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Record W6964843548 · doi:10.26071/ogsl-8f0da3ad-6ae9

Localisations GPS de fous de Bassan nichant sur l'Île-Bonaventure saison 2017

2017· dataset· fr· W6964843548 on OpenAlexaboutno aff

Bibliographic record

VenueOGSL repository · 2017
Typedataset
Languagefr
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsCoastal zoneContext (archaeology)Global Positioning System

Abstract

fetched live from OpenAlex

Depuis 2012, le Laboratoire d'ornithologie marine de Rimouski (https://ornithologiemarine.wixsite.com/lomr/david-pelletier) a mis en place un programme de suivi annuel du comportement alimentaire des fous de Bassan (Morus bassanus) nichant dans le parc national de l'Île-Bonaventure-et-du-Rocher-Percé (plus spécifiquement sur l'île Bonaventure). Le LOMR est dirigé par Magella Guillemette (professeur à l'Université du Québec à Rimouski) en collaboration avec David Pelletier (professeur au Cégep de Rimouski). Plusieurs dizaines d'étudiant.e.s des niveaux collégial et universitaire (1er, 2e et 3e cycles) ont participé la collecte de ces données. Les données présentes dans cette base de données sont celles de 2017, mais celles au delà de 2017 peuvent être demandées au LOMR en contactant les propriétaires des données. Les localisations ont été enregistrées à l'aide de consignateurs de données GPS, programmés à une fréquence de 5 ou 10 minutes (suivant les années) et fixés sur la queue des oiseaux avec du ruban adhésif blanc de grade marin de marque Tesa.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.033
GPT teacher head0.269
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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