Forest landowner decisions and the value of information under fire risk
Bibliographic record
Abstract
We estimate the value of three types of information about fire risk to a nonindustrial forest landowner: the relationship between fire arrival rates and stand age, the magnitude of fire arrival rates, and the efficacy of fuel reduction treatment. Our model incorporates planting density and the level and timing of fuel reduction treatment as landowner decisions. These factors affect, among other things, the loss a landowner incurs should fire arrive before harvesting. The value of information depends on the nature and combination of mistakes a landowner makes, the relationship between fire arrival and stand age, and on whether the landowner undertakes fuel treatment and values nontimber benefits. Information of various types is of most value to a landowner who does not undertake fuel treatment. The value of information about the magnitude of fire risk is also more than twice as high when the landowner underestimates fire risk, rather than overestimating it. For a landowner who undertakes fuel treatment but makes multiple mistakes, the asymmetry between overestimating and underestimating fire risk and efficacy of fuel reduction is even more pronounced.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".