Lidar measurements of thin laminations within Arctic clouds
Bibliographic record
Abstract
Very thin ( < 10 m) laminations within Arctic clouds have been observed in all seasons using the Canadian Network for the Detection of Atmospheric Change (CANDAC) Rayleigh–Mie–Raman lidar (CRL) at the Polar Environment Atmospheric Research Laboratory (PEARL; located at Eureka, Nunavut, in the Canadian High Arctic). CRL's time (1 min) and altitude (7.5 m) resolutions from 500 m to greater than 12 km altitude make these measurements possible. We have observed a variety of thicknesses for individual laminations, with some at least as thin as the detection limit of the lidar (7.5 m). The clouds which contain the laminated features are typically found below 4 km, can last longer than 24 h, and occur most frequently during periods of snow and rain, often during very stable temperature inversion conditions. Results are presented for range-scaled photocounts at 532 and 355 nm, ratios of 532∕355 nm photocounts, and the 532 nm linear depolarization parameter, and with context provided by twice-daily Eureka radiosonde temperature and relative humidity profiles.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".