Fish habitat models for a future of novel riverscapes
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
Multiple anthropogenic forces have pushed river ecosystems into undesirable states with no clear understanding of how they should be best managed. The advancement of riverine fish habitat models intended to provide management insights has slowed. Investigations into theoretical and empirical gaps to define habitat more comprehensively across different scales and ecological organizations are crucial in managing the freshwater biodiversity crisis. We introduce the concept of novel riverscapes to reconcile anthropogenic forcing, fish habitat, limitations of current fish habitat models, and opportunities for new models. We outline three priority data-driven opportunities that incorporate the novel riverscape concept: fish movement, river behavior, and drivers of novelty that all are integrated into a scale-based framework to guide the development of new models. Last, we present a case study showing how researchers, model developers, and practitioners can work collaboratively to implement the novel riverscape concept.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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