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Record W3002453511 · doi:10.1139/cjfas-2019-0328

Age validation of yellowfin (<i>Thunnus albacares</i>) and bigeye (<i>Thunnus obesus</i>) tuna of the northwestern Atlantic Ocean

2020· article· en· W3002453511 on OpenAlexvenueno aff
Allen H. Andrews, Ashley Pacicco, Robert J. Allman, Brett J. Falterman, Erik T. Lang, Walter J. Golet

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsYellowfin tunaThunnusScombridaeFisheryOtolithOceanographyTunaBiologyGeologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Estimates of age and growth of yellowfin (Thunnus albacares) and bigeye (Thunnus obesus) tuna remain problematic because validation of growth zone deposition (opaque and translucent) has not been properly evaluated. Otolith growth structure (zone clarity) can be poorly defined for tropical tunas, but the use of bomb radiocarbon dating has validated age estimates to 16–18 years for yellowfin and bigeye tuna. Use of the radiocarbon decline period — defined by regional coral and otoliths — provided valid ages through ontogeny. Yellowfin tuna aged 2–18 years (n = 34, 1029–1810 mm FL) and bigeye tuna aged 3–17 years (n = 12, 1280–1750 mm FL) led to birth years that were coincident with the bomb radiocarbon decline. The results indicate there was no age reading bias for yellowfin tuna and that age estimates of previous studies were likely underestimated for both species.

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)0.003
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 score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.212
Teacher spread0.192 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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