MétaCan
Menu
Back to cohort
Record W2962956776 · doi:10.1186/s13244-019-0752-4

MRI of the axial skeleton in spondyloarthritis: the many faces of new bone formation

2019· review· en· W2962956776 on OpenAlexaff
Frederiek Laloo, Nele Herregods, Jacob L. Jaremko, Philippe Carron, Dirk Elewaut, Filip Van den Bosch, Koenraad Verstraete, Lennart Jans

Bibliographic record

VenueInsights into Imaging · 2019
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsMedicineNeuroradiologyMagnetic resonance imagingAxial skeletonRadiologyModality (human–computer interaction)Axial spondyloarthritisInterventional radiologySkeleton (computer programming)PathologyAnatomyNeurologyComputer scienceArtificial intelligenceSacroiliitis

Abstract

fetched live from OpenAlex

Spondyloarthritis has two hallmark features: active inflammation and structural lesions with new bone formation. MRI is well suited to assess active inflammation, but there is increasing interest in the role of structural lesions at MRI. Recent MRI studies have examined the established features of new bone formation and demonstrated some novel features which show diagnostic value and might even have potential as possible markers of disease progression. Although MRI is not the first imaging modality that comes into mind for assessment of bony changes, these features of new bone formation can be detected on MRI-if one knows how to recognize them. This review illustrates the MRI features of new bone formation and addresses possible pitfalls.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.031
GPT teacher head0.314
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInsights into ImagingSame topicSpondyloarthritis Studies and TreatmentsFrench-language works237,207