The influence of bedrock type on the magnitude, frequency and spatial distribution of debris torrents on Northern Vancouver Island
Bibliographic record
Abstract
This thesis examines the influence of lithology on debris torrent occurrence. The analysis covers a thirty-year period in 80 supply-limited basins distributed in the 400 km2 Tsitika River watershed, on northern Vancouver Island, British Columbia. Two bedrock types occur in the watershed, the Igneous Intrusive and the extrusive Karmutsen formations, covering forty-nine and fifty-one percent respectively. The debris torrent source basins are unlogged. The frequency data were obtained in the field using dendrochronological evidence of debris torrents. Field data were compared with data derived from air photographs, the latter were found to be unrepresentative of debris torrent occurrence and were not used. All study basins were digitised from 1 : 20 000 Terrain Resource Inventory Maps (TRIM), and were characterised by selected morphometric parameters. Results show that geology exerts significant control over the temporal and spatial occurrence of debris torrents in the Tsitika watershed; the Karmutsen formation is more prolific. Geology also was found to exert significant control over the runout area and volume of debris torrents. Climate, morphometry and surficial materials do not appear to be confounding parameters. Differences in weathering rates, infiltration patterns and detrital grain-size distribution associated with the two bedrock types are believed to account for the differences in debris torrent behaviour.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".