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Record W4286582004 · doi:10.5772/intechopen.98110

Multiple Sclerosis - Genetics, Disease Mechanisms and Clinical Developments

2022· book· en· W4286582004 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntechOpen eBooks · 2022
Typebook
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsInstitute of Infection and Immunity
FundersMedical Research CouncilEuropean CommissionRoyal Society of BiologyWellcome TrustRoyal College of Pathologists of AustralasiaNational Aeronautics and Space Administration
KeywordsMultiple sclerosisDiseaseMedical geneticsGeneticsBiologyEvolutionary biologyComputational biologyMedicinePathologyImmunologyGene

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a lifelong neurological condition that has no known cure. This book provides an extensive exploration of current and future directions for understanding immunology, neuroscience, and the development of potent treatment modalities. It presents an in-depth analysis and expert commentary on the role of genetics, lifestyle factors, biomarkers, neuroimaging, cognitive domains, artificial intelligence, and innate immunity in MS pathogenesis. We hope that the book is helpful to readers of all spheres of life, including those who want to understand more about MS, those who are keen to improve their understanding of MS disease pathogenesis, those who are enthusiastic to know more about treatment modalities, and those who want to be informed about state-of-the-art clinical developments in MS.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.003
Research integrity0.0010.001
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 head0.053
GPT teacher head0.306
Teacher spread0.253 · 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