Developing a toolkit for fish passage, ecological flow management and fish habitat works
Bibliographic record
Abstract
Fish passage, including fishways and fish screens, ecological flow management for open or ice-covered waters and fish habitat works, such as stream rehabilitation, habitat replacement, erosion and sediment management, are the subject of increased interest worldwide. Research and development in these areas, establishing a foundation of sound science and innovative engineering, has intensified, as a result of widespread recognition of the importance of sustainable and environmentally acceptable use of water resources. Scientific and engineering studies, along with technological advancements have allowed the development of a range of methods and tools for assessing the feasibility of and for providing guidance in seeking effective solutions. Methods and tools range from fairly simple to fairly sophisticated, from long-life rigid structures to adjustable ones, and solutions that are applicable at a variety of projects, scales, site conditions, fish species, aquatic biota, data sources and economic circumstances. A set of tools and methods is presented, which together form a toolkit under development. Each tool is at a different stage of advancement and the process of development is outlined. The toolkit includes analytical methods for relating fish migration timing to hydrographs, ways of attracting and guiding fish to fishways, analysis of fishway hydraulics and fish passage abilities, fish screen hydraulics and fish responses, nature-mimicking fish habitat structures, hydrodynamic and habitat simulation, and the initial stages of considering sediment and ice processes. Suggestions are made for further research and development in these interdisciplinary areas, which challenge interested researchers to focus their individual studies on fish passage, habitat and ecological issues and improve available tools.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.025 |
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".