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Record W3185683441 · doi:10.1002/etc.5173

Are We Underestimating Anthropogenic Microfiber Pollution? A Critical Review of Occurrence, Methods, and Reporting

2021· review· en· W3185683441 on OpenAlex

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

VenueEnvironmental Toxicology and Chemistry · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsMicrofiberSynthetic fiberEnvironmental scienceBiotaPollutionEnvironmental chemistryNatural (archaeology)Environmental pollutionBiochemical engineeringFiberEcologyChemistryEnvironmental protectionBiologyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Anthropogenic microfibers, a ubiquitous environmental contaminant, can be categorized as synthetic, semisynthetic, or natural according to material of origin and production process. Although natural fibers, such as cotton and wool, originated from natural sources, they often contain chemical additives, including colorants (e.g., dyes, pigments) and finishes (e.g., flame retardants, antimicrobial agents, ultraviolet light stabilizers). These additives are applied to textiles during production to give textiles desired properties like enhanced durability. Anthropogenically modified "natural" and semisynthetic fibers are sufficiently persistent to undergo long-range transport and accumulate in the environment, where they are ingested by biota. Although most research and communication on microfibers have focused on the sources, pathways, and effects of synthetic fibers in the environment, natural and semisynthetic fibers warrant further investigation because of their abundance. Because of the challenges in enumerating and identifying natural and semisynthetic fibers in environmental samples and the focus on microplastic or synthetic fibers, reports of anthropogenic microfibers in the environment may be underestimated. In this critical review, we 1) report that natural and semisynthetic microfibers are abundant, 2) highlight that some environmental compartments are relatively understudied in the microfiber literature, and 3) report which methods are suitable to enumerate and characterize the full suite of anthropogenic microfibers. We then use these findings to 4) recommend best practices to assess the abundance of anthropogenic microfibers in the environment, including natural and semisynthetic fibers. By focusing exclusively on synthetic fibers in the environment, we are neglecting a major component of anthropogenic microfiber pollution. Environ Toxicol Chem 2022;41:822-837. © 2021 SETAC.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.068
GPT teacher head0.384
Teacher spread0.317 · 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