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Record W4280557253 · doi:10.1177/23259671221083589

Glenoid Version Assessment When the CT Field of View Does Not Permit the Friedman Method: The Robertson Method

2022· article· en· W4280557253 on OpenAlexaff
Douglas D. Robertson, Gulshan B. Sharma, Patrick J. McMahon, Spero G. Karas

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineField (mathematics)OrthodonticsCalculus (dental)Pure mathematicsMathematics

Abstract

fetched live from OpenAlex

Background: To improve spatial resolution, current clinical shoulder cross-sectional imaging studies reduce the field of view of the shoulder, excluding the medial scapula border and preventing glenoid version measurement according to the Friedman method. Purpose: To evaluate a method to accurately and reliably measure glenoid version on cross-sectional shoulder images when the medial scapula border is not included in the field of view, and to establish measurements equivalent to the Friedman method. Study Design: Controlled laboratory study. Methods: Sixty-five scapulae underwent computed tomography (CT) scanning with an optimal shoulder CT-positioning protocol. Glenoid version was measured on CT images of the full scapula using the Friedman method. We developed a measurement method (named the Robertson method) based on the glenoid vault version from partial scapula images, with a correction angle subtracted from the articular-surface-glenoid vault measurement. Comparison with the Friedman method defined the accuracy of the Robertson method. Three observers tested inter- and intraobserver reliability of the Robertson method. Accuracy was statistically evaluated with t tests and reliability with the intraclass correlation coefficient (ICC). Results: The statistical distribution of glenoid version was similar to published data,–0.5° ± 3° [mean ± SD]. The initial measurement using the Robertson method resulted in a more retroverted angle compared with the Friedman method, and a correction angle of 7° was then applied. After this adjustment, the difference between the 2 methods was nonsignificant (0.1° ± 4°; P > .65). Reliability of the Robertson method was excellent, as the interrater ICC was 0.77, the standard error of measurement (SEM) was 1.1° with P < .001. The intrarater ICC ranged between 0.84 and 0.92, the SEM ranged between 0.9° and 1.2° with P < .01. Conclusion: A validated glenoid version measurement method is now available for current clinical shoulder CT protocols that reliably create Friedman-equivalent values. Clinical Relevance: Friedman-equivalent values may be made from common clinical CTs of the shoulder and compared with prior and future Friedman measurements of the scapula.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.355
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2022
Admission routes1
Has abstractyes

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