MétaCan
Menu
Back to cohort
Record W2310461224

La fin de l’utilisation abusive commence par les médecins: Choisir avec soin

2016· article· fr· W2310461224 on OpenAlexaff
Kimberly Wintemute, Karen McDonald, Tai Huynh, Ciara Pendrith, Lynn Wilson

Bibliographic record

VenuePubMed Central · 2016
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversité LavalCentre de Santé et de Services Sociaux de la MontagneThe Society of Obstetricians and Gynaecologists of CanadaNorth York General Hospital
Fundersnot available
KeywordsHumanitiesMedicinePsychologyPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Les medecins connaissent universellement le contrat social stipulant qu’en premier lieu, ils ne doivent pas causer de prejudices. Les examens, les traitements et les interventions inutiles nuisent aux patients comme il est si eloquemment demontre dans l’article intitule « Rational test

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.101
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.101
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.358
GPT teacher head0.446
Teacher spread0.088 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Explore more

Same venuePubMed CentralSame topicHealthcare cost, quality, practicesFrench-language works237,207