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Record W6908524149 · doi:10.26071/b35efc0a-6d56-4fe5

La grande baie Saint-Nicolas - Caractérisation des habitats littoraux d'importance de la rive nord de l'estuaire maritime du Saint Laurent

2025· dataset· fr· W6908524149 on OpenAlexaboutno aff

Bibliographic record

VenueOGSL repository · 2025
Typedataset
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCoastal zoneHabitatPacific oceanBenthic habitatGeolocation

Abstract

fetched live from OpenAlex

Un projet de caractérisation des habitats littoraux d’importance de la rive nord de l’estuaire maritime du Saint-Laurent a été subventionné pour une période de 4 ans (2023-2027). Ce projet a pour but de générer des données écologiques de référence pour tracer un portrait global de l’état des habitats littoraux le long de la rive nord de l'estuaire maritime. Ce jeu de données couvre le secteur de la grande baie Saint-Nicolas (municipalité de Franquelin). Afin d'améliorer les connaissances de cet écosystème, des inventaires floristiques et fauniques (ichtyologiques) ont été réalisés et les différents facteurs abiotiques caractérisés. Ce projet fait partie du Programme sur les données environnementales côtières de référence de Pêche et Océans Canada.

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)0.003
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 score0.272
Threshold uncertainty score0.548

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.009

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 head0.259
Teacher spread0.250 · 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
Published2025
Admission routes1
Has abstractyes

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Same venueOGSL repositoryFrench-language works237,207