q 2001 American Meteorological Society Assessing Cloud-Phase Conditions
Bibliographic record
Abstract
In situ microphysics measurements made during the First and Third Canadian Freezing Drizzle Experiments (CFDE I and III, respectively) have been used to assess the relative responses to ice and liquid hydrometeors for several common instruments. These included the Rosemount icing detector, 2D-C monoscale and 2D-C grayscale probes, forward-scattering spectrometer probes (FSSP) on three measurement ranges, Nevzorov liquid water content (LWC) and total water content probes, and King LWC probes. The Nevzorov LWC and King LWC probes responded to between 5 % and 30 % of the ice water content, with an average response of approx-imately 20%. The average FSSP measurements of droplet spectra were dominated by ice particles for sizes greater than 35 mm, independent of the measurement range used, when the ice-crystal concentrations exceeded approximately 1 L21. In contrast, the FSSP measurements of the droplet spectra less than 30 mm appeared free of ice-crystal contamination, independent of the ice-crystal concentrations observed. Glaciated cloud conditions always had FSSP-measured median volume diameters greater than 30 mm and particle concentrations less than 15 cm23, whereas similar measurements in entirely liquid-phase clouds were observed less than 4 % of the time. Images of drops greater than or equal to 125 mm in diameter, which were collected in warm clouds greater than 08C, were used to calibrate geometric criteria, which were, in turn, used to segregate 2D images into circular
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.020 |
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".