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Record W4235807568 · doi:10.24095/hpcdp.41.7/8.05f

Avis de publication - Registre canadien des tumeurs cérébrales (RCTC) : Rapport d'incidence (2013-2017) et de mortalité (2014-2018)

2021· article· fr· W4235807568 on OpenAlexvenueaboutno aff

Bibliographic record

VenuePromotion de la santé et prévention des maladies chroniques au Canada · 2021
Typearticle
Languagefr
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHumanitiesArt

Abstract

fetched live from OpenAlex

de données de l'état civil Décès, ce rapport fournit des renseignements complets sur l'incidence et la mortalité des tumeurs du système nerveux central (SNC) au Canada.Le rapport a été réalisé grâce à un partenariat entre l'Université de l'Alberta, la Fondation canadienne des tumeurs cérébrales et l'Agence de la santé publique du Canada.Le rapport fournit des estimations de l'incidence et de la mortalité selon le groupe histologique, le site d'origine, le comportement tumoral et les données démographiques (sexe, âge, géographie), ainsi qu'au fil du temps.

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)0.013
metaresearch head score (Gemma)0.049
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.078
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0120.021
Science and technology studies0.0020.001
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.004

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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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