An empirical-statistical model for debris flow travel distance
Bibliographic record
Abstract
An empirical model is presented for analysis of debris flows based on field observations of landslides from clear-cuts in the Queen Charlotte Islands, British Columbia. Given an initial failure volume, changes in event magnitude arising from entrainment and deposition along the path of movement are used to establish the point at which the cumulative flow volume diminishes to zero, and therefore the total travel distance. Hillslope morphology is used to assign three types of flow behaviour: unconfined, confined, and transition flow. Flow behaviour and slope angle determine the occurrence of entrainment or deposition in the model, for every reach of the event path. Volume change in a reach is calculated from regression analysis of the Queen Charlotte Islands field observations. Predictor variables are reach length, width (of entrainment and (or) deposition), and slope angle, together with a bend-angle function and the incoming flow volume.Key words: slope stability, debris flow, travel distance, runout, risk, clear-cut.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".