Salmon Habitat Restoration Practice in Vancouver Island: An active review of the literature developed by restoration practitioners to restore salmon habitat degraded by forestry practises.
Bibliographic record
Abstract
Wild Salmon on the Pacific Northwest coast are under threat. Historical silvicultural activities, both timber harvesting and road construction have degraded salmon habitat all over the coast to the point that many watersheds currently require restoration. This project developed an interactive tool to review the project reports developed by restoration practitioners to restore salmon habitat degraded by silviculture practices on Vancouver Island, British Columbia, Canada. The project reviewed restoration reports on this specific area of restoration to serve as a first step to inform future restoration projects or people interested in salmon habitat restoration. The project also serves as a repository where grey literature on this topic can be easily accessed. This project stores restoration reports describing management actions planned, underway, and completed easily accessible. This project surveyed non-scholarly sources (grey literature) to provide an overview highlighting a variety of attributes such as: The name of organizations carrying out the project Date of publication and timeline of the project A description of the location and overview of ecosystems managed Project expenditures and funding sources A summary of the methods/techniques used Evaluation of project outcomes Compilation of monitoring data
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.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".