Bibliographic record
Abstract
Abstract Forest disturbance has a significant impact on hydrology due to its effect on the forest canopy, which is important for precipitation interception, transpiration, site micrometeorology, and snow accumulation and ablation. This study examines the impact of mountain pine beetle infestation and subsequent forest death on snow ablation. Dead stands experience needle loss and canopy reduction due mainly to the loss of small branches and stems, which has a subsequent impact on micrometeorological conditions. Ablation is driven largely by incoming short‐wave radiation, which in dead stands is greater than in alive stands, but does not reach that available in clearcuts. Long‐wave radiation emission in dead stands is lower than that in alive stands, reducing its contribution to snowpack warming and ablation. Turbulent flux contributions to snow ablation are limited in forest stands relative to clearcuts, although they are slightly greater in dead than alive stands due to the more open forest structure. Additional studies are required to refine the basic energy balance model and incorporate all processes affecting the snow ablation energy balance. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".