MétaCan
Menu
Back to cohort
Record W2914580059 · doi:10.1021/acs.est.9b00259

Insights into Long-Term Toxicity of Triclosan to Freshwater Green Algae in Lake Erie

2019· article· en· W2914580059 on OpenAlexafffund
Xiaying Xin, Chunjiang An, Renata Raina‐Fulton, Harold G. Weger

Bibliographic record

VenueEnvironmental Science & Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsConcordia UniversityUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsTriclosanAlgaeGreen algaeBiologyToxicityEnvironmental chemistryBotanyChlamydomonas reinhardtiiChemistryBiochemistry

Abstract

fetched live from OpenAlex

This study explored the long-term impacts of a pulse disturbance of triclosan on five nontarget green algae in Lake Erie. Comprehensive analyses were performed using multiple physiological end points at community and subcellular scales. The toxic mechanism of triclosan in a wide range of concentrations was analyzed. The diverse sensitivity of algae species and complex interrelationships among multiple end points were revealed. The results showed the taxonomic groups of algae were the key issue for sensitivity difference. High doses of triclosan caused irreversible damage on algae, and environmentally relevant doses initiated either inhibition or stimulation. Smaller cells had higher sensitivity to triclosan, while larger cells had a wider size variation after exposure. Colonial cells were less sensitive than unicells. For chlorophyll, there were better dose–response relationships in Chlorococcum sp., Chlamydomonas reinhardtii CPCC 12 and 243 than Asterococcus superbus and Eremosphaera viridis . For chlorophyll fluorescence, F v / F m was the most sensitive parameter, and q N was more sensitive than q P . Triclosan showed long-term effects on biochemical components, such as lipids, proteins, and nucleic acids. The findings will be helpful for a systematic and complete assessment of triclosan toxicity in natural waters and the development of appropriate strategies for its risk management.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

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

Citations82
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental Science & TechnologySame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207