MétaCan
Menu
Back to cohort
Record W2051089012 · doi:10.1177/107155170401100206

Robot-Assisted Neurosurgery

2004· review· en· W2051089012 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

VenueSurgical Innovation · 2004
Typereview
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRobotMedicineNeurosurgeryStereotaxyMicrosurgerySurgical robotMedical physicsSurgeryComputer scienceSimulationArtificial intelligenceHaptic technology

Abstract

fetched live from OpenAlex

Technological advances in the modern operating room have pushed neurosurgeons to the limits of their dexterity and stamina. Motion scalers and tremor filters on robots permit unprecedented precision of tool manipulation, upgrading the human hand, and closing the deftness deficit. The evolution of neurosurgical robots from stereotactic systems to hybrid systems capable of both stereotaxy and microsurgery is examined. The future of robot-assisted neurosurgery, including expanded tool sets and the prospect of semi-autonomous surgery, is discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.053
GPT teacher head0.316
Teacher spread0.263 · 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