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Record W2083937969 · doi:10.1080/09603120902749090

Assessment of mercury in muscle of fish from Cartagena Bay, a tropical estuary at the north of Colombia

2009· article· en· W2083937969 on OpenAlexfundno aff
Jesús Olivero‐Verbel, Karina Caballero-Gallardo, Nivis Torres-Fuentes

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Research Council CanadaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsPredatory fishBayOmnivoreTrophic levelMercury (programming language)MugilEstuaryFishingFisheryMulletBiologyEcologyFish <Actinopterygii>GeographyPredation

Abstract

fetched live from OpenAlex

Fish belonging to several trophic levels from Cartagena Bay, a tropical estuary, were collected and analyzed for total mercury (T-Hg) concentrations in muscle. T-Hg concentrations varied from 0.010-0.526 microg/g, and the overall average was 0.051 +/- 0.002 microg/g. Carnivorous species presented the highest T-Hg mean value (0.100 +/- 0.006 microg/g), followed by omnivorous (0.076 +/- 0.014 microg/g) and detritivorous (0.028 +/- 0.001 microg/g). The relationships between weight and T-Hg content were found for the carnivorous species Sciades herzbergi (r = 0.508, p < 0.001) and not for the detritivorous Mugil incilis (r = 0.086, p = 0.207). Although results suggest fish from the bay pose a low health threat for humans in terms of Hg exposure, vulnerable groups such as pregnant women, should avoid eating large size carnivorous species. Knowledge about species with low Hg content should be widespread within fishing communities, guaranteeing adequate nutrition by including fish in the diet and reducing the risk of Hg poisoning.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.066
GPT teacher head0.410
Teacher spread0.344 · 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 teacher head, not a consensus.

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

Citations36
Published2009
Admission routes1
Has abstractyes

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