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Record W2791715268 · doi:10.1097/paf.0000000000000392

Epidermis and Enamel

2018· article· en· W2791715268 on OpenAlexaff
Robert E. Barsley, Mark L. Bernstein, Paula C. Brumit, Robert B. J. Dorion, Gregory S. Golden, James M. Lewis, John D. McDowell, Roger D. Metcalf, David R. Senn, D Sweet, Richard A. Weems

Bibliographic record

VenueAmerican Journal of Forensic Medicine & Pathology · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsMedicineScrutinyTerminologyHarmRoot causeDentistryLawOperations management

Abstract

fetched live from OpenAlex

Critics describe forensic dentists' management of bitemark evidence as junk science with poor sensitivity and specificity and state that linkages to a biter are unfounded. Those vocal critics, supported by certain media, characterize odontologists' previous errors as egregious and petition government agencies to render bitemark evidence inadmissible. Odontologists acknowledge that some practitioners have made past mistakes. However, it does not logically follow that the errors of a few identify a systemic failure of bitemark analysis. Scrutiny of the contentious cases shows that most occurred 20 to 40 years ago. Since then, research has been ongoing and more conservative guidelines, standards, and terminology have been adopted so that past errors are no longer reflective of current safeguards. The authors recommend a comprehensive root analysis of problem cases to be used to determine all the factors that contributed to those previous problems. The legal community also shares responsibility for some of the past erroneous convictions. Currently, most proffered bitemark cases referred to odontologists do not reach courts because those forensic dentists dismiss them as unacceptable or insufficient for analysis. Most bitemark evidence cases have been properly managed by odontologists. Bitemark evidence and testimony remain relevant and have made significant contributions in the justice system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.442
Teacher spread0.395 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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