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Record W2808238728 · doi:10.7202/1047148ar

Les oiseaux marins nicheurs dans l’aire de coordination du parc marin du Saguenay–Saint-Laurent

2018· article· fr· W2808238728 on OpenAlexvenueaboutno aff
Jean‐François Rail

Bibliographic record

VenueLe Naturaliste canadien · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyForestryArt

Abstract

fetched live from OpenAlex

Dans l’aire de coordination du parc marin du Saguenay–Saint-Laurent, on compte 27 sites abritant des colonies actives d’oiseaux marins. Cette communauté compterait plus de 23 000 couples nicheurs appartenant à 8 espèces, dont 4 laridés et 3 alcidés, en plus du cormoran à aigrettes (Phalacrocorax auritus). Le goéland argenté (Larus argentatus) et le cormoran à aigrettes, de par leur abondance et leur répartition, sont sans doute les deux espèces les plus représentatives de l’aire d’étude. Quatre espèces sont tout près de la limite amont de leur aire de répartition dans le Saint-Laurent. Les effectifs de la plupart des espèces ont fluctué passablement depuis le milieu des années 1970, mais apparaissent maintenant relativement stables. Deux tendances plus récentes apparaissent cependant : la multiplication rapide du guillemot marmette (Uria aalge) et le déclin du guillemot à miroir (Cepphus grylle) jusqu’à un niveau très bas. Des recommandations sont émises pour la conservation et la gestion de cette communauté.

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)0.000
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: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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".

Quick stats

Citations4
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueLe Naturaliste canadienSame topicFire effects on ecosystemsFrench-language works237,207