Effects of copper, cadmium, lead, and arsenic in a live diet on juvenile fish growth
Bibliographic record
Abstract
The effects of diet-borne copper, cadmium, lead, and arsenic on juvenile fish were evaluated using a live diet consisting of the oligochaete Lumbriculus variegatus . In 30 d exposures, no effects were observed on the growth and survival of rainbow trout ( Oncorhynchus mykiss ), fathead minnow ( Pimephales promelas ), and channel catfish ( Ictalurus punctatus ) fed diets contaminated with copper [130–310 µg Cu·(g dm)−1], cadmium [90–540 µg Cd·(g dm)−1], and lead [850–1000 µg Pb·(g dm)−1]. However, rainbow trout growth was reduced in a dose-dependent manner for diets contaminated with arsenic [26–77 µg As·(g dm)−1]. These effects of arsenic on fish growth were accompanied by slower feeding rate, reduced food conversion efficiency, liver cell abnormalities, and fecal matter changes suggestive of digestive effects, and occurred to a similar extent whether the diet was exposed to arsenate or arsenite. Effects from these dietary levels of arsenic, and the absence of effects from these dietary levels of metals, were generally consistent with literature reports using laboratory diets amended with toxicant salts. These results also indicated that reported growth effects on rainbow trout fed diets of invertebrates collected from mining-contaminated areas of the Clark Fork River (Montana, USA) or exposed in the laboratory to Clark Fork River sediments are likely more attributable to the arsenic than the metals in those diets.
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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 | 0.000 |
| 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".