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Record W2990569846 · doi:10.1021/acs.est.9b05327

Experimental Study of OH-Initiated Heterogeneous Oxidation of Organophosphate Flame Retardants: Kinetics, Mechanism, and Toxicity

2019· article· en· W2990569846 on OpenAlexaff
Qifan Liu, John Liggio, Dongmei Wu, Amandeep Saini, Sabina Halappanavar, Jeremy J. B. Wentzell, Tom Harner, Kun Li, Patrick Lee, Shao‐Meng Li

Bibliographic record

VenueEnvironmental Science & Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsHealth CanadaEnvironment and Climate Change Canada
Fundersnot available
KeywordsChemistryEnvironmental chemistryParticulatesOrganophosphateKineticsPhosphateChemical kineticsDegradation (telecommunications)Reaction rate constantPesticideOrganic chemistry

Abstract

fetched live from OpenAlex

, respectively. Using recently developed real-time particle chemical composition measurements, particulate products from heterogeneous photooxidation and the associated degradation mechanisms for particulate OPFRs are reported for the first time. Subsequent cytotoxicity analysis of the unreacted and oxidized OPFR particles indicated that the overall particle cytotoxicity was reduced by up to 94% with heterogeneous photooxidation, likely due to a significantly lower cytotoxicity associated with the oxidized OPFR products relative to the parent OPFRs. The present work not only provides guidance for future field sampling for the detection of transformation products of OPFRs, but also strongly supports the ongoing risk assessment of these emerging chemicals and most critically, their products.

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 score0.003

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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

Citations40
Published2019
Admission routes1
Has abstractyes

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Same venueEnvironmental Science & Technology→Same topicToxic Organic Pollutants Impact→French-language works237,207→