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Record W2069076161 · doi:10.1021/es200285c

Evaluating Microcystin Exposure Risk through Fish Consumption

2011· article· en· W2069076161 on OpenAlexaff
Amanda Poste, Robert E. Hecky, Stephanie J. Guildford

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Waterloo
FundersNational Institute of Environmental Health SciencesNational Institutes of HealthGreat Lakes Fishery Commission
KeywordsMicrocystinHepatotoxinCyanotoxinBiotaFisherySanitationFish <Actinopterygii>BiologyEcologyEnvironmental scienceEnvironmental healthCyanobacteriaEnvironmental engineeringMedicine

Abstract

fetched live from OpenAlex

Microcystin is a cyanobacterial hepatotoxin that is found worldwide, and poses a serious threat to the ecological communities in which it is found as well as to those who rely on these waters for drinking, sanitation, or as a food source. Microcystin is known to accumulate in fish and other aquatic biota, however the prevalence of microcystin in fish tissue and the human health risks posed by microcystin exposure through fish consumption remain poorly resolved. Here we show that microcystin is pervasive in water and fish from several tropical (Ugandan) and temperate (North American) lakes, including lakes that support some of the largest freshwater fisheries in the world. We establish that fish consumption can be an important and sometimes dominant route of microcystin exposure for humans, and can cause consumers to exceed recommended total daily intake guidelines for microcystin. These results highlight the importance of monitoring microcystin concentrations in fish, and the need to consider potential exposure to microcystin through fish consumption in order to adequately assess human exposure risk.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
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
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.028
GPT teacher head0.260
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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

Citations202
Published2011
Admission routes1
Has abstractyes

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