Bibliographic record
Abstract
Several post-wildfire debris flows and other landslides occurred after the extreme wildfire season of 2003 in the southern interior of British Columbia. Such events had not been previously reported in Canada, although they are common in lower latitudes. Severe wildfire seasons also were experienced in 2007 and 2009, and additional events were observed in four fires. Post-wildfire landslides have occurred in spring, summer and fall (autumn); events have been triggered by spring snowmelt, high-intensity summer rainstorms and low-intensity fall rainstorms. Of a total of 36 documented events, 23 were debris flows, and the most common initiating mechanism was high peak flow in channels. Most sediment in these events was derived from the channels, not from erosion in burned areas. Seven of the events were infiltration-triggered debris slides, and six events were debris floods. A variety of hydrologic changes can contribute to the prevalence of post-wildfire landslides and floods, including an increase in snowmelt rate. High-severity burn in catchment headwaters above steep channels is a topographic factor favouring debris flow occurrence. These observations demonstrate that the likelihood of debris flows and other mass-movement events in susceptible terrain is significantly increased following severe wildfire in this snow-dominated environment.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".