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Record W2159111005 · doi:10.1109/ca.1994.324010

A multilevel approach to surface response in dynamically deformable models

2002· article· en· W2159111005 on OpenAlexaff
Larry Palazzi, David R. Forsey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiscretizationRepresentation (politics)Flexibility (engineering)Surface (topology)Object (grammar)Computer scienceDisplacement (psychology)Stability (learning theory)StiffnessSimple (philosophy)Point (geometry)Artificial intelligenceComputer visionAlgorithmMathematicsMathematical analysisGeometryStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Discretized representations of deformable objects, based upon simple dynamic point-mass systems, rely upon the propagation of forces between neighbouring elements to produce a global change in the shape of the surface. Attempting to make such a surface rigid produces stiff equations that are costly to evaluate with any numerical stability. This paper introduces a new multilevel approach for controlling the response of a deformable object to external forces. The user specifies the amount of flexibility or stiffness of the surface by controlling how the applied forces propagate through the levels of a multi-resolution representation of the object. A wide range of surface behaviour is possible, and rigid motion is attained without resort to special numerical methods. This technique is applied to the displacement constraints method of Gascuel and Gascuel (1992) to provide explicit graduated control of the response of a deformable object to imposed forces.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.591
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.186
Teacher spread0.169 · 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 teacher head, 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

Citations7
Published2002
Admission routes1
Has abstractyes

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