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Record W6906075589 · doi:10.15468/vvrs6u

DFO Quebec Region Biodiversity of the Arctic surfclam hydraulic dredge survey in the St. Lawrence Estuary (2017)

2022· dataset· fr· W6906075589 on OpenAlexaffabout

Bibliographic record

VenueGlobal Biodiversity Information Facility · 2022
Typedataset
Languagefr
Field
Topic
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsEstuaryBenthic zoneArcticHabitatBiodiversityAbundance (ecology)The arctic

Abstract

fetched live from OpenAlex

A research survey on the Arctic surfclam (Mactromeris polynyma) was carried out by DFO in 2017 in the Estuary of the St. Lawrence River on the clam bed named Forestville using a "New England" type hydraulic dredge. The main objective of this survey was to study the spatial distribution of pre-commercial (anteroposterior length of less than 80 mm) and commercial (anteroposterior length equal or greater than 80 mm) sizes of Arctic surfclams as well as to assess the abundance and diversity of benthic species associated with the sandy habitat of the Arctic surfclams. Only benthic species data associated with Arctic surfclams habitat are presented in this dataset. Un relevé de recherche sur le stock de la mactre de Stimpson (Mactromeris polynyma) a été réalisé par le MPO en 2017 dans l'estuaire du Saint-Laurent sur le gisement nommé Forestville à l’aide d’une drague hydraulique de type « Nouvelle-Angleterre ». L’objectif principal de ce relevé était d’étudier la répartition spatiale des tailles pré-commerciale (longueur antéropostérieure de moins de 80 mm) et commerciale (longueur antéropostérieure égale ou plus de 80 mm) de la mactre de Stimpson ainsi que d’évaluer l’abondance et la diversité des espèces benthiques associées à l’habitat sableux de la mactre de Stimpson. Seules les données des espèces benthiques associées à l’habitat de la mactre de Stimpson sont présentées dans ce jeu de données.

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)0.001
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 score0.016
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.037
GPT teacher head0.226
Teacher spread0.189 · 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
Published2022
Admission routes2
Has abstractyes

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