Evaluation of Single-Pass Electrofishing and Rapid Habitat Assessment for Monitoring Redside Dace
Bibliographic record
Abstract
Abstract To date, monitoring of the status of the provincially threatened redside dace Clinostomus elongatus in Ontario has been ad hoc or incidental to other sampling programs. We evaluated the efficacy of single-pass backpack electrofishing without block nets to detect redside dace, provide an index of abundance, and characterize size-class distributions. We also examined whether a rapid stream habitat assessment method was suitable for monitoring habitat condition at redside dace sites. Based on 40 sites across 7 Lake Ontario tributaries, catch data and length frequency distributions from single-pass sampling were compared with those from multiple-pass depletion sampling. Single-pass electrofishing captured 47% of estimated redside dace abundance and 34% of biomass. Abundance and biomass data from the single-pass method were positively correlated (abundance r2 = 0.83; biomass r2 = 0.52) with estimates from the multiple-pass depletion method. Probability of detection and precision of single-pass estimates of abundance were similar to those reported in previous studies on stream salmonids. Single-pass and multiple-pass length frequency distributions were not significantly different. The habitat assessment method failed to detect expected habitat differences between sites that contained redside dace and those that did not. Habitat monitoring could be improved by including more detailed measurements of fine sediment, pool depth, and riparian vegetation.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".