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Record W2792758496 · doi:10.4184/asj.2018.12.1.94

Quantitative Magnetic Resonance Imaging Analysis of the Cervical Spine Extensor Muscles: Intrarater and Interrater Reliability of a Novice and an Experienced Rater

2018· article· en· W2792758496 on OpenAlexaff
Maryse Fortin, Octavian Dobrescu, Peter Jarzem, Jean Ouellet, Michael H. Weber

Bibliographic record

VenueAsian Spine Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsInter-rater reliabilityIntraclass correlationMedicineMagnetic resonance imagingIntra-rater reliabilityReliability (semiconductor)Physical medicine and rehabilitationPhysical therapyStandard errorNuclear medicineRadiologyPsychometricsPsychologyRating scaleStatisticsInternal medicineConfidence intervalDevelopmental psychology

Abstract

fetched live from OpenAlex

<sec><title>Study Design</title><p>Reliability study.</p></sec><sec><title>Purpose</title><p>To examine the reliability of novice and experienced raters for measurements of the size and composition of the cervical extensor muscles using a thresholding technique.</p></sec><sec><title>Overview of Literature</title><p>Although some authors have reported on the dependability of magnetic resonance imaging (MRI) measurements of the cervical muscles, there remains some variability regarding intrarater and interrater reliabilities, and few studies have examined the associated measurement error. Whether the rater's experience noticeably influences the reliability and precision of such measurements has also not been examined.</p></sec><sec><title>Methods</title><p>A sample of 10 patients with cervical pathologies was selected. Muscle cross-sectional area (CSA), functional cross-sectional area (FCSA), and signal intensity of the cervical extensor muscles were acquired from axial T2-weighted MRIs by a novice and an experienced rater. All measurements were obtained twice, at least 5 days apart, while the raters were blinded to all earlier measurements.</p></sec><sec><title>Results</title><p>Interrater reliability estimates (intraclass correlation coefficients) varied between 0.84 and 0.99 for the novice rater and between 0.94 and 0.99 for the experienced rater, indicating excellent reliability. The standard error of measurement for the novice rater was, however, noticeably higher for all cervical muscle measurements. Most of the interrater estimates showed excellent agreement with the exception of CSA measurement of the semispinalis cervicis at C4–C7 and FCSA measurement of the multifidus and semispinalis cervicis at C4–C7, which showed poor interrater reliability.</p></sec><sec><title>Conclusions</title><p>The proposed method of investigating cervical muscle measurements was highly reliable; however, novice raters should receive adequate training before using this method for diagnostic, research, and clinical purposes.</p></sec>

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.316
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.

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

Citations15
Published2018
Admission routes1
Has abstractyes

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