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Abundance and characteristics of microplastics in commercial marine fish from Malaysia

2019· article· en· W2965747174 on OpenAlexaff
Samaneh Karbalaei, Abolfazl Golieskardi, Hazilawati Hamzah, Samiaa Jamil Abdulwahid, Parichehr Hanachi, Tony R. ‎Walker, Ali Karami

Bibliographic record

VenueMarine Pollution Bulletin · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsDalhousie University
FundersMinistry of Higher Education, Malaysia
KeywordsMicroplasticsMarine debrisDebrisEnvironmental chemistryLitterFish <Actinopterygii>Environmental scienceFisheryBiologyEcologyChemistryOceanographyGeology

Abstract

fetched live from OpenAlex

Plastic debris is widespread and ubiquitous in the marine environment and ingestion of plastic debris by marine organisms is well-documented. Viscera and gills of 110 individual marine fish from 11 commercial fish species collected from the marine fish market were examined for presence of plastic debris. Isolated particles were characterized by Raman spectroscopy, and elemental analysis was assessed using energy-dispersive X-ray spectroscopy (EDX). Nine (of 11) species contained plastic debris. Out of 56 isolated particles, 76.8% were plastic polymers, 5.4% were pigments, and 17.8% were unidentified. Extracted plastic particle sizes ranged from 200 to 34,900 μm (mean = 2600 μm ±7.0 SD). Hazardous material was undetected using inorganic elemental analysis of extracted plastic debris and pigment particles. The highest number of ingested microplastics was measured in Eleutheronema tridactylum and Clarias gariepinus, suggesting their potential as indicator species to monitor and study trends of ingested marine litter.

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 score0.018
Threshold uncertainty score0.035

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 studies0.0000.000
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 head0.004
GPT teacher head0.171
Teacher spread0.168 · 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

Citations285
Published2019
Admission routes1
Has abstractno

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