Aircraft Escape Strategy from Supercooled Cloud Layers
Bibliographic record
Abstract
Vertical profiles of liquid water in supercooled frontal stratiform clouds have been studied in order to estimate the potential rate of ice accretion at different levels within the cloud and to develop recommendations for escape strategies to avoid severe in-flight icing. The vertical soundings of the supercooled liquid clouds were obtained using the National Research Council of Canada Convair-580 equipped by Environment Canada for cloud microphysical measurements. The data were collected during five flight campaigns (CFDE 1, CFDE 3, AIRS 1, AIRS 1.5 and AIRS 2). In total 584 vertical LWC profiles were analyzed. A statistical summary has been prepared from the profiles of the potential thickness of accreted ice, liquid water content, temperature, and cloud depths. The maximum potential accreted thickness of ice does not exceed 2cm for a transit with a 3 degree glide slope thoughout the cloud depth. Based on the statistics, in order to avoid severe icing once significant icing is encountered, it is suggested that a climb or descent should be initiated. The aircraft should not stay at the same altitude within the cloud layer. I.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".