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Record W4380300721 · doi:10.1039/d3em00083d

Monitoring microplastic–contaminant sorption processes in real-time using membrane introduction mass spectrometry

2023· article· en· W4380300721 on OpenAlexafffund
Misha Zvekic, Gregory W. Vandergrift, Christine C. Tong, Chris G. Gill, Erik T. Krogh

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsVancouver Island UniversitySimon Fraser UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaVancouver Island UniversityUniversity of VictoriaAgilent Technologies
KeywordsSorptionEnvironmental chemistryMicroplasticsChemistryLow-density polyethyleneAnthracenePyreneNaphthaleneNonylphenolDesorptionPolyethyleneAdsorptionChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

, respectively, while nonylphenol did not sorb to pristine plastics over this time period. Similar trends among contaminants were observed for other pristine plastics with 4- to 10-fold faster sorption rates associated with LDPE when compared to PS and PP. Sorption was largely complete after three weeks, with the percent analyte sorbed ranging from 40-100% across various microplastic-contaminant combinations. Photo-oxidative ageing of LDPE had little effect on PAH sorption. However, a marked increase in nonylphenol sorption was consistent with increased hydrogen-bonding interactions. This work provides kinetic insights into surface interactions and describes a powerful experimental platform to directly observe contaminant sorption behaviours in complex samples under a variety of environmentally relevant conditions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2023
Admission routes2
Has abstractyes

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