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Record W4388673085 · doi:10.46747/cfp.6911e216

Réfutation des mythes entourant le dépistage

2023· article· fr· W4388673085 on OpenAlexaffvenue
Guylène Thériault, Donna L. Reynolds, Roland Grad, James A. Dickinson, Harminder Singh, Olga Szafran, Viola Antao, Neil R. Bell

Bibliographic record

VenueCanadian Family Physician · 2023
Typearticle
Languagefr
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of AlbertaCancerCare ManitobaPublic Health OntarioUniversité du Québec en Outaouais
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Le dépistage est souvent considéré comme un effort noble et valable. La plupart des patients croient que le dépistage ne cause pas de préjudices et ne peut produire que des bénéfices pour la santé[1][1]. En tant que médecins, nous savons que ce n’est pas le cas. Cet article a pour but de

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.031
GPT teacher head0.258
Teacher spread0.227 · 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 designOther design
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

Citations2
Published2023
Admission routes2
Has abstractyes

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