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Record W2095086749 · doi:10.1139/p02-117

Effects of gravity on directional growth and melting of ice crystals in solution

2003· article· en· W2095086749 on OpenAlexvenueno aff
K. Nagashima, Yoshinori Furukawa

Bibliographic record

VenueCanadian Journal of Physics · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsnot available
Fundersnot available
KeywordsDiffusionIce crystalsPhase (matter)Crystal growthPhysicsThermodynamicsOptics

Abstract

fetched live from OpenAlex

In the present study, side-view images of the solute concentration distribution in water–KCl solution were obtained near the directionally growing and melting ice crystals by Moire phase shift interferometry to elucidate the effect of gravity. The results showed that the concentration distribution of solute changed drastically depending on the growth-cell thickness. In the thickest growth cell used, the concentrated solution near the growth interface flowed down under the influence of gravity and flowed ahead much further than the diffusion length of solute. In the thinnest growth cell, although the fluid motion was almost stabilized, the growth pattern deformed very sensitively to the effect of gravity. During directional melting of ice crystals, the dilute solution released from the melting ice rose up and flowed away from the interface. The cell thickness significantly affected not only the growth process, but also the concentration distribution. In addition, because of interest in sea-ice growth and melting, the downward growth and the upward melting of ice crystals were also studied. It was found that the dense solution accumulated below the growth interface released plumes of dense solution downward. PACS Nos.: 47.20Bp, 66.30Jt, 81.30Fb, 47.20Hw

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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 designBench or experimental
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

Citations5
Published2003
Admission routes1
Has abstractyes

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Same venueCanadian Journal of PhysicsSame topicnanoparticles nucleation surface interactionsFrench-language works237,207