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Record W7111039303 · doi:10.1021/acs.est.5c07859.s001

Spatial Distribution,Seasonal Variation, and EcologicalRisk Assessment of Benzotriazole UV Stabilizers in Waters from CanadianTributaries and Coastal Systems

2025· article· W7111039303 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Language
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsEstuaryTributaryBenzotriazolePollutantParticulatesContaminationSeasonalityRisk assessmentEcological assessment

Abstract

fetched live from OpenAlex

Benzotriazole UV stabilizers (BZT-UVs) are industrial additives of emerging environmental concern, with UV-328 recently listed under the Stockholm Convention on Persistent Organic Pollutants and several congeners listed as Substances of Very High Concern in Europe. However, their distribution and fate in coastal environments remain poorly understood. This study investigated the spatial and seasonal variations of dissolved and suspended particulate matter (SPM)-bound BZT-UVs in surface water from the St. Lawrence River, Estuary and Gulf (SLREG) and the coast of Vancouver and Victoria, spanning Canada’s east and west coasts. BZT-UV contamination was higher in the SLREG, with peak UV-328 levels in July, likely due to increased summer use. Most congeners were more abundant in the SPM from July to October in the St. Lawrence Estuary, while elevated UV-329 levels in April suggest a distinct source, possibly related to snowmelt. These seasonal variations may influence the exposure of local species to BZT-UVs. While the concentrations of the dissolved BZT-UVs in most samples are expected to pose minimal ecological risks, the concentrations of some BZT-UVs in a few samples from the upper estuary of the SLREG may pose moderate to high risk in summer, highlighting the need for further assessment.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0170.000

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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