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Record W3129787858 · doi:10.1002/9780470027318.a9265

Mercury Speciation in Foods

2018· other· en· W3129787858 on OpenAlexaff
Zhongwen Wang

Bibliographic record

VenueEncyclopedia of Analytical Chemistry · 2018
Typeother
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMercury (programming language)MethylmercuryContaminated foodEnvironmental chemistryMercury contaminationContaminationEnvironmental scienceChemistryEcologyBiologyBioaccumulationComputer science

Abstract

fetched live from OpenAlex

Abstract Mercury (Hg) is an extremely rare element in earth's crust and also the only metallic element that is liquid at room temperature and pressure. Mercury in the environment originates from both natural and anthropogenic sources. A number of exposure cases around the world, which have led to adverse health effects in humans, have been reported as a result of incidents related to mercury. Mercury and its species, especially methylmercury (CH3Hg+/MeHg), are a concern for certain foods. Contamination of fish, seafood products, and other food sources, such as rice, by MeHg/Hg continues to be a challenging issue. Although numerous articles regarding mercury in the environment have been published, there are limited articles regarding mercury speciation in food. This article discusses the topics of mercury speciation in foods, such as fish and rice, with the focus on advances in the analytical methods for mercury speciation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.004

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 head0.010
GPT teacher head0.259
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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