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Record W2547021310 · doi:10.5376/ijms.2016.06.0041

Record of Litter Ingestion by Cod (<i>Gadus morhua</i>) Collected from Masfjorden, Western Norway

2016· article· en· W2547021310 on OpenAlexvenueno aff
Laith A. Jawad, Odd-B. Humborstad, Per Gunnar Fjelldal

Bibliographic record

VenueInternational Journal of Marine Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsGadusMarine debrisFisheryIngestionDebrisFish <Actinopterygii>LitterGadidaeMarine Strategy Framework DirectivePollutionEnvironmental scienceBiologyAtlantic codEcologyOceanographyGeologyEcosystem

Abstract

fetched live from OpenAlex

We present the finding of a wild caught Atlantic cod ( Gadus morhua ) that had ingested a metal beverage can, common marine debris. The can was detected when the fish was radiographed alive as part of a scientific experiment. A possible cause for the death of the fish was the blockage of the digestive tract by the can. Due to paucity in marine debris monitoring programs and lack of impact studies of diverse marine debris in Norwegian waters it is not possible to assess the scale and extent of the effects of this type of pollution on cod and other species.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

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

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 head0.011
GPT teacher head0.254
Teacher spread0.243 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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