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Record W1603487090 · doi:10.1002/cav.1446

Particle‐based drop animation on meshes in real time

2012· article· en· W1603487090 on OpenAlexafffund
Khalid Djado, Richard Egli, Fabrice Granger

Bibliographic record

VenueComputer Animation and Virtual Worlds · 2012
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversité de SherbrookeComputer Research Institute of Montréal
FundersNatural Sciences and Engineering Research Council of CanadaUniversité Bretagne SudUniversité de Sherbrooke
KeywordsPolygon meshComputer scienceDrop (telecommunication)AnimationRendering (computer graphics)Computer graphics (images)Particle systemMechanicsPhysics

Abstract

fetched live from OpenAlex

ABSTRACT This paper presents a method for simulating the motion of water drops on a surface in real time. We describe the dynamics of a drop moving on the surface, and then we present our simulation model. We use a geometry‐based representation of a drop. Each drop is modeled by a deformable 3D mesh. This geometrical representation allows drops to be on the surface or in the air. We also propose a simple method to handle drop merging and separation. For the rendering, we simulate reflection and refraction. The drop trace is also taken into account. Our method is fast and robust and yields realistic results when applied to treat condensation on a surface or human sweating in real time. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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

Citations6
Published2012
Admission routes2
Has abstractyes

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