Evaluating the Drought Code Using In Situ Drying Timelags of Feathermoss Duff in Interior Alaska
Bibliographic record
Abstract
The Drought Code (DC) is a moisture code of the Canadian Forest Fire Weather Index System underlain by a hydrological water balance model in which drying occurs in a negative exponential pattern with a relatively long timelag. The model derives from measurements from an evaporimeter and no soil parameters are specified, leaving its physical nature uncertain. One way to approximate the attributes of a “DC equivalent soil” is to compare its drying timelag with measurements of known soils. In situ measurements of timelag were made over the course of a fire season in a black spruce-feathermoss forest floor underlain by permafrost in Interior Alaska, USA. On a seasonally averaged basis, timelag was 28 d. The corresponding timelag of the DC water balance model was 60 d. Water storage capacity in a whole duff column 200 mm deep was 31 mm. Using these figures and a relationship between timelag, water storage capacity, and the potential evaporation rate, a “DC equivalent soil” was determined to be capable of storing 66 mm of water. This amount of water would require a soil 366 mm deep, suggesting a revision of the way fire managers in Alaska regard the correspondence between soil and the moisture codes of the FWI. Nearly half of the soil depth would be mineral rather than organic. Much of the soil water necessary to maintain a 60 d timelag characteristic of a “DC equivalent soil” is frozen until after the solstice. Unavailability of frozen water, coupled with a June peak in the potential evaporation rate, appears to shorten in situ timelags early in the season.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".