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Record W2040666782 · doi:10.1175/2008jamc1934.1

Drop Size Distributions and the Lack of Small Drops in RICO Rain Shafts

2008· article· en· W2040666782 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Meteorology and Climatology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsPrecipitationEnvironmental scienceRain rateDrop (telecommunication)Spurious relationshipCloud physicsMeteorologyDrizzleAtmospheric sciencesGeologyRemote sensingPhysicsCloud computingMathematics

Abstract

fetched live from OpenAlex

Abstract Data from the new two-dimensional stereo (2D-S) probe are used to evaluate drop size distributions in rain shafts observed during the Rain in Shallow Cumulus over the Ocean (RICO) experiment. The 2D-S takes images of both precipitation drops and cloud droplets with 10-μm resolution. These are the first reported measurements of rain to include sizes smaller than 100 μm. The primary result is that there are almost no hydrometeors smaller than about 100 μm in these rain shafts. The measured low concentration of small hydrometeors implies that their rate of production is slow relative to their removal rate. Algorithms for removing the spurious effects of splashing precipitation and noisy photodiodes on 2D probes are also described.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.239
Teacher spread0.210 · 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