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Record W4292553373 · doi:10.3389/fimmu.2022.959575

Chronic recurrent multifocal osteomyelitis. A narrative and pictorial review

2022· review· en· W4292553373 on OpenAlexafffund
Consolato Sergi, Elka Miller, Dina El Demellawy, Fan Shen, Mingyong Zhang

Bibliographic record

VenueFrontiers in Immunology · 2022
Typereview
Languageen
FieldMedicine
TopicOsteomyelitis and Bone Disorders Research
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern OntarioUniversity of Alberta
FundersWuhan University of Science and TechnologyWuhan UniversityUniversity of Ottawa
KeywordsChronic recurrent multifocal osteomyelitisMedicineMetaphysisPelvisHyperostosisSubclinical infectionOsteomyelitisAxial skeletonRadiologyPathologyAnatomyOsteitisSurgery

Abstract

fetched live from OpenAlex

Chronic recurrent and multifocal osteomyelitis (CRMO) is a nonsporadic autoinflammatory disorder. Currently, it is diagnosed based on clinical, radiologic, pathological, and longitudinal data. Numerous aspects should be highlighted due to increased knowledge in imaging and immunology. We emphasize the use of whole-body MRI, which is a non-invasive diagnostic strategy. A literature review was carried out on longitudinal studies. Commonly, the mean age at diagnosis is 11 years, ranging between 3 and 17. The most common sites are the long bone metaphysis, particularly femoral and tibial metaphysis. In addition, the pelvis, spine, clavicle, and mandible may be involved. In long bones, the radiologic appearance can show typical structure, mixed lytic and sclerotic, sclerotic or lytic. It is frequently metaphyseal or juxta-physeal, with hyperostosis or periosteal thickening. The involvement of the vertebral skeleton is often multifocal. Therefore, whole-body MRI is essential in identifying subclinical lesions. CRMO is a polymorphic disorder in which whole-body MRI is beneficial to demonstrate subclinical edema. Vertebral collapse requires long-term monitoring.

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)0.000
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.354
Teacher spread0.315 · 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

Citations50
Published2022
Admission routes2
Has abstractyes

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