Overview of results from the WaterTox intercalibration and environmental testing phase II program: Part 1, statistical analysis of blind sample testing
Bibliographic record
Abstract
There is an urgent need to evaluate the presence of toxicants in waters used for human consumption and to develop strategies to reduce and prevent their contamination. The International Development Research Centre undertook an intercalibration project to develop and validate a battery of bioassays for toxicity testing of water samples. The project was carried out in two phases by research institutions from eight countries that formed the WaterTox network. Results for the first phase were reported in the special September 2000 issue of Environmental Toxicology. Phase II involved toxicity screening tests of environmental and blind samples (chemical solutions of unknown composition to participating laboratories) using the following battery: Daphnia magna, Hydra attenuata, seed root inhibition with Lactuca sativa, and Selenastrum capricornutum. This battery was also used to assess potential toxicity in concentrated (10x) water samples. Results are presented for a set of six blind samples sent to the participating laboratories over a 1-year period. Analyses were performed for each bioassay to evaluate variations among laboratories of responses to negative controls, violations of test quality control criteria, false positive responses induced by sample concentration, and variability within and between labs of responses to toxic samples. Analyses of the data from all bioassays and labs provided comparisons of false positive rates (based on blind negative samples), test sensitivities to a metal or organic toxicant, and interlaboratory test variability. Results indicate that the battery was reliable in detecting toxicity when present. However, some false positives were identified with a concentrated soft-water sample and with the Lactuca and Hydra (sublethal end-point) tests. Probabilities of detecting false positives for individual and combined toxic responses of the four bioassays are presented. Overall, interlaboratory comparisons indicate a good reliability of the battery.
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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 | 0.118 | 0.088 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".