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Record W4291002900 · doi:10.3389/frwa.2022.958130

Change in microplastic concentration during various temporal events downstream of a combined sewage overflow and in an urban stormwater creek

2022· article· en· W4291002900 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

VenueFrontiers in Water · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsCarleton University
FundersMitacsNational Geographic Society
KeywordsSnowmeltStormwaterCombined sewerEnvironmental scienceOutfallMicroplasticsSewageHydrology (agriculture)Surface runoffEnvironmental chemistryEnvironmental engineeringEcologyGeology

Abstract

fetched live from OpenAlex

Changes in microplastic concentrations were examined during various temporal events including heavy rain and snowmelt in a river and an urban stream receiving stormwater. Additionally, microplastic concentrations were measured in an urban river during an active combined sewage overflow event. Microplastic concentrations downstream of a combined sewage outfall were observed to increase seven times compared to ambient conditions. During heavy rainfall an increase of 50 times the microplastic concentration was observed in the urban creek with microplastic concentrations doubling in the urban river. However, the largest increase in microplastic concentration at both locations was observed during the primary snowmelt of spring, with microplastic concentrations increasing 114 times in the urban creek and 11 times in the urban river. These results suggest that more research is required to further establish the influence of both combined sewage overflows and snowmelt as a major temporal conduit of microplastics to freshwater 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.420

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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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