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Record W2131819690 · doi:10.1080/02652030701305470

Total and organic mercury concentrations in the white muscles of swordfish (<b><i>Xiphias gladius</i></b>) from the Indian and Atlantic oceans

2007· article· en· W2131819690 on OpenAlexfundno aff
M.-H. Chen, C.-Y. Chen, Shui‐Kai Chang, S.-W. Huang

Bibliographic record

VenueFood Additives & Contaminants · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Research Council CanadaNational Science CouncilNational Sun Yat-sen University
KeywordsSwordfishMercury (programming language)FleshFisheryFishingChemistryFish <Actinopterygii>BiologyTuna

Abstract

fetched live from OpenAlex

A total of 226 swordfish samples collected from Taiwanese fishing vessels in the Indian and Atlantic oceans were examined for total mercury (THg) and organic Hg (OHg). Analysis of 56 pooled white muscle samples showed that THg and OHg concentrations ranged from 0.056 to 3.97 (1.3 +/- 0.97) and from 0.043 to 3.92 (1.01 +/- 0.82) microg g(-1) flesh mass, respectively. These values were similar to those from various previous studies during the past three decades. THg and OHg were significantly linearly correlated with fork length (FL, cm) of the fish from Indian and Atlantic oceans; however, there was no significant OHg%-FL relationship. OHg and THg also were significantly correlated. Fishes with FL < or = 140 cm met the methyl Hg (meHg) regulatory standard set by the European Commission Decision (meHg < or = 1.0); and fish with FL < or = 211 cm met the Taiwanese Food and Hygiene Standard (meHg < or = 2.0). Weekly swordfish consumption rates and amounts are recommended accordingly.

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 score0.018
Threshold uncertainty score0.036

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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

Citations18
Published2007
Admission routes1
Has abstractyes

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