Physical properties of High Arctic tropospheric particles during winter
Bibliographic record
Abstract
Abstract. A climatology of particle properties in the wintertime High Arctic troposphere is constructed using measurements from a lidar and cloud radar located at Eureka, Nunavut Territory (80° N, 86° W). Four different particle groupings are considered: aerosols, mixed-phase clouds, ice clouds and boundary-layer ice crystals. Two-dimensional histograms of occurrence probabilities against depolarization and radar/lidar colour ratio, as well as their vertical distributions, are presented. The largest ice crystals originate from mixed-phase clouds, whereas the smallest are topographic blowing snow residuals in the boundary layer. Ice cloud crystals have depolarization and size decreasing with height. The depolarization trend is associated with the large ice crystal sub-population. Small crystals depolarize more than large ones in ice clouds at a given altitude, and show constant modal depolarization with height. Ice clouds in the mid-troposphere are sometimes observed to precipitate to the ground. Water clouds are constrained to the lower troposphere and are associated with the surface inversion layer depth. Aerosols are most abundant near the ground and are frequently mixed with the other particle types. The data are used to construct a classification chart for particle scattering in wintertime Arctic conditions.
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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 | 0.000 | 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 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".