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Record W2765345238 · doi:10.1002/etc.4019

Avoidance threshold to oil water-soluble fraction by a juvenile marine teleost fish

2017· article· en· W2765345238 on OpenAlexaff
Guy Claireaux, Pierre Quéau, Stefano Marras, Stéphane Le Floch, Anthony P. Farrell, Annabelle Nicolas-Kopec, Philippe Lemaire, Paolo Domenici

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDicentrarchusPopulationJuvenileContaminationEnvironmental chemistryFish <Actinopterygii>EcotoxicologySea bassFraction (chemistry)Environmental scienceBiologyFisheryToxicologyChemistryEcologyChromatography

Abstract

fetched live from OpenAlex

Abstract When oil spills occur, behavior is the first line of defense for a fish to avoid being contaminated. We determined the avoidance threshold of the European seabass (Dicentrarchus labrax) to the water-soluble fraction (WSF) of oil using a dual-flow choice box. The results showed that a plume of 20%-diluted WSF (total polycyclic aromatic hydrocarbon [PAH] concentration: 8.54 μg L−1) triggered a significant avoidance response that was detected within 7.5 min of introducing WSF-contaminated water into the experimental setup. However, the ecological relevance of seabass capacity to detect and avoid WSF remains to be established. In the short term, such a response is indeed liable to reduce seabass contact time with oil-contaminated water and thus preserve their functional integrity. In the long term, however, avoidance may contribute to the displacement of a population into a possibly less auspicious environment, with consequences very similar to those of contaminant exposure, that is, disturbed population dynamics and demography. Environ Toxicol Chem 2018;37:854–859. © 2017 SETAC

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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 designBench or experimental
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

Citations13
Published2017
Admission routes1
Has abstractyes

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