A practical method for forecasting rockfall ditch effectiveness deterioration
Bibliographic record
Abstract
Rockfall ditch effectiveness is a common component in risk calculations for cut slopes. Therefore, understanding ditch effectiveness deterioration is vital for forecasting changes in slope risk. However, studies analyzing changes in ditch behavior over time are limited. In this study, we propose a practical method for forecasting ditch effectiveness deterioration based on a conceptual model. The model assumes that ditch effectiveness is zero once a talus pile of rockfall debris has formed to its angle of repose. Using initial ditch effectiveness estimates, rockfall frequency estimates, and assuming linear deterioration of ditch effectiveness as a function of volume in the talus pile, ditch effectiveness can be forecasted. To evaluate the conceptual model, rockfall trajectory numerical models were developed for different cut slope and ditch geometries. Ditch-filling was simulated by approximating talus pile geometry as a triangle. The talus pile angle was increased incrementally until the angle of repose was reached, and ditch effectiveness was recorded as proportion of rockfall retained. Numerical modeling results can be approximated with our conceptual model for steeper cut slopes (∼4V:1H), while the conceptual model is conservative relative to modeling results for shallower cut slopes; we attribute this to the transition from bouncing- to rolling-dominated rockfall trajectories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".