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Record W4291710134 · doi:10.46747/cfp.6808573

Le racisme environnemental au Canada

2022· article· fr· W4291710134 on OpenAlexaffvenueabout
Maya Venkataraman, Stefan Grzybowski, Darlene Sanderson, Jordie A. J. Fischer, Arlin Cherian

Bibliographic record

VenueCanadian Family Physician · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsThompson Rivers UniversityUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesGynecologyArtMedicine

Abstract

fetched live from OpenAlex

> Vous êtes médecin de famille suppléant dans le Nord-Ouest ontarien. Votre prochain patient est un enfant de 6 ans qui souffre de fatigue chronique et de paresthésie aux extrémités. À l’examen physique, vous découvrez aussi une déficience auditive bilatérale[1][1]. Vous vous rappelez

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0160.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0150.000

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 designObservational
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

Citations1
Published2022
Admission routes3
Has abstractyes

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