The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
(Mis)use of scientific measurements in forensic science
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In the citing paper
“As indicated, an important point made by [10] is that validation of Likelihood Ratio in the forensic field should take into account not only accuracy (if it is right or wrong assessment of match-mismatch) but also its calibration, i.e., the system capacity to make strong assessments.”
From Calibration of score based likelihood ratio estimation in automated forensic facial image comparison (2022) · cites this paper as [10]
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Citations
Cites
Orne, M. T. (1962) · American Psychologist · doi:10.1037/h0043424 · Cited by 4,041
Accuracy and reliability of forensic latent fingerprint decisions
Ulery, B. T., Hicklin, R. A., Buscaglia, J., & Roberts, M. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018707108 · Cited by 350
Flagged first, then by citations
Research works printed but not linked: 31
- Garrett, B.L. (in press). Autopsy of a Crime Lab. University of California Press..
- Howes, 2015, The communication of forensic science in the criminal justice system: a review of theory and proposed directions for research, Sci. Justice, 55, 145, 10.1016/j.scijus.2014.11.002 · DOI
- Lyon, 1996, Relevance ratio: evaluating the probative value of expert testimony in child sexual abuse cases, Cornell Law Rev., 82, 43
- Sangero, 2018, Safety from flawed forensic sciences evidence, Ga. State Univ. Law Rev., 34, 1129
- Haber, 2014, Experimental results of fingerprint comparison validity and reliability: a review and critical analysis, Sci. Justice, 54, 375, 10.1016/j.scijus.2013.08.007 · DOI
- Saks, 2005, The coming paradigm shift in forensic identification science, Science, 309, 892, 10.1126/science.1111565 · DOI
- Koehler, 2013, Proficiency tests to estimate error rates in the forensic sciences, Law Probab. Risk, 12, 89, 10.1093/lpr/mgs013 · DOI
- Cole, 2005, More than zero: accounting for error in latent fingerprint identification, J. Crim. Law Criminol., 95, 985
- Garrett, 2009, Invalid forensic science testimony and wrongful convictions, Va. Law Rev., 95, 1
- Murrie, 2019, Perceptions and estimates of error rates in forensic science, Forensic Sci. Int., 302, 10.1016/j.forsciint.2019.109887 · DOI
- Daubert, 1993, vol. 509, 579
- Meixner, 2014, The hidden Daubert factor: how judges use error rates in assessing scientific evidence, Wis. Law Rev., 1063
- Gatowski, 2001, Asking the gatekeepers: a national survey of judges on judging expert evidence in a post-Daubert world, Law Hum. Behav., 25, 433, 10.1023/A:1012899030937 · DOI
- United States v, 2001, Havvard, 260
- Capra, 2018, Symposium on forensic expert testimony, Daubert, and Rule 702, Fordham Law Rev., 86, 1463
- Dror, 2019, Cannot Decide": the fine line between appropriate inconclusive determinations VS. unjustifiably deciding not to decide, J. Forensic Sci., 64, 1, 10.1111/1556-4029.13854 · DOI
- McQuiston-Surrett, 2009, The testimony of forensic identification science: what expert witnesses say and what factfinders hear, Law Hum. Behav., 33, 436, 10.1007/s10979-008-9169-1 · DOI
- Dror, 2020, The Error in ‘Error Rate’: why error rates are so needed, yet so elusive, J. Forensic Sci., 65, 1034, 10.1111/1556-4029.14435 · DOI
- Kelley, 2020, How do latent print examiners perceive proficiency testing? An analysis of examiner perceptions, performance, and print quality, Sci. Justice, 60, 120, 10.1016/j.scijus.2019.11.002 · DOI
- Koehler, 2008, Fingerprint error rates and proficiency tests: what they are and why they matter, Hastings Law J., 59, 1077
- Pierce, 2020, Development and implementation of an effective blind proficiency testing program, J. Forensic Sci., 65, 809, 10.1111/1556-4029.14269 · DOI
- Jeanguenat, 2018, Human factors effecting forensic decision making: workplace stress and wellbeing, J. Forensic Sci., 63, 258, 10.1111/1556-4029.13533 · DOI
- Dror, 2020, Cognitive and human factors in expert decision making: six fallacies and the eight sources of bias, Anal. Chem., 92, 7998, 10.1021/acs.analchem.0c00704 · DOI · Paper page
- Cole, 2018, Fingerprints and miscarriages of justice: “other” types of error and a post-conviction right to database searching, Albany Law Rev., 81, 807
- Ulery, 2012, Repeatability and reproducibility of decisions by latent fingerprint examiners, PLoS, 7
- Langenburg, 2009, Testing for Potential contextual bias effects during the verification stage of the ACEV methodology when conducting fingerprint comparisons, J. Forensic Sci., 54, 571, 10.1111/j.1556-4029.2009.01025.x · DOI
- Keisler, 2018, Isolated pairs research study, AFTE Journal, 50, 56
- Lyons, 2009, The identification of consecutively manufactured extractors, AFTE Journal, 41, 246
- Dror, 2016, A hierarchy of expert performance (HEP), Journal of Applied Research in Memory and Cognition, 5, 121, 10.1016/j.jarmac.2016.03.001 · DOI · Paper page
- Bunch, 2003, A comprehensive validity study for the forensic examination of cartridge cases, AFTE Journal, 35, 201
- Smith, 2005, Cartridge case and bullet comparison validation study with firearms submitted in casework, AFTE Journal, 37, 130
Cited by
Sorted by citations
Calibration of score based likelihood ratio estimation in automated forensic facial image comparison
Rodriguez, A. M., Geradts, Z., & Worring, M. (2022) · Forensic Science International · doi:10.1016/j.forsciint.2022.111239 · Cited by 19
Understanding ‘error’ in the forensic sciences: A primer
Martire, K. A., Chin, J. M., Davis, C., Edmond, G., Growns, B., Gorski, S., Kemp, R. I., Lee, Z., Verdon, C. M., Jansen, G., et al. (2024) · Forensic Science International: Synergy · doi:10.1016/j.fsisyn.2024.100470 · Cited by 9
Metadata
- Authors
- Dror, I. E., & Scurich, N.
- Venue
- Forensic Science International: Synergy
- Publisher
- Elsevier BV
- Published
- 2020
- Volume
- 2
- Pages
- 333-338
- ISSN
- 2589-871X
- PMC
- PMC7770438
- Cited by
- 51
- References
- 2
- Language
- en
- Licence
- Funders
- Carnegie Mellon University
- University of Virginia
- Duke University
- National Institute of Standards and Technology
- Swarthmore College
- University of California, Irvine
- West Virginia University
- University of Pennsylvania
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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.
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