Non‐salmonids in a salmonid fishway: what do 50 years of data tell us about past and future fish passage?
Bibliographic record
Abstract
Abstract Salmonid fishways have been used in many countries for non‐salmonid fishes, including Australia, but generally with poor results. Trapping the entrance and exit of a 1:9 gradient salmonid fishway on the Murray River confirmed very poor passage of native fish, with <1% of the most abundant species ascending. Fifty years of fish passage monitoring showed the numbers of three native species declining by 95–100% and non‐native fish becoming dominant. Fishways are now being designed for native fish and being quantitatively assessed, but daily flow management also needs to be addressed. The ecological model for passage of potamodromous fishes has changed from passing adults of a few species to one that incorporates the whole fish community, specifically: immature fish of large‐bodied species that dominate numbers migrating upstream; a diverse range of movement strategies; and small‐bodied species, crustaceans and low numbers of less‐mobile species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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 teacher head, 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".