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Record W3210337099 · doi:10.1139/cjfas-2020-0444

Support for the Slope Sea as a major spawning ground for Atlantic bluefin tuna: evidence from larval abundance, growth rates, and particle-tracking simulations

2021· article· en· W3210337099 on OpenAlexvenueno aff
Christina M. Hernández, David E. Richardson, Irina I. Rypina, Ke Chen, Katrin E. Marancik, Kathryn Shulzitski, Joel K. Llopiz

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsTunaFisheryThunnusLarvaPopulationOceanographyScombridaeAbundance (ecology)BiologyGeographyEcologyGeologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Atlantic bluefin tuna (Thunnus thynnus) are commercially and ecologically valuable, but management is complicated by their highly migratory lifestyle. Recent collections of bluefin tuna larvae in the Slope Sea off northeastern United States have opened questions about how this region contributes to population dynamics. We analyzed larvae collected in the Slope Sea and the Gulf of Mexico in 2016 to estimate larval abundance and growth rates and used a high-resolution regional ocean circulation model to estimate spawning locations and larval transport. We did not detect a regional difference in growth rates, but found that Slope Sea larvae were larger than Gulf of Mexico larvae prior to exogenous feeding. Slope Sea larvae generally backtracked to locations north of Cape Hatteras and would have been retained within the Slope Sea until the early juvenile stage. Overall, our results provide supporting evidence that the Slope Sea is a major spawning ground that is likely to be important for population dynamics. Further study of larvae and spawning adults in the region should be prioritized to support management decisions.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.284
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations26
Published2021
Admission routes1
Has abstractyes

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