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Record W3207449693 · doi:10.1139/er-2021-0048

Microplastics in lakes and rivers: an issue of emerging significance to limnology

2021· article· en· W3207449693 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEnvironmental Reviews · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcGill UniversityBureau de Coopération Interuniversitaire
Fundersnot available
KeywordsMicroplasticsEnvironmental sciencePlanktonZooplanktonBiogeochemical cycleEcologyBenthic zoneFreshwater ecosystemBiodiversityEcosystemInvertebrateAquatic ecosystemBiology

Abstract

fetched live from OpenAlex

Microplastics, i.e., plastic particles in the size range of planktonic organisms, have been found in the water columns and sediments of lakes and rivers globally. The number and mass of plastic particles drifting through a river can exceed those of living organisms such as zooplankton and fish larvae. In freshwater sediments, concentrations of microplastics reach the same magnitude as in the world’s most contaminated marine sediments. Such particles are derived from a unique biogeochemical cycle that ultimately influences productivity, biodiversity, and ecosystem functioning. Furthermore, microplastics act as vectors of toxic substances to invertebrates, fishes, herpetofauna, and waterfowl. We contend that the concentration of this distinct particle component is an ecologically significant parameter of inland waterbodies because of its ubiquity, environmental persistence, and interactions with key ecological processes. No environmental field survey that has searched for microplastics has yet failed to detect their presence. Standardized limnological protocols are needed to compare spatio-temporal variation in the concentration of microplastics within and across watersheds. Data obtained from such protocols would facilitate environmental monitoring and inform policy for managing plastic waste; furthermore, they would enable more accurate modeling of contaminant cycling and the development of a global plastic budget that identifies sources, distribution and circulation pathways, reservoir size, and retention times.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.999

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)0.0010.000

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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