Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 2,350

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Computer science as empirical inquiry: symbols and search

Newell, Allen, Simon, Herbert A.·1976·Communications of the ACM
DOI 10.1145/360018.360022
Open this paper in CoChat — free account

Abstract

Computer science is the study of the phenomena surrounding computers. The founders of this society understood this very well when they called themselves the Association for Computing Machinery. The machine—not just the hardware, but the programmed, living machine—is the organism we study.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/360018.360022

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 3

  1. 10.1145/367177.367199 · DOI · Paper page
  2. McCulloch W.S. {1961}. What is a number that a man may know it and a man that he may know a number. General Semantics Bulletin Nos. 26 and 27 (1961) 7-18. McCulloch W.S. {1961}. What is a number that a man may know it and a man that he may know a number. General Semantics Bulletin Nos. 26 and 27 (1961) 7-18.
  3. Nilsson N.J. {1971}. Problem Solving Methods in Artificial Intelligence. McGraw-Hill New York. Nilsson N.J. {1971}. Problem Solving Methods in Artificial Intelligence. McGraw-Hill New York.

Cited by

See all 2,350

Metadata

Authors
Newell, A., & Simon, H. A.
Venue
Communications of the ACM
Publisher
Association for Computing Machinery (ACM)
Published
1976-03
Volume
19
Issue
3
Pages
113-126
ISSN
  • 0001-0782 (ISSN-L)
  • 1557-7317
DOI
10.1145/360018.360022
OpenAlex
W1968079292
Cited by
2,350
References
2
FWCI
26.74
Type
journal article
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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.

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.