Single-Stream Recycling Inspires Selective Fish Passage Solutions for the Connectivity Conundrum in Aquatic Ecosystems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Barrier removal is a recognized solution for reversing river fragmentation, but restoring connectivity can have consequences for both desirable and undesirable species, resulting in a connectivity conundrum. Selectively passing desirable taxa while restricting the dispersal of undesirable taxa (selective connectivity) would solve many aspects of the connectivity conundrum. Selective connectivity is a technical challenge of sorting an assortment of things. Multiattribute sorting systems exist in other fields, although none have yet been devised for freely moving organisms within a river. We describe an approach to selective fish passage that integrates ecology and biology with engineering designs modeled after material recycling processes that mirror the stages of fish passage: approach, entry, passage, and fate. A key feature of this concept is the integration of multiple sorting processes each targeting a specific attribute. Leveraging concepts from other sectors to improve river ecosystem function may yield fast, reliable solutions to the connectivity conundrum.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it