fireexposuR: An R package for computing and visualizing wildfire exposure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
fireexposuR (v1.2.0) is an R package that automates wildfire exposure methodologies presented in several scientific publications (Beverly et al., 2010(Beverly et al., , 2021;;Beverly & Forbes, 2023), providing an accessible and adaptable platform to a broad user base.Wildfire exposure is a numeric rating of potential wildfire transmission to, or from, a location based on the composition and configuration of the surrounding wildland fuels (i.e., flammable vegetation).Exposure assessments can be applied at multiple spatial scales (e.g., neighbourhood, region, country) to inform a wide range of management objectives and decisions (e.g., fuel management priorities, evacuation planning, land-use planning, habitat conservation, firefighting resource optimization); and are particularly well-suited for scenario and contingency planning.fireexposuR has functions for computational analysis and generating visualizations of results in summary tables, plots, and maps.
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.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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 it