Comparison of a partial life-cycle bioassay in artificial streams to a standard beaker bioassay to assess effects of metal mine effluent on <i>Chironomus tentans</i>
Bibliographic record
Abstract
A novel, partial life-cycle bioassay using Chironomus tentans in artificial streams was developed for evaluating the effects of metal mine effluent. The utility of this bioassay was compared to an existing beaker life-cycle bioassay under laboratory conditions. Chironomus tentans larvae were exposed to 45% (v/v) treated metal mine effluent from day 11 through hatching of the second generation. Response patterns were consistent between the two bioassays for hatching success and time to emergence but inconsistent for other endpoints. Significant effects of effluent were obtained for growth, survival, number of adults emerged, and number of eggs per egg case in the artificial stream bioassay but not in the beaker bioassay. Conversely, significant effects on sex ratio and number of egg cases per female were observed in the beaker bioassay but not in the artificial stream bioassay. These differences are believed to be a consequence of the number of organisms per replicate used in each bioassay, which results in a difference in statistical power. As a result, higher coefficients of variation and effects sizes were observed in the beaker bioassay relative to the artificial stream bioassay for almost all endpoints. These results provide evidence that the bioassay in artificial streams can be an effective tool for evaluating the effects of metal mine effluent on life-cycle endpoints in C. tentans.
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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) | 0.000 | 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) | 0.000 | 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".