The evaluation of 3 diets for rearing<i>Hyalella azteca</i>and the influence of diet on acute ammonia toxicity
Bibliographic record
Abstract
Three Hyalella azteca cultures were reared on different diets since birth, reflecting the recommended diets of various investigators. The 3 diets consisted of fish flakes (FF), a mixture of fish flakes supplemented with the diatom Thalassiosira weissflogii (FF-D), and a mixture of fish flakes supplemented with yeast, cereal grass media, and trout chow (FF-YCT). The 3 diets were evaluated by comparing 20 wk of culturing data, along with the organism's response to standard 96-h toxicity testing with ammonium chloride over a range of pH and temperature. Hyalella azteca fed the FF-D diet had the highest overall survival rate (96.6%, standard deviation [SD] 4.3%) compared to those fed the FF diet (92.0%, SD 12.7%), or the FF-YCT diet (91.1%, SD 14.8%), although difference in survival was not statistically significant. Organisms fed the FF-D diet produced a higher number of young per week per adult (6.1, SD 2.8) than the FF diet (5.1, SD 2.2), or the FF-YCT diet (4.0, SD 1.2), although differences were not statistically significant. Of the diets evaluated, H. azteca reared on the FF-D diet were often significantly more resistant to total and un-ionized ammonia toxicity in acute 96-h testing than those reared on the other 2 diets across the 2 temperatures and 5 pHs tested, suggesting this may be the most optimal diet for this species. Environ Toxicol Chem 2016;35:2416-2424. © 2016 SETAC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".