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Record W2113296984 · doi:10.1109/4233.870035

Application of an object-oriented programming paradigm in three-dimensional computer modeling of mechanically active gastrointestinal tissues

2000· article· en· W2113296984 on OpenAlexaff
Peter Z. Rashev, Martin P. Mintchev, Kenneth L. Bowes

Bibliographic record

VenueIEEE Transactions on Information Technology in Biomedicine · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsComputer scienceVisualizationElectrophysiologyBiomedical engineeringArtificial intelligenceNeuroscienceEngineeringBiology

Abstract

fetched live from OpenAlex

The aim of this study was to develop a novel three-dimensional (3-D) object-oriented modeling approach incorporating knowledge of the anatomy, electrophysiology, and mechanics of externally stimulated excitable gastrointestinal (GI) tissues and emphasizing the "stimulus-response" principle of extracting the modeling parameters. The modeling method used clusters of class hierarchies representing GI tissues from three perspectives: 1) anatomical; 2) electrophysiological; and 3) mechanical. We elaborated on the first four phases of the object-oriented system development life-cycle: 1) analysis; 2) design; 3) implementation; and 4) testing. Generalized cylinders were used for the implementation of 3-D tissue objects modeling the cecum, the descending colon, and the colonic circular smooth muscle tissue. The model was tested using external neural electrical tissue excitation of the descending colon with virtual implanted electrodes and the stimulating current density distributions over the modeled surfaces were calculated. Finally, the tissue deformations invoked by electrical stimulation were estimated and represented by a mesh-surface visualization technique.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Citations11
Published2000
Admission routes1
Has abstractyes

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