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Record W1987254635 · doi:10.1080/02652030400004259

Methylmercury levels in predatory fish species marketed in Canada

2004· article· en· W1987254635 on OpenAlexaffabout
Don Forsyth, Valerie Casey, Robert Dabeka, Arthur D Mckenzie

Bibliographic record

VenueFood Additives & Contaminants · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsHealth Canada
Fundersnot available
KeywordsSwordfishMethylmercuryTunaFisheryMercury (programming language)ChemistryFish <Actinopterygii>Environmental chemistryBiologyBioaccumulation

Abstract

fetched live from OpenAlex

Mercury was detected in all analysed samples of swordfish, marlin, shark and tuna purchased from major supermarket outlets and fish retailers in three cities across Canada. Total mercury and methylmercury levels ranged up to 3845 and 2346 ng g(-1), respectively. Swordfish contained the highest levels, followed by shark, fresh/frozen tuna and marlin. Levels in canned tuna were considerably less than the other examined samples. Methylmercury was extracted with toluene from enzymatically hydrolysed samples after the addition of sulphuric acid and potassium bromide. An L-cysteine back-extraction was used to separate the methylmercury from most organic co-extractives. Analysis of methylmercury (as methylmercury bromide) was by gas chromatography with pulsed discharge detection.

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)0.001
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 score0.081
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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

Citations67
Published2004
Admission routes2
Has abstractyes

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