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Record W4417009638 · doi:10.1139/cjfas-2025-0166

Comparing capelin abundance estimates from predator diet data and an acoustic survey

2025· article· en· W4417009638 on OpenAlexafffundvenueabout
Mariano Koen‐Alonso, Hannah J. Munro, Matthew Robertson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsCapelinPredationPopulationAbundance (ecology)ZooplanktonPredatorMallotusApex predator

Abstract

fetched live from OpenAlex

In Newfoundland and Labrador marine food webs, capelin ( Mallotus villosus) is a critical energetic link between zooplankton and larger vertebrates, making an accurate assessment of capelin population dynamics integral to effective regional fisheries management. In 1990–1991, the capelin population off the east coast of Newfoundland collapsed, with limited recovery since. Shifts in capelin biology and uncertainties associated with capelin survey data since their collapse have limited understanding of the causes of the capelin collapse and subsequent lack of recovery. We sought to gain a better understanding of capelin population dynamics by modifying a recently developed integrated prey dynamics model to account for temperature- and ontogenetic-induced diet shifts. The best-performing model included an ontogenetic, but not temperature-induced, diet shift to account for changes in predator selectivity. Abundance estimates from our model were not correlated with current assessment estimates. Different estimated trends between predators indicated potential spatial and temporal shifts in predator-prey dynamics. This model helps improve understanding of capelin population dynamics by compensating for limitations associated with individual data sources.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.880

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.293
Teacher spread0.232 · 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 designObservational
Domainnot available
GenreEmpirical

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 routes4
Has abstractyes

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