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Record W1979431894 · doi:10.1039/b800784p

10th Anniversary Review: when healthy food becomes polluted—implications for public health and dietary advice

2008· review· en· W1979431894 on OpenAlexaff
Magritt Brustad, Torkjel M. Sandanger, Evert Nieboer, Eiliv Lund

Bibliographic record

VenueJournal of Environmental Monitoring · 2008
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)Environmental healthAgency (philosophy)Fish <Actinopterygii>Public healthConsumption (sociology)Food chainUncertaintyRisk assessmentScientific evidenceFish consumptionBusinessMedicineBiologyFisheryEcologySociologyEconomics

Abstract

fetched live from OpenAlex

Divergent scientific and regulatory agency perspectives about contaminants in fish have lead to contradictory advice and confusing public messages about its consumption. The evidence for the protective effect of eating fish on cardiovascular outcomes is considered to be convincing. It has long been attributed to n-3 unsaturated long-chain fatty acids. Persistent organic pollutants (POPs) are compounds that are lipid soluble and accumulate in the aquatic food chain. Despite a considerable decrease in their levels in fish during the last two decades, there is still significant concern about potential negative health effects and an ongoing debate exists about what type of fish consumption advisories are most suitable. In this review our aim is twofold, namely to explore: (1) the underlying causes for the conflicting recommendations by discussing the strengths and limitations of risk assessment and epidemiological evidence; and (2), the role of risk management in formulating public dietary advisories. It is our view that the latter advice is most appropriately formulated in the context of risk management, of which both epidemiologic evidence and risk assessment are essential components.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.389
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2008
Admission routes1
Has abstractyes

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