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2002· article· en· W4245541203 on OpenAlexaboutno aff

Bibliographic record

VenueAMA guides newsletter · 2002
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMemory impairmentGlasgow Coma ScaleCognitive impairmentFunctional impairmentRating scalePsychologyMedicinePsychiatryCognitionDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Different jurisdictions use the AMA Guides to the Evaluation of Permanent Impairment ( AMA Guides ) for different purposes, and this article reviews a specific jurisdictional definition in the Province of Ontario of catastrophic impairment that incorporates the AMA Guides . In Ontario, a whole person impairment (WPI) exceeding 54% or a mental or behavioral impairment of Class 4 or 5 qualifies the individual for catastrophic benefits, and individuals who do not meet the test receive a lesser benefit. By inference, this establishes a parity threshold among dissimilar injuries and dissimilar outcome assessment scales for benefits. In Ontario, the Glasgow Coma Scale (GCS) identifies patients who have a high probability of death or of severely disabled survival. The GCS recognizes gradations of vegetative state and disability, but translating the gradations for rating individual impairment on ordinal scales into a method of assessing percentage impairments cannot be done reliably, as explained in the AMA Guides, Fifth Edition. The AMA Guides also notes that mental and behavioral impairment in Class 4 (marked impairment) or 5 (extreme impairment) indicates “catastrophic impairment” by significantly impeding useful functioning (Class 4) or significantly impeding useful functioning and implying complete dependency on another person for care (Class 5). Translating the AMA Guides guidelines into ordinal scales cannot be done reliably.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Empirical
Teacher disagreement score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0060.004

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 head0.042
GPT teacher head0.278
Teacher spread0.237 · 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
Published2002
Admission routes1
Has abstractyes

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