Streambed Composition and its Contribution to Spawning Viability Following the Completion of the Stoney Creek Weir Restoration Project
Bibliographic record
Abstract
Salmon populations are highly endangered, and in an attempt to restore these populations, habitat restoration projects have become abundant. The Stoney Creek Environment Committee established one such project to enhance salmon spawning conditions at Stoney Creek in Burnaby, BC, by building three weirs. In this report, the streambed composition of the three weirs is analyzed in relation to salmon spawning conditions for the five species of Salmonidea present in Stoney Creek. The result is a number of spawning viability maps ranking spawning conditions in sections of the weirs for each species. Weir 1 contained the smallest amount of undesirable spawning conditions, mainly because the streambed composition was dominated by cobble. Weir 3 contained the most suitable spawning conditions, with smaller gravel sizes and lower sedimentation levels. We provide rationale to explain which factors may have led to the conditions observed. This is followed by a discussion of our method’s uncertainties and restrictions as well as suggestions for future research and management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".