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Record W4386430718 · doi:10.1039/d3ay01286g

Microplastic <i>in situ</i> detection based on a portable triboelectric microfluidic sensor

2023· article· en· W4386430718 on OpenAlexafffund
Abbas Motalebizadeh, Somayeh Fardindoost, Julia Jungwirth, Nishat Tasnim, Mina Hoorfar

Bibliographic record

VenueAnalytical Methods · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTriboelectric effectIn situMicrofluidicsMicroplasticsMaterials scienceEnvironmental scienceNanotechnologyEnvironmental chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

measurement of the size and concentration of polystyrene (PS) micro-particles in water. The M-TES sensor relies on inducing and measuring electrical charges generated by microplastic flow within water droplets passing through a microfluidic channel. The experimental samples encompass pure polystyrene (PS) microparticles ranging from 500 nm to 10 μm, as well as actual samples collected from a coffee machine. The results reveal that the sensor's response exhibits a linear correlation with the increase in both microplastic size and concentration. The proposed sensing system could distinguish between microplastics of different sizes and concentrations. The results demonstrate the applicability of the M-TES in the field of sensors for environmental monitoring.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.019
GPT teacher head0.298
Teacher spread0.280 · 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

Citations14
Published2023
Admission routes2
Has abstractyes

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