Characterization of anionic surfactant-induced toxicity in a primary effluent
Bibliographic record
Abstract
A simple and rapid analytical approach was developed that can be used to investigate the anionic surfactant-induced toxicity associated with the primary effluent from the Lions Gate wastewater treatment plant (North Vancouver, BC). Using this approach, the effluent was characterized on two occasions in terms of anionic surfactant concentration and anionic surfactant-induced toxicity. The results suggest that the concentration of anionic surfactants, measured as methylene blue active substances (MBAS), in the primary effluent increased throughout each day and was highest at night (11:30 p.m.). The toxicity, measured using Vibrio fischeri bioassays (i.e., MicroTox™), also increased throughout each day and was the highest at night. The high molecular weight fraction of anionic surfactants was identified as the most toxic fraction although it was present at the lowest concentration. The results of the present study suggest that the concentration of the high molecular weight fraction of anionic surfactants could be used as a good surrogate to easily and rapidly quanitfy the anionic surfactant-induced toxicity of the primary effluent.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".