Science and practice of salmonid spawning habitat remediation
Bibliographic record
Abstract
Salmon and trout are evocative symbols of natural river ecosystems. Despite their symbolic (and economic) importance for humans, especially in the case of anadromous salmon and trout, we have inflicted great losses in their numbers and distribution. Within Europe, the Atlantic salmon (Salmo salar) is currently extinct in four countries – Germany, Belgium, the Netherlands and Switzerland – and populations are close to extinction in another six – Spain, France, Portugal, Denmark, Finland and the Baltic states. Only Scotland, Norway, Iceland and Ireland have comparatively healthy populations, although figures suggest that even there salmon numbers are significantly depleted when compared to historical densities (WWF 2001; Youngson et al. 2002; Montgomery 2003). Within North America, current figures indicate that 84% of Atlantic salmon populations are now extinct, with the remaining populations in a critical condition (WWF 2001). In Canada, the picture is less severe, although only 8% of populations have recently been classified as healthy. Figures for Pacific salmon (Oncorhynchus spp.) indicate that populations have also declined, and 17 Pacific salmon runs are now extinct, with a further 214 runs at risk of extinction or of special concern (Nehlsen et al. 1991; Huntington et al. 1996; Shea and Mangel 2001). Alaska remains the primary natural haven in North America where one can observe Pacific salmon populations in a more or less pristine state, although even here returning salmon numbers are affected by fisheries harvest. Unfortunately, declining salmon numbers are not a recent phenomenon and historical accounts reveal a tortuous path of decline that traces human influence over riverine landscapes (Montgomery 2003). For some, the future for many salmon and trout populations can appear bleak (Lackey et al. 2006).
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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 | 0.018 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.020 |
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".