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Record W4414235345 · doi:10.58530/2025/1091

Reproducibility of advanced MR measures across all 3 major scanner vendors in a longitudinal 5-site multiple sclerosis study

2025· article· en· W4414235345 on OpenAlexaboutno aff
Irene Vavasour, Anthony Traboulsee, Jiwon Oh, Roger Tam, Shannon Kolind

Bibliographic record

VenueProceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsnot available
Fundersnot available
KeywordsReproducibilityIntraclass correlationMultiple sclerosisSpinal cordDiffusion MRIMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Motivation: Advanced brain and spinal cord MRI is being collected in the Canadian prospective cohort study to understand progression in multiple sclerosis (CanProCo). Reproducibility was investigated in healthy controls. Goal(s): Determine reproducibility of brain volumetrics, myelin water fraction, magnetisation transfer ratio, diffusion tensor imaging metrics and spinal cord area across sites. Approach: 52 healthy controls were scanned at year 0 and 1 at a 3T site (2 Siemens, 2 Philips, 1 GE). Reproducibility was assessed using intraclass correlation coefficients, Bland-Altman plots and coefficients of variation. Results: Variability in most MR metrics was similar between sites although values themselves differed for a few metrics. Impact: CanProCo is a Canada-wide study collecting advanced brain and spinal cord MRI. Reproducibility of healthy control data was assessed to enable interpretation of longitudinal multi-site multiple sclerosis data. Variability in most MR metrics over 1 year was similar between sites.

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)0.013
metaresearch head score (Gemma)0.016
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 score0.109
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueProceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and ExhibitionSame topicUltrasound Imaging and ElastographyFrench-language works237,207