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Record W4389154285 · doi:10.1039/d3em00424d

Understanding the importance of atmospheric transformation in assessing the hazards of liquid crystal monomers

2023· article· en· W4389154285 on OpenAlexfundno aff
Jinlong Wang, Shenghong Wang, Zhizhen Zhang, Xinkai Wang, Kaihui Xia, Li Li, Qifan Liu

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
FundersEnvironment and Climate Change CanadaNational Natural Science Foundation of China
KeywordsBioaccumulationEnvironmental chemistryPersistence (discontinuity)Environmental sciencePollutantHuman healthChemistryTransformation (genetics)ContaminationBiochemical engineeringToxicologyBiologyOrganic chemistryEcologyEngineeringEnvironmental healthBiochemistryMedicine

Abstract

fetched live from OpenAlex

used by the United States Environmental Protection Agency, 44% are classified "mobile" according to the criterion used by the German Environmental Agency, and 58% have the potential to induce unacceptable toxic effects in aquatic organisms. Furthermore, we identified several transformation products with increased persistence, bioaccumulation potential, and mobility compared to their parent compounds. These findings not only offer insights for prioritizing LCM transformation products for future risk assessment, but also underscore the significance of considering atmospheric transformation in the evaluation of environmental risks posed by emerging contaminants, including LCMs.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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