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Record W1989687011 · doi:10.1109/mra.2008.930401

Surgical and interventional robotics: part III [Tutorial]

2008· article· en· W1989687011 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

VenueIEEE Robotics & Automation Magazine · 2008
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsQueen's University
FundersDivision of Engineering Education and CentersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthNational Science Foundation
KeywordsCADRoboticsWorkstationSurgical robotRobotComputer scienceComputer Aided DesignEngineering drawingMedical physicsArtificial intelligenceSoftware engineeringSystems engineeringHuman–computer interactionEngineeringMedicineOperating system

Abstract

fetched live from OpenAlex

Part I of this tutorial described two broad paradigms of interventional assistance: surgical computer-aided design (CAD)/computer-aided manufacturing (CAM) and surgical assistance. Part II focused on the underlying concepts of surgical CAD/CAM, with a particular emphasis on percutaneous procedures. This final installment of our three-part tutorial series discusses surgical assistance. In this section, we introduce the basic concepts of a surgical workstation and briefly review several core robotic technologies used in surgicalworkstations

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.242
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