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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
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

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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