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Record W3088723966 · doi:10.29169/1927-5129.2020.16.07

Microplastics Occurrence in Waters off the Northwest Coast of Peninsular Malaysia: A Spatial Difference

2020· article· en· W3088723966 on OpenAlexvenueno aff
Mohamad Najihah, Mohamad Saupi Ismail, Chee Kong Yap, Ku Kassim Ku Yaacob

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsMicroplasticsEnvironmental sciencePlastic pollutionPollutionSeawaterSampling (signal processing)OceanographyMarine pollutionFisheryEnvironmental chemistryEcologyGeologyBiologyChemistry

Abstract

fetched live from OpenAlex

Microplastics pollution has been receiving extensive attention globally with its presence felt in both remote and pristine coastal marine environments. Defined as plastics with diameters of 5mm or less and originating from primary and secondary sources, its impact is still not fully understood. Our investigation was conducted along two northern states in Peninsular Malaysia, i.e. Pulau Pinang and Kedah, to quantify microplastics occurrence in the surface waters. Seawater samples were collected from different sampling stations using a 355µm manta net. The plastics was removed from the water samples by density separation, treated with hydrogen peroxide and were identified using a stereo microscope. Microplastics occurred at all sampling stations with numbers varying from 8 to 73 particles/L. Samples were dominated by fragment and filament shapes. Sizes (2 to 3mm) and white colouration were found to be dominant. Future research is suggested to the identification of polymer type and a better understanding of its impact on marine communities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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.

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

Citations11
Published2020
Admission routes1
Has abstractyes

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