Behavioral and sex ratio modification of Japanese medaka (Oryzias latipes) in response to environmentally relevant mixtures of three pesticides
Bibliographic record
Abstract
We exposed Japanese medaka (Oryzias latipes) to environmentally relevant concentrations of azinphos-methyl, chlorothalonil, endosulfan, and mixtures of all three to determine if combinations of these pesticides result in additive, less-than-additive, or more-than-additive effects. Medaka were exposed from fertilization until 7 days posthatching, and end points included survival, time to hatch, size at 7 days posthatching, activity level (as measured by distance swam) and foraging ability at 3 weeks posthatching, and adult size, liver size, and sex ratio at 5 months posthatching. Although exposure to individual pesticides or pesticide mixtures did not affect survival, hatching time, or foraging ability, fry exposed to azinphos-methyl were significantly smaller at 1 week of age, and those exposed to chlorothalonil and a combination of the chemicals showed reduced activity. Adult sex ratios were biased toward females in all groups exposed to pesticides, with those exposed to azinphos-methyl, chlorothalonil, and the pesticide mixture departing significantly from an even sex ratio. There was no evidence of additive or synergistic effects of pesticide mixtures.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".