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Record W2159344837 · doi:10.1175/jas-d-12-0164.1

New Hailstone Physics. Part I: Heat and Mass Transfer (HMT) and Growth

2013· article· en· W2159344837 on OpenAlexaff
Roland List

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHomogeneousLiquid water contentHeat transferMass transferFraction (chemistry)MechanicsMass fractionMaterials scienceMeteorologyPhysicsAstrophysicsAtmospheric sciencesThermodynamicsChemistryChromatographyComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.020
GPT teacher head0.207
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2013
Admission routes1
Has abstractyes

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