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Record W2143647052 · doi:10.1300/j030v13n04_04

Mercury Content in Pacific Troll-Caught Albacore Tuna (<i>Thunnus alalunga</i>)

2005· article· en· W2143647052 on OpenAlexaboutno aff
Michael T. Morrissey, Rosalee S. Rasmussen, Tomoko Okada

Bibliographic record

VenueJournal of Aquatic Food Product Technology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlbacoreTunaMercury (programming language)FisheryThunnusChemistryFleshAnimal scienceMethylmercuryEnvironmental chemistryFood scienceBiologyFish <Actinopterygii>Bioaccumulation

Abstract

fetched live from OpenAlex

Ninety-one albacore tuna (Thunnus alalunga) captured during the 2003 commercial fishing season were tested for total mercury content in muscle tissue. The fish were harvested between 32.72°N (off Southern California) and 48.30°N (off the northern tip of Washington) between July and November. Fish weighed from 3.14 to 11.62 kg and were 50.8-86.4 cm long. Total mercury content in the albacore muscle tissue ranged from 0.027 ppm (μg/g) to 0.26 ppm. The average total mercury content was 0.14 ± 0.05 ppm, which is below the U.S. Food and Drug Administration action level and Canadian standards (1.0 ppm methylmercury and 0.50 ppm total mercury, respectively). Total mercury concentrations showed positive correlations with length and weight of albacore (R2= 0.40 and 0.38, respectively), but there was no correlation with date of capture or lipid content. Results indicate that Pacific troll-caught albacore have low levels of total mercury in the edible flesh and are well within international safety standards for mercury levels in fish.

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)0.000
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.246
Teacher spread0.221 · 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

Citations28
Published2005
Admission routes1
Has abstractyes

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