Evaluation of miniature temperature‐loggers to monitor snowpack evolution at mountain permafrost sites, northwestern Canada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A technique to monitor snowpack development using miniature temperature‐loggers mounted in a vertical array is evaluated from nearly 100 site‐years of measurements in northwestern Canada. The method shows good agreement between interpreted values and actual snow depths checked during site visits. Inferred snowpack build‐up and ablation follow the patterns recorded at nearby climatological stations while absolute amounts and the duration of snow cover vary with elevation and vegetation type. Interpretation of snowpack evolution was possible at 93 per cent of the monitoring sites, a success rate that is judged to be acceptable given the low costs of the technique and the difficulty of obtaining the same information through other methods. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 it