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Record W2162383878 · doi:10.1109/robot.2004.1307178

Design issues in a haptics-based master-slave system for minimally invasive surgery

2004· article· en· W2162383878 on OpenAlexaff
Mahdi Tavakoli, R.V. PateI, Mehrdad Moallem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsHaptic technologyInvasive surgeryComputer scienceRobot end effectorRobotRobotic surgeryInterface (matter)Human–computer interactionMaster/slaveMinimally invasive proceduresMedical roboticsSimulationSurgeryArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

Minimally invasive surgery (MIS) is an alternative to open surgery where special instruments are inserted into the body cavity through tiny incisions in order to perform surgical procedures. In this work, some design issues in a master-slave robotic system for use in MIS are discussed. First, we discuss the design of a user interface that can be used to incorporate haptic interaction in robot-assisted MIS. Then we discuss the design of a laparoscopic end effector that meets MlS requirements and is instrumented for haptic feedback.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.231
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations43
Published2004
Admission routes1
Has abstractyes

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