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Record W1748229947 · doi:10.1017/cbo9780511543760

The Clinical Neuropsychiatry of Multiple Sclerosis

2007· book· en· W1748229947 on OpenAlexaff
Anthony Feinstein

Bibliographic record

VenueCambridge University Press eBooks · 2007
Typebook
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeuropsychiatryPsychosocialDepression (economics)Multiple sclerosisNeuropsychological assessmentNatural historyNeuropsychologyPsychiatryPsychologyCognitionMedicineClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

Multiple sclerosis is the most common cause of neurological disability in young and middle-aged adults. This fully updated and revised new edition provides a detailed account of the many neuropsychiatric disorders associated with MS and is relevant to both the research and the clinical setting. Using the latest brain imaging findings and results from treatment trials, the symptoms, assessment, diagnosis, and treatment of depression in MS are covered, as are psychosocial factors and the link between depression and MRI abnormalities. Subsequent chapters focus on cognitive dysfunction in MS, including the natural history of cognitive change, the use of screening instruments and neuropsychological batteries, brain imaging correlations and management strategies. The book concludes with a survey of the behavioral benefits and risks associated with disease-modifying drugs. It will be valuable to all mental health professionals, neurologists, and others caring for those affected by 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.

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)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0330.032

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 head0.111
GPT teacher head0.305
Teacher spread0.194 · 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
GenreOther

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

Citations65
Published2007
Admission routes1
Has abstractyes

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