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Determinants of Therapeutic Lag in Multiple Sclerosis (2059)

2020· article· en· W3083348652 on OpenAlexaff
Izanne Roos, Emmanuelle Leray, Federico Frascoli, Romain Casey, Dana Horáková, Eva Havrdová, María Trojano, Guillermo Izquierdo Ayuso, Sara Eichau Madueño, Francesco Patti, Alexandre Prat, Marc Girard, Pierre Duquette, Marco Onofrj, Alessandra Lugaresi, Pierre Grammond, Serkan Özakbaş, Patrizia Sola, Diana Ferraro, Roberto Bergamaschi, Maria Aragüés José, Cavit Boz, François Grand’Maison, Jeannette Lechner‐Scott, Murat Terzi, Franco Granella, Gerardo Iuliano, Daniele Spitaleri, Vincent Van Pesch, Aysun Soysal, Francisco Javier Olascoaga Urtaza, Eduardo Agüera, Recai Türkoğlu, Mark Slee, Cristina Ramo, Youssef Sidhom, Riadh Gouider, Pamela McCombe, Helmut Butzkueven, Charles B. Malpas, Sandra Vukusic, Tomáš Kalinčík

Bibliographic record

VenueNeurology · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des LaurentidesCégep de LévisHôpital Notre-Dame
Fundersnot available
KeywordsLag timeLagMultiple sclerosisTime lagMedicineComputational biologyBiologyComputer scienceImmunologyBiological system

Abstract

fetched live from OpenAlex

To explore the associations of patient and disease characteristics with the duration of therapeutic lag for relapses and disability progression.

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)0.006
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.165
GPT teacher head0.331
Teacher spread0.166 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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