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Record W2068914701 · doi:10.1115/1.2815329

A New Medical Parallel Robot and Its Static Balancing Optimization

2007· article· en· W2068914701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Medical Devices · 2007
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRobotComputer scienceRevolute jointLinear programmingTorqueSimulationArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

The preoperative procedure for treating peripheral arterial disease requires 3D mapping of the blood vessel of interest. Because the available technologies are costly and invasive, and have an iodizing effect, new 3D imaging systems are being developed from ultrasound scanning technology using a robot as the probe manipulator. The authors of this paper have designed a new parallel robot along these lines. In response to the great concern for safety generated by the use of robots in medicine, we present a new approach for static balancing to enhance the safety of the proposed robot. Because total balancing is not practical for this device, the approach we have chosen is an optimization based on the addition of torsion springs on the actuated and the passive revolute joints. The optimization consists of a sequence of objectives, which are met using a linear programming technique, since the equations of torques and forces are linear with respect to the unknown variables.

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.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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