Weight loss and net abnormalities of<i>Hydropsyche betteni</i>(caddisfly) larvae exposed to aqueous zinc
Bibliographic record
Abstract
Abstract Caddisfly larvae (Hydropsyche betteni) were collected near a zinc mining operation and exposed to elevated concentrations of zinc in an attempt to determine the efficacy of using weight change and capture net architecture for assessing the toxicological impact of metal exposure. One group of larvae was collected near the mine site (Adjacent) with another collected upstream and away from the mine (Remote). Weight change and capture net architecture was monitored on 400 individually identifiable larvae. The threshold-observed-effect concentration after 13 d was 7.6 mg/L for the Remote group and 30.2 mg/L for the Adjacent group. After 48 d, the highest test concentration of 42 mg/L resulted in a 23 and 19% loss in live-body weight in the Remote and Adjacent groups, respectively, while control larvae from both groups gained 6% in comparison to initial pre-exposure weights. Five weeks of exposure at 22 mg Zn/L or greater was required by both larval groups to statistically reduce the frequency of normal nets, indicating that the sensitivity of the net response was less sensitive than weight loss. Relative differences in weight changes and net architecture strongly suggest that the Adjacent larval group was slightly more tolerant than the Remote and that this increased tolerance may be related to chronic pre-exposure to zinc prior to collection of larvae. This study demonstrates the utility of using weight loss, net architecture, and tissue burdens for assessing the impact of elevated zinc.
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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".