Bibliographic record
Abstract
Bioassays are among the ecotoxicologist's most effective weapons in the evaluation of water quality and the assessment of ecological impacts of effluents, chemicals, discharges, and emissions on the aquatic environment. Information on these assessment aids is needed throughout the international scientific and environmental management community. This comprehensive reference provides an excellent overview of the small-scale aquatic bioassay techniques and applications currently in use around the world. This special volume is the result of several years of collaboration between Environment Canada and Fisheries and Oceans Canada. Internationally recognized research scientists at many institutions have contributed to this state-of-the-art examination of the exciting, environmentally important field of microscale testing in aquatic toxicology. Microscale Testing in Aquatic Toxicology contains over forty chapters covering relevant principles, new techniques and recent advancements, and applications in scientific research, environmental management, academia, and the private sector.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.000 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.963 | 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 teacher head, 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".