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Identifying opportunities for harmonized microplastics and mesoplastics monitoring for Caribbean Small Island Developing States using a spatiotemporal assessment of beaches in South Eleuthera, The Bahamas

2023· article· en· W4380870944 on OpenAlexaff
Kristal K. Ambrose, Tony R. ‎Walker

Bibliographic record

VenueMarine Pollution Bulletin · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMicroplasticsBaseline (sea)Marine debrisOceanographyCaribbean regionFisheryAbundance (ecology)TreatyPlastic pollutionEnvironmental monitoringSmall Island Developing StatesGeographyEnvironmental scienceDebrisEcologyBiologyClimate change

Abstract

fetched live from OpenAlex

Increasing quantities of microplastics and mesoplastics in the marine environment underscore the need for marine microplastics to be included in the global Plastics Treaty to end plastic pollution. Caribbean Small Island Developing States (SIDS) lack harmonized microplastics monitoring protocols, leaving them data deficient at the science-policy interface required for treaty negotiations. This baseline study assessed spatial and seasonal abundance and distribution of microplastic (1-5 mm) and mesoplastic (5-25 mm) on 16 beaches with three coastal exposures (Atlantic Ocean, Exuma Sound, Bahama Bank) in South Eleuthera, The Bahamas and its implications for Caribbean SIDS. Microplastics were the dominant debris type sampled (74 %) across all beaches, with significant spatial (p = 0.0005) and seasonal (p = 0.0363) differences in abundance and distribution across study sites. This baseline study identifies opportunities required for developing harmonized microplastics and mesoplastics monitoring by Caribbean SIDS to collect data to help support global plastics treaty negotiations.

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 score0.437
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

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

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 head0.100
GPT teacher head0.286
Teacher spread0.186 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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