Preliminary data of a single-blind, multicountry trial of six bioassays for water toxicity monitoring
Bibliographic record
Abstract
Simple and affordable, yet sensitive and reliable batteries of bioassays for water toxicity testing in developing countries are still not available. The International Development Research Centre (IDRC, Canada) created an international network of laboratories (WaterTox) whose goal is to identify and test a battery of bioassays which could serve that purpose. Eight laboratories from both developing and industrialized countries undertook a standardization and calibration exercise which involved the testing of 24 samples (simple blind design) over the course of a year. The samples were either organic or inorganic toxicants, or mixtures of the two. The bioassays used were the onion root bundle growth assay, the lettuce seed germination assay (root and seedling length), the Daphnia 48 h mortality assay, the Hydra 96 h mortality assay, the Muta-Chromoplate mutagenicity test, and the nematode maturation 96 h assay. Based on test performance, reproducibility, and user-friendliness, inclusion of three of the bioassays in a simplified battery is recommended: lettuce seed germination, Daphnia, and Hydra. A fourth test, the onion bulb bioassay, was also found to be compatible with the criteria used in selecting the battery. The results of two parallel projects were also described: the standardization of an algal micro assay (Selenastrum sp) and the screening of alternative concentration procedures which could increase the ability of the tests to detect low levels of contaminants in environmental water samples. © 2000 John Wiley & Sons, Inc. Environ Toxicol 15: 362–369, 2000
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 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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".