Thermal Properties of Tree Cavities During Winter in a Northern Hardwood Forest
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Tree cavities likely vary in their thermal quality for cavity‐nesting animals, which could be especially important during winter. We conducted a winter field experiment to test whether cavities vary either in their buffering capacity or in their mean temperature according to predictable characteristics. We found that cavities buffered temperature and that there was a lag effect in temperature that appeared to be related to heating and cooling. Diameter at breast height was the most important variable influencing cavity temperature during the day, with smaller trees warming up more. During the night, diameter at breast height and tree decay class were important, such that larger, live trees cooled down less. Maintaining live trees with cavities in managed forests should be considered in addition to snag retention, because live trees appear to provide warmer structures during winter.
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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 | 0.000 | 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) | 0.002 | 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