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Record W4395322601 · doi:10.15468/5kjxva

DFO Quebec Region Magdalen Islands Sea Scallop Survey 2021-2022

2023· dataset· fr· W4395322601 on OpenAlexaffabout
Claude Nozères

Bibliographic record

VenueGlobal Biodiversity Information Facility · 2023
Typedataset
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsScallopOceanographyGeographyFisheryBiologyGeology

Abstract

fetched live from OpenAlex

A sea scallop (Placopecten magellanicus) research survey using a dredge was carried out by DFO in 2021 and 2022 in the Magdalen Islands (Fishing Area 20). The main objective of this research survey was to assess sea scallop stocks. Another objective was to document the associated taxa in the catch associated with scallop habitat according to a fixed sampling plan. Occurrences by species (or taxon) are presented by station. Starting in 2021, catches were weighed, and specimens photographed, with information available upon request. / Un relevé de recherche sur le pétoncle géant (Placopecten magellanicus) effectué à l'aide d'une drague a été réalisée par MPO en 2021 et 2022 aux îles de la Madeleine (zone de pêche 20). L'objectif principal de ce relevé de recherche était d'évaluer les stocks du pétoncle géant. Un autre objectif était de documenter les taxons associés dans la capture associée à l'habitat de pétoncle selon un plan d'échantillonnage fixe. Les occurrences par espèce (ou taxon) sont présentées par station. À partir de 2021, les captures étaient pesées et des spécimens photographiés, avec l’information disponible sur demande.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.002

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 head0.039
GPT teacher head0.290
Teacher spread0.251 · 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
Published2023
Admission routes2
Has abstractyes

Explore more

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