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Record W2792993916 · doi:10.1002/ieam.4042

Deriving a water quality guideline for protection of aquatic communities exposed to triclosan in the Canadian environment

2018· article· en· W2792993916 on OpenAlexaffabout
Katie Hill, Roger L. Breton, Gillian E Manning, R. Scott Teed, Marie Capdevielle, Brian Slezak

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsIntrinsik (Canada)
FundersColgate-Palmolive Company
KeywordsTriclosanWater qualityEnvironmental scienceGuidelineEnvironmental healthAquatic environmentEnvironmental protectionEnvironmental planningEcologyBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract Triclosan is an antibacterial and antifungal chemical used in a variety of consumer products, including soaps, detergents, moisturizers, and cosmetics. Aquatic ecosystems may be exposed to triclosan following the release of remaining residues in wastewater effluents and biosolids. In December 2017, Environment and Climate Change Canada (ECCC) released a federal environmental quality guideline (FEQG) report that contained a federal water quality guideline (FWQG) for triclosan. This guideline will be used as an adjunct to the risk assessment and risk management of priority chemicals identified under the Government of Canada's Chemicals Management Plan (CMP). The FWQG value for triclosan (0.47 μg/L) was derived by ECCC using a hazardous concentration for 5% of species (HC5) from a species sensitivity distribution (SSD). We recalculated the FWQG after performing an independent analysis and evaluation of the available aquatic toxicity data for triclosan and compared our results with the ECCC FWQG value. Our independent analysis of the available aquatic toxicity data entailed conducting a literature search of all available and relevant studies, evaluating the quality and reliability of all studies considered using thorough and consistent study evaluation criteria, and thereby generating a data set of high-quality toxicity values. The selected data set includes 22 species spanning 5 taxonomic groups. An SSD was developed using this data set following the ECCC approaches. The HC5 from the SSD derived based on our validated data set is 0.76 μg/L. This HC5 value is slightly greater (i.e., less sensitive) than the value presented in ECCC's final FWQG. Integr Environ Assess Manag 2018;14:437–441. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC) Key Points Using a similar approach to Environment and Climate Change Canada's (ECCC's) Federal Environmental Quality Guideline (FEQG) to derive a chronic HC5 for Canadian freshwater communities, several differences from the FEQG dataset were identified in both species and endpoints selected. An HC5 of 0.76 µg/L for chronic exposure of triclosan to freshwater aquatic life was generated in the present study, which is slightly greater (i.e., less sensitive) than the HC5 calculated by ECCC in their FEQG.

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)0.010
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.010
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.333
Teacher spread0.270 · 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

Citations13
Published2018
Admission routes2
Has abstractyes

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