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Record W6926278385 · doi:10.25318/1010012401-fra

Statistiques boursières, Canada et États-Unis, Banque du Canada

2019· dataset· fr· W6926278385 on OpenAlexaffabout

Bibliographic record

VenueStatistics Canada Dissemination · 2019
Typedataset
Languagefr
FieldArts and Humanities
Topiclinguistics and terminology studies
Canadian institutionsBank of Canada
Fundersnot available
KeywordsContext (archaeology)

Abstract

fetched live from OpenAlex

Ce tableau contient 14 séries. Les données commencent en 1953 (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 (1 élément : Canada), Statistiques boursières (14 éléments : Bourse de Toronto, valeur des actions négociées; Bourse de Toronto, volume des actions négociées; Actions ordinaires des États-Unis, Dow-Jones, industriels, haut; Actions ordinaires des États-Unis, Dow-Jones, industriels, bas; ...).

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)0.009
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.040
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.036
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0400.032

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 head0.011
GPT teacher head0.253
Teacher spread0.243 · 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
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 routes2
Has abstractyes

Explore more

Same venueStatistics Canada DisseminationSame topiclinguistics and terminology studiesFrench-language works237,207