Estrogen-, androgen- and aryl hydrocarbon receptor mediated activities in passive and composite samples from municipal waste and surface waters
Bibliographic record
Abstract
Passive and composite sampling in combination with in vitro bioassays and identification and quantification of individual chemicals were applied to characterize pollution by compounds with several specific modes of action in urban area in the basin of two rivers, with 400,000 inhabitants and a variety of industrial activities. Two types of passive samplers, semipermeable membrane devices (SPMD) for hydrophobic contaminants and polar organic chemical integrative samplers (POCIS) for polar compounds such as pesticides and pharmaceuticals, were used to sample wastewater treatment plant (WWTP) influent and effluent as well as rivers upstream and downstream of the urban complex and the WWTP. Compounds with endocrine disruptive potency were detected in river water and WWTP influent and effluent. Year-round, monthly assessment of waste waters by bioassays documented estrogenic, androgenic and dioxin-like potency as well as cytotoxicity in influent waters of the WWTP and allowed characterization of seasonal variability of these biological potentials in waste waters. The WWTP effectively removed cytotoxic compounds, xenoestrogens and xenoandrogens. There was significant variability in treatment efficiency of dioxin-like potency. The study indicates that the WWTP, despite its up-to-date technology, can contribute endocrine disrupting compounds to the river. Riverine samples exhibited dioxin-like, antiestrogenic and antiandrogenic potencies. The study design enabled characterization of effects of the urban complex and the WWTP on the river. Concentrations of PAHs and contaminants and specific biological potencies sampled by POCIS decreased as a function of distance from the city.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".