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The engineering of an interventional MRI with a movable 1.5 Tesla magnet

2001· article· en· W2006560595 on OpenAlexafffund
D. I. Hoult, John K. Saunders, Garnette R. Sutherland, Jonathan C. Sharp, Marcia Gervin, H. Glen Kolansky, D. Kripiakevich, Andrew E. Procca, Rudy Sebastian, Akos Dombay, David L. Rayner, Frank A. Roberts, Bogusław Tomanek

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2001
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of CalgaryNational Research Council Institute for Biodiagnostics
FundersNational Research Council Canada
KeywordsLimitingMagnetic resonance imagingMedicineMagnetComputer scienceRadiologyMedical physicsEngineeringElectrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The engineering of a novel intra-operative MRI system is described. A movable, 1.5 Tesla MRI magnet was placed in a neurosurgical operating room without affecting established neurosurgical procedure. The system allows fast, high-quality MR intra-operative imaging of the brain and spine without the necessity of patient transportation. A neuro-navigational device capable of displaying and updating spatially referenced MR images in the operating room was integrated with the MRI system. Over 100 procedures have been carried out with this system without limiting surgical access and without compromising traditional neurosurgical, nursing or anesthetic techniques. J. Magn. Reson. Imaging 2001;13:78-86.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.225

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 head0.007
GPT teacher head0.273
Teacher spread0.266 · 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 designOther design
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

Citations35
Published2001
Admission routes2
Has abstractyes

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