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Record W6908378330 · doi:10.26071/ogsl-3e9c3887-d969

Coastal zooplankton of the north of St-Lawrence estuary.

2019· dataset· en· W6908378330 on OpenAlexaffabout

Bibliographic record

VenueOGSL repository · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsZooplanktonEstuaryBaseline (sea)Abundance (ecology)TaxonEnvironmental monitoringPlan (archaeology)

Abstract

fetched live from OpenAlex

These files contain abundance data for zooplankton species collected on the north coast of the St. Lawrence Maritime Estuary between Longue-Rive and Godbout (summer and fall 2019 to be completed with 2020 and 2021 data). They were collected using 63 µm (vertical line) and 200 µm (vertical-oblique line) nets to identify the diversity of mesozooplankton species and their different stages of development. The main taxon are: Copepods, Acartia, Calanus, Appendicularia, Fritillaria, Cladocera, Evadne. This research project is part of DFO's Oceans and Freshwater Scientific Research Contribution Program (CSOED) on the Characterization of Coastal Zones of the St. Lawrence Estuary. Environmental data, such as temperature, salinity, fluorescence and dissolved oxygen, are available by following the link provided to a dedicated archiving platform. This project is part of the Coastal Environmental Baseline Program Initiative under the Oceans Protection Plan of Fisheries and Oceans 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)0.000
metaresearch head score (Gemma)0.002
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 score0.678
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.010
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.034

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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
Published2019
Admission routes2
Has abstractyes

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