Atmospheric Physics As Observed By A Vertically Pointing Doppler Radar
Bibliographic record
Abstract
ddress: Frdric Fabry, Dept. Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. W., Montreal, Quebec, H3A 2K6, Canada; E-mail: frederic@radar.mcgill.ca. FIG. 2. Examples of the 5 classes of vertical reflectivity profiles in rain. All time-height sections span over 40 min and show echoes from 0.2 km to 7 km. a) Low level drizzle (bottom, class wS) accompanied by a palm-tree shaped echo with a bright band (class cS). Note how low the drizzle forms compared with the height of the 0C isotherm indicated by the bright band. b) Rain with bright band (class cS). c) Rain from compact ice (class cM). Observe the increase in reflectivity at the same height as the bright band in b). d) Showers (class wC, 0450-0505) within drizzle echoes. e) Deep convection (class cC) from a squall line. Adapted from Fabry and Zawadzki (1995). A more careful analysis of radar echoes from rain shows that, occasionally, rain falling at the ground at a given instan
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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 | 0.000 | 0.001 |
| 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) | 0.005 | 0.001 |
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".