MétaCan
Menu
Back to cohort
Record W4393526577 · doi:10.1007/s00415-024-12289-1

The diagnostic workup of children with the radiologically isolated syndrome differs by age and by sex

2024· article· en· W4393526577 on OpenAlexaff
Naila Makhani, Christine Lebrun‐Frénay, Aksel Sıva, Veronika Shabanova, Evangeline Wassmer, Jonathan D. Santoro, Sona Narula, J. Nicholas Brenton, Soe Mar, Françoise Durand‐Dubief, Hélène Zéphir, Guillaume Mathey, Juan Ignacio Rojas, de Sèze, Sílvia Tenembaum, Robert Thompson Stone, Olivier Casez, Clarisse Carra‐Dallière, Rinze F. Neuteboom, Nusrat Ahsan, H Arroyo, Philippe Cabre, Grace Gombolay, Matilde Inglese, Céline Louapre, Monica Margoni, Filipe Palavra, Daniela Pohl, Daniel S. Reich, Aurélie Ruet, Éric Thouvenot, Niklas Timby, Mar Tintoré, Uğur Uygunoğlu, Wendy Vargas, Sunita Venkateswaran, Hélène Verhelst, Ronny Wickström, Christina Azevedo, Orhun H. Kantarci, Eugene D. Shapiro, Darin T. Okuda, Daniel Pelletier

Bibliographic record

VenueJournal of Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalChildren's Hospital of Eastern Ontario
FundersNational Center for Advancing Translational SciencesCenters for Disease Control and PreventionEuropean Committee for Treatment and Research in Multiple SclerosisMultiple Sclerosis SocietyAlexion PharmaceuticalsNational Institute of Neurological Disorders and StrokeTeva Pharmaceutical IndustriesBiogenIstanbul Üniversitesi-CerrahpasaIstanbul ÜniversitesiCharles H. Hood FoundationNational Institutes of HealthTürkiye Bilimsel ve Teknolojik Araştırma KurumuSanofiNational Multiple Sclerosis Society
KeywordsNeuroradiologyMedicineNeurologyPediatricsRadiologyPsychiatry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
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 score0.492
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.263
Teacher spread0.249 · 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

Citations6
Published2024
Admission routes1
Has abstractno

Explore more

Same venueJournal of NeurologySame topicMultiple Sclerosis Research StudiesFrench-language works237,207