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Record W1999718790 · doi:10.1055/s-0032-1307259

Uncovertebral Anatomic Midline Targeting for Cervical Disc Arthroplasty

2012· article· en· W1999718790 on OpenAlexaff
Drew A. Bednar

Bibliographic record

VenueGlobal Spine Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineFluoroscopyImplantArthroplastyRadiographySurgeryNuclear medicine

Abstract

fetched live from OpenAlex

Study Design Prospective observational cohort. Objective To document the accuracy of uncovertebral anatomic targeting in positioning cervical disc arthroplasty. Summary of Background Data Disc arthroplasty implants depend on midline placement for optimum mechanical function. Fluoroscopy is used to delineate the midline. Anatomic targeting from the uncovertebral joints in the neck may be adequate. We have investigated the efficacy of uncovertebral anatomic targeting for cervical disc arthroplasty. Methods Anatomic uncovertebral midline targeting for disc arthroplasty insertion was performed in 18 male (mean age 51 years, range 27 to 67) and 22 female (mean age 50, range 35 to 70) patients receiving a total of 59 implants over a 5-year period. Device insertion was under only lateral imaging control. Postinsertion operative fluoroscopy with optimized centering was used to record implant position in the anteroposterior plane, and centerline analysis was performed using cursor measurement technology from the GE PACS™ imaging system (GE Medical Systems, Mt. Prospect, IL). Results Analysis found a mean deviation from the ideal midline placement of only 0.7 mm (range, 0 to 2.9 mm). Only three devices were more than 2 mm off the anatomic midline. Conclusion This anatomic technique is effective, safely minimizing imaging resource needs and X-ray exposure to the patient and operating team.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score1.000

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)0.0010.000

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 head0.018
GPT teacher head0.321
Teacher spread0.303 · 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.

Study designObservational
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

Citations2
Published2012
Admission routes1
Has abstractyes

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