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Record W2153479003 · doi:10.1016/j.envint.2013.12.009

What level of estrogenic activity determined by in vitro assays in municipal waste waters can be considered as safe?

2014· review· en· W2153479003 on OpenAlexafffund
Barbora Jarošová, Luděk Bláha, John P. Giesy, Klára Hilscherová

Bibliographic record

VenueEnvironment International · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Saskatchewan
FundersNanjing UniversityState Key Laboratory in Marine PollutionState Administration of Foreign Experts AffairsChinese Academy of SciencesGrantová Agentura České RepublikyCanada Research Chairs
KeywordsEffluentBioassayEstroneEnvironmental chemistryWastewaterIn vitro toxicologyEstriolIn vitroChemistryIn vivoEnvironmental scienceEnvironmental engineeringBiologyHormoneBiochemistryBiotechnologyEcology

Abstract

fetched live from OpenAlex

In vitro assays are broadly used tools to evaluate the estrogenic activity in Waste Water Treatment Plant (WWTP) effluents and their receiving rivers. Since potencies of individual estrogens to induce in vitro and in vivo responses can differ it is not possible to directly evaluate risks based on in vitro measures of estrogenic activity. Estrone, 17beta-estradiol, 17alfa-ethinylestradiol and to some extent, estriol have been shown to be responsible for the majority of in vitro estrogenic activity of municipal WWTP effluents. Therefore, in the present study safe concentrations of Estrogenic Equivalents (EEQs-SSE) in municipal WWTP effluents were derived based on simplified assumption that the steroid estrogens are responsible for all estrogenicity determined with particular in vitro assays. EEQs-SSEs were derived using the bioassay and testing protocol-specific in vitro potencies of steroid estrogens, in vivo predicted no effect concentration (PNECs) of these compounds, and their relative contributions to the overall estrogenicity detected in municipal WWTP effluents. EEQs-SSEs for 15 individual bioassays varied from 0.1 to 0.4ng EEQ/L. The EEQs-SSEs are supposed to be increased by use of location-specific dilution factors of WWTP effluents entering receiving rivers. They are applicable to municipal wastewater and rivers close to their discharges, but not to industrial waste waters.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.106
GPT teacher head0.351
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations156
Published2014
Admission routes2
Has abstractyes

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