Bibliographic record
Abstract
Abstract Snow surface temperature (Ts) plays an important role in the formation of surface hoar or near-surface faceted crystals The goal of this study was to obtain detailed information on Ts in different forest stands nelr the timberline. The investigations were conducted during clear nights and showed that the snow surface temperature is influenced very strongly by the forest canopy. While the air temperature was very similar on the different experimental sites, Ts was higher in the forest than in the open field; on the south-facing slope the difference between the forest and the open field was 3–4.5°C, and on the north-facing slope approximately 3–7°C. Taking into account that εair is 0.7 and εtree is 0.94, the incoming radiation (I ↓) for the different experimental sites was calculated by the equation of Brunt (the canopy density was estimated using photographs taken with an 8 mm fish-eye). To calculate Ts, air temperature and averaged values of the net radiation (because the net radiation (I) has only a small range of variation during clear nights) were used. The results show that the calculated values were higher than the measured values (by approximately 2°C). However, a better correlation was found by using lower values of the emissivity (εair0.67 and εtree0.91).
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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".