Predicting coastal cutthroat trout molt productive capacity from physiographic variables
Bibliographic record
Abstract
For the management of anadromous coastal cutthroat trout, fisheries managers require an understanding of how physiographic variables, at a watershed scale, influence cutthroat smolt productive capacity. The primary purpose was to produce a practical desktop procedure to reliably predict smolt abundance based upon physiographic variables. A total of 653 annual \nestimates of smolt abundance from 50 watersheds in British Columbia and Washington State were assessed in this study. Cutthroat dominated reaches were identified using hydrology and mapping data, then modelled to predict smolt abundance. The model results found primarily that smolt abundance was weakly correlated with permanent stream length of 0-4% channel gradient \nand lake area of 0-5 ha. The results suggest that smolt abundance is limited partially by the availability of physical habitat within a watershed. The model performance could have been influenced by uncertainties related to the species life history diversity, identification, and undocumented barriers to fish movement.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".