MétaCan
Menu
Back to cohort
Record W4389273753 · doi:10.24297/ijct.v23i.9549

Rotitome-G: Principles and design concept of experimental compliant continuum robotic microsurgical endoscopic sarcotome for pixel/voxel-level target access neurosurgery

2023· article· en· W4389273753 on OpenAlexafffund
Harjeet Singh Gandhi

Bibliographic record

VenueINTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY · 2023
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsHamilton Health Sciences
FundersHamilton Health Sciences
KeywordsEndoscopeComputer scienceArtificial intelligenceTendrilComputer visionMedical physicsSurgeryMedicineBiology

Abstract

fetched live from OpenAlex

The practice of minimal access surgery is widely accepted, and it has become prevalent with improved endoscope design. The traditional microscope in neurosurgery is gradually being challenged by the neuro-endoscope for its direct co-axial vision and direct illumination of the deep set subcortical pathology. The conceptualized design of Rotitome-G is based on compliant continuum robotic system. The system is a biomimicry of muscular hydrostat anatomy of the elephant trunk, a plant tendril, and many similar structures in the animal world with an infinite degree of freedom. The article describes the functional anatomy of these structures and the extensor expansion of the human finger as applied to the construction and implementation of the Rotitome-G. This flexible microsurgical endoscope integral to its design has unique cutting tool versions and multiple assistive tools passed through single ‘target access’ burr hole aperture. It is navigable within the surgical space co-relative to the image space to increase precision and improve the volume of tumour resection. The current study is theoretical and further work is in progress to assess its surgical capabilities to bring it to the clinical arena.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.089
GPT teacher head0.340
Teacher spread0.251 · 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 teacher head, 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueINTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGYSame topicCerebrospinal fluid and hydrocephalusFrench-language works237,207