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Record W2045135441 · doi:10.1109/icsmc.2006.384438

A Macro-Robot Manipulator for Medical Applications

2006· article· en· W2045135441 on OpenAlexaff
Basem F. Yousef, Rajni V. Patel, Mehrdad Moallem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsWorkspaceRobotComputer scienceMacroMobile manipulatorSimulationDisplacement (psychology)Robot kinematicsActuatorControl engineeringEngineeringMobile robotArtificial intelligence

Abstract

fetched live from OpenAlex

An actuated robot arm is designed for use as a macro manipulator that can carry, appropriately orient, precisely position and firmly "lock" in position different types of micro robots and surgical tools necessary for applications in minimally invasive therapy. The sophisticated configuration and joint structure of the arm enable it to perform and interact efficiently with the constrained and limited workspace of surgical environments. The normally locked braking system and the simple quick release joint enhance the safety features of the robot for emergencies and power shutdown. With a simple manipulation protocol, the surgeon can use the robot without undergoing any training. Robot workspace analysis indicates that all singularities are outside the operating work envelope. A performance analysis shows that the robot operates with an average displacement accuracy of 0.58 mm and a roll, pitch and yaw angular accuracies of 0.26deg, 0.26deg and 0.38deg respectively.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0130.006

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 designBench or experimental
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

Citations13
Published2006
Admission routes1
Has abstractyes

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