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Record W4393791953 · doi:10.5281/zenodo.3256401

Test de DOI événementiel pour Espace temps

2019· dataset· fr· W4393791953 on OpenAlexaboutno aff
Jean-Robert Bisaillon

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typedataset
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Computer scienceGeology

Abstract

fetched live from OpenAlex

Production Formation aux métadonnées culturelles Variante Atelier de préparation Artiste principal Jean-Robert Bisaillon Artiste principal ISNI http://isni.org/isni/0000000466242395 Discipline Conférence Genre Artiste secondaire Artiste secondaire ISNI Promoteur Date 2019-06-25 Event Name (EN) Brainstorm your data Nom de l'événement (FR) Tempête de données Type d'événement Conférence Type d'événement détaillé URL de l'événement URL de l'événement Facebook DoorTime 14:30:00 BeginTime 15:00:00 AnnounceDateTime 11:00:00 PointOfSale ID Description billetterie Gratuit Description billetterie (alternative) OnsaleDate Nom du lieu Temps libre UN-LOCODE du lieu CA MTR Adresse rue 5605 Avenue de Gaspé #106 Adresse ville Montréal Adresse code postal H2T 2A4 Media Context (EN) Accroche médiatique (FR) Image (.jpg) Lead Performer Bio (EN) Bio de l'artiste principal (FR) Autre URL (1) http://tempslibre.coop/

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)0.003
metaresearch head score (Gemma)0.024
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 score0.048
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0480.043

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 head0.188
GPT teacher head0.296
Teacher spread0.109 · 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 routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicCultural Insights and Digital Impacts→French-language works237,207→