Bibliographic record
Abstract
Abstract An all-encompassing new theory of heat and mass transfer (HMT) and growth equations have been developed for freely falling spherical hailstones with diameters of 0.5–8 cm. The initial six variables are diameter, liquid water content, air and hailstone surface temperatures, net collection efficiency, and ice fraction of spongy deposit. They are replaced by three or four new ones, depending on the three growth categories. Two new variables are products of “old” ones: (i) the square root of the Reynolds number Re and the liquid water content and (ii) net collection efficiency and ice fraction of the spongy deposit. Only the products matter, not the individual parts. [The two variables in (ii) are as important as the two in (i).] Two old variables remain: air and surface temperatures. The HMT can be further compacted for hailstorms with specified pressure–air temperature–height profiles. Further, Re for free-fall reveals unexpected complexities—issues important to solve HMT problems. The “new hailstone physics” is based on 55 years of in-house studies of all aspects of hailstone growth, followed by 5 years of shaping these puzzle pieces and assembling them into a coherent picture. This was only possible by recognizing the free-fall mode: a special gyration that allows hailstones to grow with a radial symmetry and, thus, homogeneous surface temperature. Part II will display the surprising solutions to growth and HMT and firmly link the hailstones to mostly spongy growth with shedding that favors a hail-coupled rain mechanism.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".