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Record W7130693616 · doi:10.5061/dryad.p5hqbzm1h

Migration timing metrics of 11 Atlantic salmon populations in Eastern Canada

2025· dataset· en· W7130693616 on OpenAlexaffabout
Samantha V. Beck, Tony Kess, Cameron M. Nugent, Brian J. Dempson, Gérald Chaput, Hallie E. Arno, Steve J. Duffy, Nicole C. Smith, Paul Bentzen, Matthew Kent, Victoria L. Pritchard, Ian R. Bradbury

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsFisheries and Oceans CanadaDalhousie University
Fundersnot available
KeywordsBaseline (sea)MetadataPopulationSpatial ecologyClimate changeDiel vertical migration

Abstract

fetched live from OpenAlex

This dataset contains migration timing metadata for Atlantic salmon (Salmo salar) populations across 11 rivers in eastern Canada, spanning the regions of Labrador, Newfoundland, and the Maritimes. For each site, the dataset includes geographic coordinates, the Julian day at which 5 % and 95 % of the cumulative annual run was reached, and the run-timing modality (unimodal or bimodal). Populations vary widely in migration timing, with early runs beginning as early as day 145 and late runs extending beyond day 288. Bimodal populations, found primarily in the Maritimes, display two distinct peaks in migration timing, whereas unimodal populations in Labrador and Newfoundland have a single, more continuous run. These data provide baseline information on spatial variation in run timing and migration modality in North American Atlantic salmon, enabling integration with genetic, environmental, and climate projections to investigate the ecological and evolutionary drivers of migration phenology.

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 score0.057
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.005

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 head0.095
GPT teacher head0.351
Teacher spread0.256 · 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
Published2025
Admission routes2
Has abstractyes

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