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Record W2956898134

An analysis of ingested microplastics found in offshore Atlantic cod (Gadus morhua) and inshore capelin (Mallotus villosus) using scientific and citizen science methods

2019· dissertation· en· W2956898134 on OpenAlexfundaboutno aff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
FundersFisheries and Oceans CanadaSocial Sciences and Humanities Research Council of CanadaMarine Environmental Observation Prediction and Response Network
KeywordsCapelinGadusMicroplasticsMallotusFisheryAtlantic codPlastic pollutionGadidaePollockFish <Actinopterygii>Marine pollutionBiologyEnvironmental sciencePollutionEcologyPredation
DOInot available

Abstract

fetched live from OpenAlex

Analyzing plastic ingestion rates in fish and other marine organisms is an effective tool to understand the impacts of marine plastic pollution worldwide. As more and more marine organisms ingest plastic pollution, more attention has focused on the ability of local citizens to locate and identify plastics in their food fish. In this study, I expanded the list of species examined for plastic ingestion by adding inshore capelin (Mallotus villosus) and offshore Atlantic cod (Gadus morhua) from Northwest Atlantic Fisheries Organization Division 3 of Newfoundland, Canada. The frequency of occurrence of plastic ingestion in Atlantic cod and capelin was 1.1%, and 0, respectively. I also examined the success rate of citizens locating and identifying ingested microplastics in fish without the use of scientific tools. I found that citizen scientists can be successfully organised to monitor microplastic in fish.

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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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Same venueMemorial University Research Repository (Memorial University)Same topicMicroplastics and Plastic PollutionFrench-language works237,207