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Record W2941887489 · doi:10.24095/hpcdp.39.4.02f

Aperçu - Les effets des changements climatiques sur la santé et le bien-être dans les régions rurales et éloignées au Canada : synthèse documentaire

2019· article· fr· W2941887489 on OpenAlexafffundvenueabout
Amy Kipp, Ashlee Cunsolo, Kelly Vodden, Nia King, Sean Manners, Sherilee L. Harper

Bibliographic record

VenuePromotion de la santé et prévention des maladies chroniques au Canada · 2019
Typearticle
Languagefr
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsQueen's UniversityMemorial University of NewfoundlandUniversity of Alberta
FundersNatural Resources Canada
KeywordsPolitical scienceHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

Cet article présente une synthèse de la version préliminaire du chapitre à venir « Collectivités rurales et éloignées » de l’Évaluation nationale des changements climatiques du gouvernement du Canada, et il répertorie les principales préoccupations en matière de santé exposées dans la littérature sur les changements climatiques à propos des régions rurales et éloignées, ainsi que les stratégies d’adaptation actuelles et celles à mettre en place. Cet aperçu, fondé sur un processus de recherche systématique, souligne l’importance de tenir compte des composantes socioculturelles, économiques et géographiques spécifiques de ces régions ainsi que de l’expertise dont disposent déjà leurs habitants et leurs collectivités si l’on veut contribuer à la santé et au bien-être des populations qui subissent les effets nocifs des changements climatiques.

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)0.009
metaresearch head score (Gemma)0.025
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: Review · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0040.003
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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
GenreReview

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
Published2019
Admission routes4
Has abstractyes

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