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Record W2023362853 · doi:10.1115/sbc2007-175963

Grasping Contact Analysis of Tissues With Semi-Cylindrical Teeth Grasper for Minimally Invasive Surgery Applications

2007· article· en· W2023362853 on OpenAlexaff
Ali Bonakdar, Marjan Molavi, Javad Dargahi, Rama Bhat

Bibliographic record

VenueASME 2007 Summer Bioengineering Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsConcordia University
Fundersnot available
KeywordsInvasive surgeryBiomedical engineeringMinimally invasive proceduresComputer scienceMaterials scienceSurgeryMedicine

Abstract

fetched live from OpenAlex

This study presents both numerical and analytical methods to determine the contact pressure on the surface of tissues being grasped by an endoscopic grasper with semi-cylindrical teeth, in Minimally Invasive Surgery (MIS). It is highly important to avoid damage to the tissues during grasping and manipulation by endoscopes. Therefore, it is essential to determine the exact contact pressure on the surface of the tissue.

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 categoriesMeta-epidemiology (narrow)
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 score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.264
Teacher spread0.235 · 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.

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

Citations4
Published2007
Admission routes1
Has abstractyes

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