (2006) · Springer eBooks · doi:10.1007/1-4020-3830-5_5 · Cited by 17
Annually Laminated Lake Sediments
Bernd Zolitschka, A., & Tylmann, W. (2020) · MDPI eBooks · doi:10.3390/books978-3-03928-787-1 · Cited by 16
Effects Of Conceptual Understanding, Math And Visualization Skills On Problem Solving In Statics
Higley, K., Litzinger, T., Meter, P. N. V., et al. (2020) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--2382 · Cited by 16
Hidayat, R., & Evendi, E. (2022) · International Journal of Essential Competencies in Education · doi:10.36312/ijece.v1i2.1069 · Cited by 16
Alessandroni, N. (2016) · Integrative Psychological and Behavioral Science · doi:10.1007/s12124-016-9373-3 · Cited by 16
Deep Analogical Inference as the Origin of Hypotheses
Blokpoel, M., Wareham, T., Haselager, P., Toni, I., & van Rooij, I. (2019) · The Journal of Problem Solving · doi:10.7771/1932-6246.1197 · Cited by 17
Student assumptions and mental models encountered in IR spectroscopy instruction
Wright, L. C., & Oliver-Hoyo, M. T. (2019) · Chemistry Education Research and Practice · doi:10.1039/c9rp00113a · Cited by 16
7 Morphological analogy: Only a beginning
Goldsmith, J. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0007 · Cited by 17
Neural structure mapping in human probabilistic reward learningPreprint
Luyckx, F., Nili, H., Spitzer, B., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/366757 · Cited by 16
Thinking as Analogy-Making: Toward a Neural Process Account of General Intelligence
Theves, S. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1555-24.2025 · Cited by 15
In-Context Analogical Reasoning with Pre-Trained Language Models
Hu, X., Storks, S., Lewis, R. L., & Chai, J. Y. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.109 · Cited by 32
Farheen, A., Martin, N., & Lewis, S. E. (2023) · Chemistry Education Research and Practice · doi:10.1039/d3rp00173c · Cited by 17
Liang, C., & Forbus, K. D. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v29i1.9218 · Cited by 15
Hauser, D., & Fleming, M. E. (2021) · Science Communication · doi:10.1177/10755470211031246 · Cited by 21
El desarrollo regional y la sostenibilidad: revisión sistemática y análisis bibliométrico
Rincon, J. C. S., León, J. A. P., & Monsalve, E. J. B. (2021) · Revista Universidad y Empresa · doi:10.12804/revistas.urosario.edu.co/empresa/a.10403 · Cited by 21
Young Children's Spontaneous Personification as Analogy
Inagaki, K., & Hatano, G. (1987) · Child Development · doi:10.2307/1130542 · Cited by 188
Imitative problem solving: Why transfer of learning often fails to occur
Robertsonnm, I. (2000) · Instructional Science · doi:10.1023/a:1003884601109 · Cited by 15
English for Vocational Purposes
Coxhead, A., Parkinson, J., Mackay, J., & McLaughlin, E. (2019) · Routledge eBooks · doi:10.4324/9780429449932 · Cited by 23
EXPLORING THE IMPACT OF GENERATIVE STIMULI ON THE CREATIVITY OF DESIGNERS IN COMBINATIONAL DESIGN
Wang, D., & Han, J. (2023) · Proceedings of the Design Society · doi:10.1017/pds.2023.181 · Cited by 14
Metaphor Detection via Explicit Basic Meanings Modelling
Li, Y., Wang, S., Lin, C., et al. (2023) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.18653/v1/2023.acl-short.9 · Cited by 14
A Conceptual Blending Approach to the Generation of Cognitive Scripts for Interactive Narrative
Permar, J., & Magerko, B. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v9i4.12621 · Cited by 14
The nature of creativity: cognitive and confluence perspectives
Mégalakaki, O., Craft, A., & Cremin, T. (2018) · Electronic Journal of Research in Educational Psychology · doi:10.25115/ejrep.v10i28.1548 · Cited by 17
From Ronchamp by Sledge: On the Pragmatics of Object References
Stacey, M., Eckert, C. M., & Earl, C. (2022) · CRC Press eBooks · doi:10.1201/9780429182433-27 · Cited by 14
On the activation of sensorimotor systems during the processing of emotionally-laden stimuli
Marmolejo‐Ramos, F., & Dunn, J. C. (1969) · Universitas Psychologica · doi:10.11144/javeriana.upsy12-5.assp · Cited by 14
Extending requirement specifications using analogy
Pisan, Y. (2000) · Proceedings/Proceedings - International Conference on Software Engineering · doi:10.1145/337180.337190 · Cited by 14
A Symbolic-Connectionist Model of Relation Discovery
Doumas, L. A. A., Hummel, J. E., & Holyoak, K. J. (2004) · PsycEXTRA Dataset · doi:10.1037/e537052012-519 · Cited by 14
Baden‐Fuller, C. W. F., Giudici, A., & Morgan, M. S. (2017) · Academy of Management Proceedings · doi:10.5465/ambpp.2017.90 · Cited by 14
Srinivasan, M., & Carey, S. E. (2019) · doi:10.31234/osf.io/vpbwa · Cited by 14
Zhou, Q., Deng, J., Liu, Y., Wang, Y., Xia, Y., Ou, Y., Lu, Z., Ma, S., Li, S., & Xu, Y. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713935 · Cited by 15
Argumentation by Analogy and Weighing of Reasons
Alhambra, J. (2022) · Informal Logic · doi:10.22329/il.v42i4.7143 · Cited by 13
On the multiple roles of ontologies in explanations for neuro-symbolic AI
Confalonieri, R., & Guizzardi, G. (2024) · Neurosymbolic Artificial Intelligence · doi:10.3233/nai-240754 · Cited by 15
Analogical Classifiers: A Theoretical Perspective
Hug, N., Prade, H., Gilles, R., et al. (2016) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-61499-672-9-689 · Cited by 13
Human-Like Sketch Object Recognition via Analogical Learning
Chen, K., Rabkina, I., McLure, M. D., & Forbus, K. D. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33011336 · Cited by 17
The RK processor: A program for analysing metaphor and word feature-listing data
Reid, J. N., & Katz, A. N. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01564-y · Cited by 11
Effects of figural and numerical presentation formats on growing pattern performance
Mielicki, M. K., Fitzsimmons, C. J., Woodbury, L. H., Marshal, H., Zhang, D.-K., Rivera, F., & Thompson, C. A. (2021) · Journal of Numerical Cognition · doi:10.5964/jnc.6945 · Cited by 11
Accelerating Innovation Through Analogy Mining
Hope, T., Chan, J., Kittur, A., & Shahaf, D. (2018) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/736 · Cited by 13
Can Analogy Help in Science Education Research?
Aubusson, P. J. (2006) · Springer eBooks · doi:10.1007/1-4020-3830-5_14 · Cited by 13
Gholson, B., Dattel, A. R., Morgan, D. T., & Eymard, L. A. (1989) · Child Development · doi:10.1111/j.1467-8624.1989.tb03548.x · Cited by 13
Wang, Q. (2018) · Chinese Journal of Applied Linguistics · doi:10.1515/cjal-2018-0004 · Cited by 12
He, G., Balayn, A., Buijsman, S., Yang, J., & Gadiraju, U. (2022) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v10i1.21990 · Cited by 12
Shao, Z., Yuan, S., Gao, L., He, Y., Yang, D., & Chen, S. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714313 · Cited by 13
Richter, M. M. (2008) · Studies in computational intelligence · doi:10.1007/978-3-540-73180-1_2 · Cited by 12
Action Recognition From Skeleton Data via Analogical Generalization Over Qualitative Representations
Chen, K., & Forbus, K. D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11328 · Cited by 12
Guarino, K. F., & Wakefield, E. M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.575628 · Cited by 15
La traducción científico-técnica y la terminología en la sociedad de la información
Alcina, A., Pérez, S. G., & Martín, R. M. (2002) · Universitat Jaume I eBooks · doi:10.6035/estudistraduccio.2002.10 · Cited by 12
Limits on Simulation Approaches in Intuitive PhysicsPreprint
Ludwin-Peery, E., Bramley, N. R., Davis, E., et al. (2021) · doi:10.31234/osf.io/xhzuc · Cited by 12
Jiayang, C., Qiu, L., Chan, T., Fang, T., Wang, W., Chan, C., Ru, D., Guo, Q., Zhang, H., Song, Y., et al. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.706 · Cited by 31
Fang, D., Zhang, G., Yang, X., & Liu, Y. (2024) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2024.2379312 · Cited by 12
Ferragud, C. B. G., Portolés, J. J. S., & López, V. S. (2012) · Revista de Psicodidáctica · doi:10.1387/revpsicodidact.5533 · Cited by 11
Analogical Dialogue Acts: Supporting Learning by Reading Analogies in Instructional Texts
Barbella, D., & Forbus, K. D. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v25i1.7835 · Cited by 11
Promoting spontaneous analogical transfer by idealizing target representations
Trench, M., Tavernini, L. M., & Goldstone, R. L. (2023) · Memory & Cognition · doi:10.3758/s13421-023-01411-9 · Cited by 11
Sultan, O., & Shahaf, D. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.232 · Cited by 19
A Unifying Approach to High- and Low-Level Cognition
Peter König, B., Kühnberger, K., & Kietzmann, T. C. (2013) · De Gruyter eBooks · doi:10.1515/9783110313680.117 · Cited by 14
HIDIR, M., & Körhasan, N. D. (2018) · Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi · doi:10.17522/balikesirnef.506455 · Cited by 11
The Production of Metaphoric Expressions in Spontaneous Speech: A Controlled-Setting Experiment
Flor, M., & Hadar, U. (2004) · Metaphor and Symbol · doi:10.1207/s15327868ms2001_1 · Cited by 11
Harrison, A. G., & JONG, O. D. (2005) · Springer eBooks · doi:10.1007/1-4020-3673-6_28 · Cited by 11
Why and How to Learn Why: Analysis‐based Generalization of Procedures
Lewis, C. (1988) · Cognitive Science · doi:10.1207/s15516709cog1202_3 · Cited by 98
Integrating analogical mapping and general problem solving: the path-mapping theory
Salvucci, D. D. (2001) · Cognitive Science · doi:10.1016/s0364-0213(00)00035-5 · Cited by 11
Comprehending scientific metaphors in the bilingual brain: Evidence from event-related potentials
Shen, L., Li, X., Huang, S., et al. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1037525 · Cited by 10
Ferragud, C. B. G., Portolés, J. J. S., & López, V. S. (2012) · Enseñanza de las Ciencias Revista de investigación y experiencias didácticas · doi:10.5565/rev/ec/v31n1.782 · Cited by 10
Testing and Training Analogical Relational Responding in Children With and Without Autism
Kirsten, E. B., Stewart, I., & McElwee, J. (2022) · The Psychological Record · doi:10.1007/s40732-021-00493-8 · Cited by 7
4 Resolving pattern conflict: Variation and selection in phonology and morphology
Wedel, A. B. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0004 · Cited by 10
Espaces Mentaux et Intégration Conceptuelle : Retour sur la Constitution de Théories Soeurs
Fortis, J.-M. (2018) · Cognitextes · doi:10.4000/cognitextes.1111 · Cited by 10
The effect of surface similarities on the retrieval of analogous daily-life events
Olguín, M. V., Tavernini, L. M., Trench, M., et al. (2022) · Memory & Cognition · doi:10.3758/s13421-022-01279-1 · Cited by 10
Children’s Motor Learning and Working Memory: The Role of Visual and Verbal Analogy Learning
Ramezani, F., Saemi, E., & Doustan, M. (2022) · Polish Journal of Sport and Tourism · doi:10.2478/pjst-2022-0008 · Cited by 10
An Empirical Evaluation of Visual Metaphors in the Animation of Roles of Variables
Stützle, T., & Sajaniemi, J. (2005) · Informing Science and IT Education Conference · doi:10.28945/2886 · Cited by 10
Towards Understanding Successful Novice Example Use in Blocks-Based Programming
Ichinco, M., Harms, K., & Kelleher, C. (2017) · Journal of Visual Languages and Sentient Systems · doi:10.18293/vlss2017-012 · Cited by 10
Modeling Cross-Cultural Performance on the Visual Oddity Task
Lovett, A., Lockwood, K., & Forbus, K. D. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-87601-4_27 · Cited by 10
Building Robots with Analogy-Based Anticipation
Petkov, G., Naydenov, T., Grinberg, M., et al. (2007) · Springer eBooks · doi:10.1007/978-3-540-69912-5_7 · Cited by 10
Analogical approach to specification derivation
Miriyala, K., & Harandi, M. T. (1989) · doi:10.1145/75199.75230 · Cited by 10
Structure Learning and the Parietal CortexPreprint
Summerfield, C., Luyckx, F., & Sheahan, H. (2019) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/zfxj2 · Cited by 8
Ngu, B. H., & Phan, H. P. (2024) · Asian Journal for Mathematics Education · doi:10.1177/27527263241266765 · Cited by 10
Novitskaya, I. V. (2019) · Yazyk i kul tura · doi:10.17223/19996195/46/5 · Cited by 9
The Neural Correlates of Analogy Component Processes
Parsons, J., & Davies, J. (2022) · Cognitive Science · doi:10.1111/cogs.13116 · Cited by 11
VASR: Visual Analogies of Situation Recognition
Bitton, Y., Yosef, R., Strugo, E., Shahaf, D., Schwartz, R., & Stanovsky, G. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i1.25096 · Cited by 17
Searching and Analysis of Interface and Visualization Metaphors
Lifschutz, V., Mihkail, O., Yu., A., et al. (2008) · InTech eBooks · doi:10.5772/5880 · Cited by 9
Thompson, C. A., Taber, J. M., Sidney, P. G., Fitzsimmons, C. J., Mielicki, M. K., Matthews, P. G., Schemmel, E., Simonovic, N., Foust, J. L., Aurora, P., et al. (2020) · doi:10.31234/osf.io/hukyv · Cited by 9
Differential effects of semantic distance, distractor salience, and relations in verbal analogy
Jones, L. L., Kmiecik, M. J., Irwin, J. L., & Morrison, R. G. (2022) · Psychonomic Bulletin & Review · doi:10.3758/s13423-022-02062-8 · Cited by 10
Miller, A. R., Jończyk, R., Zaharchuk, H. A., & van Hell, J. G. (2025) · Psychophysiology · doi:10.1111/psyp.70066 · Cited by 8
The Development of Simile Comprehension: From Similarity to Scalar Implicature
Long, M. R., Shukla, V., & Rubio‐Fernández, P. (2021) · Child Development · doi:10.1111/cdev.13507 · Cited by 7
What is category theory to cognitive science? Compositional representation and comparison
Phillips, S. D. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1048975 · Cited by 6
Маммино, Л. (2023) · Physical Sciences Reviews · doi:10.1515/psr-2022-0318 · Cited by 7
La metáfora organizacional: alternativa de entendimiento procedente de otras ciencias
Restrepo, L. A. M., Restrepo, I. A. M., & Domínguez, Ó. F. C. (2009) · Revista Facultad de Ciencias Económicas · doi:10.18359/rfce.2282 · Cited by 8
City of physics—analogies to increase cognitive coherence in physics learning
Tabor-Morris, A., Froriep, K., Briles, T. M., et al. (2009) · Physics Education · doi:10.1088/0031-9120/44/2/013 · Cited by 8
An Empirical Evaluation of Visual Metaphors in the Animation of Roles of Variables
Stützle, T., & Sajaniemi, J. (2005) · Informing Science The International Journal of an Emerging Transdiscipline · doi:10.28945/489 · Cited by 8
8 Expanding Analogical Modeling into a general theory of language prediction
Skousen, R. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0008 · Cited by 8
Knowledge structures for natural language generation
Jacobs, P. S. (1986) · doi:10.3115/991365.991527 · Cited by 8
Turner, M. (1999) · Lecture notes in computer science · doi:10.1007/3-540-48834-0_2 · Cited by 8
Hochmann, J., & Papeo, L. (2021) · doi:10.31234/osf.io/hm49p · Cited by 8
Deep analogical inference as the origin of hypotheses
(2018) · doi:10.31234/osf.io/9w5dy · Cited by 8
Yuan, S., Chen, J., Ge, X., Xiao, Y., & Yang, D. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.160 · Cited by 15
ARN: Analogical Reasoning on Narratives
Sourati, Z., Ilievski, F., Sommerauer, P., & Jiang, Y. (2024) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00688 · Cited by 14
Analogy competence for science teachers
Eriksson, S., Gericke, N., & Thörne, K. E. (2024) · Studies in Science Education · doi:10.1080/03057267.2024.2434797 · Cited by 7
Metadata
- Authors
- GENTNER, D.
- Corresponding author
- GENTNER, D
- ORCID
- GENTNER, D
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 1983-06
- Volume
- 7
- Issue
- 2
- Pages
- 155-170
- ISSN
- 0364-0213 (ISSN-L)
- OpenAlex
- W4229954498
- Cited by
- 816
- References
- 12
- Citations by year
- 2026: 60 · 2025: 55 · 2024: 69 · 2023: 63 · 2022: 50 · 2021: 53 · 2020: 45 · 2019: 38 · 2018: 27 · 2017: 22 · 2016: 28 · 2015: 23 · 2014: 30 · 2013: 17 · 2012: 14
- FWCI
- 5.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cognitive Science (publishedVersion)
- Topics
- Social Sciences › Linguistics and Language › Language, Metaphor, and Cognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Keywords
- structure-mapping theory, analogy, analogical reasoning, mapping rules, knowledge representation, systematicity, higher-order relations, abstraction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
