The Bowron River watershed: a landscape level assessment of post-beetle change in stream riparian function.
Bibliographic record
Abstract
Streams and riparian areas in the Bowron River watershed were assessed using the Routine Riparian Effectiveness Evaluation (RREE) to determine their level of ecological function 20-30 years after accelerated harvest activity. The RREE is a procedure that includes both stream and riparian indicators to assess the health and condition of a stream reach. Sites in heavily harvested sub-basins had lower overall evaluation scores than reference sites, mainly because of high failure rates of riparian indicators. Larger streams located lower in the sub-basin appeared to score slightly better than those in the upper basin and this is likely due to a larger riparian buffer at lower basin sites. A regeneration time of 20-30 years after clearcutting was determined to be insufficient for the recovery of riparian indicators to pre-harvest conditions. Variation among sites with respect to stream indicators appeared higher within the harvested and reference groups than between them, indicating that harvesting effects have diminished and natural variability is a stronger governing factor. The within-group variability was explained in part by differences in slope, channel width, coupling and soil erodibility. Recommendations for salvage logging best management practices are given based on observations of recovery from past harvesting activities and site specific characteristics.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".