Development and Evaluation of a Novel Toxicity Test Method with Hyalella azteca to Optimize Reproduction Endpoints
Bibliographic record
Abstract
Hyalella azteca is a freshwater invertebrate used extensively in ecotoxicology. However, there are challenges associated with using reproduction as an endpoint in current standard methods, including: confounding effects of growth on reproduction, high biological variability associated with reproduction, and difficult recovery of juveniles from sediment. A novel, 28-d toxicity test method was created to optimize the reproduction endpoints by initiating tests with sexually mature amphipods to eliminate the confounding effects of growth, using a sex ratio of 2.3 females per male to reduce reproductive variability, and conducting tests in water-only conditions to improve juvenile recovery. The novel method was evaluated by comparing the sensitivity and reliability of reproduction data to standard methods. Reproduction endpoints produced similar results between methods, but the data were less variable in novel tests. The novel method shows promise to improve the use of reproduction as an endpoint in water-only toxicity tests with H. azteca.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.018 |
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".