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Record W6964043830 · doi:10.25318/1310003801-fra

Incidence du cancer (fichier du RCC de septembre 2002), selon certains sièges de cancer et le sexe, moyenne de trois ans, Canada, provinces, territoires et régions sociosanitaires (limites de juin 2003)

2019· dataset· fr· W6964043830 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2019
Typedataset
Languagefr
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsIncidence (geometry)CancerCancer incidenceLung cancer

Abstract

fetched live from OpenAlex

Ce tableau contient 3069 séries, avec des données pour les années 1997 - 1998 (il n'y a pas nécessairement de données pour toutes les années pour l'ensemble des combinaisons). Ce tableau contient des données telles que décrites par les dimensions suivantes (les combinaisons ne sont pas toutes disponibles): Géographie (93 éléments: Canada; Terre-Neuve-et-Labrador;Health and Community Services St. John's Region; Terre-Neuve-et-Labrador;Health and Community Services Eastern Region; Terre-Neuve-et-Labrador ...), Sexe (3 éléments: Hommes et femmes; Hommes; Femmes ...), Certains sièges de cancer (CIM-9) (5 éléments: Toutes les tumeurs malignes (cancers);Cancer du sein; Cancer colorectal; Cancer du poumon ...), Caractéristiques (3 éléments: Incidence du cancer; Limite inférieure de l'intervalle de confiance de 95 %; incidence du cancer; Limite supérieure de l'intervalle de confiance de 95 %; incidence du cancer ...).

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.248
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

Explore more

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