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Record W4404645061 · doi:10.1021/acsestwater.4c00650

Unlocking Passive Collection of Microplastics in Coral Reefs by Adhesion Measurements

2024· article· en· W4404645061 on OpenAlex
A-Reum Kim, Sushanta K. Mitra, Boxin Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS ES&T Water · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroplasticsCoralCoral reefEnvironmental scienceReefCoral reef organizationsOceanographyFisheryGeologyCoral reef protectionBiology

Abstract

fetched live from OpenAlex

Microplastics (MPs) pollution poses a significant threat to marine ecosystems, with MPs accumulating from various sources and ultimately settling on the seabed. Notably, corals play a crucial role in capturing MPs, primarily through their surface mucus rather than ingestion. This study explores the mechanisms behind MP capture by live elegance corals, examining their interfacial forces in comparison to Scleractinia coral skeletons and model coral skins. Our findings reveal that live elegance corals exhibit strong adhesion forces that effectively trap MPs, a trait absent in other studied surfaces. Moreover, the consistent pull-off force required to remove MPs from live corals, regardless of plastic type (polystyrene or polyethylene), indicates a universal force barrier for scavengers. By leveraging traditional adhesion measurement techniques, our research underscores the essential function of coral mucus in MP capture and offers valuable insights for conservation strategies aimed at mitigating MP pollution in marine environments.

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.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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