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Record W7100236301

Commentary CMAJ

2016· article· en· W7100236301 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)RehabilitationAssociation (psychology)Primary careMedical ethicsMedical care
DOInot available

Abstract

fetched live from OpenAlex

All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Can adian Medical Association. 248 CMAJ, March 4, 2014, 186(4) © 2014 Canadian Medical Association or its licensors An independent medical evaluation(IME) is an assessment performed by aphysician who does not treat the patient. Disability insurers, employers or lawyers often request an IME when faced with uncertainty about the cause or nature of a claimed disability, or the functional status and/or rehabilitation potential of the claimant. Independent medical evaluators are retained by the requesting party; therefore, their relation-ship with the patient is different from the rela-tionship in the traditional physician–patient model. Because the primary responsibility of the independent medical evaluator is to provide a service for the hiring third party and not for

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0620.008

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 head0.089
GPT teacher head0.478
Teacher spread0.389 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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