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Record W2015852104 · doi:10.1080/17482960802654364

Consensus criteria for the diagnosis of frontotemporal cognitive and behavioural syndromes in amyotrophic lateral sclerosis

2009· article· en· W2015852104 on OpenAlexaffabout
Michael J. Strong, Gloria M. Grace, Morris Freedman, Cathy Lomen-Hoerth, Susan Woolley, Laura H. Goldstein, Jennifer Murphy, Christen Shoesmith, Jeffery Rosenfeld, P. Nigel Leigh, Lucie Bruijn, Paul G. Ince, Denise A. Figlewicz

Bibliographic record

VenueAmyotrophic Lateral Sclerosis · 2009
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsALS Society of CanadaUniversity Health NetworkUniversity of TorontoLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsAmyotrophic lateral sclerosisFrontotemporal dementiaFrontotemporal lobar degenerationCognitionDiseaseC9orf72PsychologyDementiaPhysical medicine and rehabilitationMedicineNeurosciencePathology

Abstract

fetched live from OpenAlex

Amyotrophic lateral sclerosis (ALS) is increasingly recognized to be a multisystem disorder which includes both clinical and neuropathological features of a frontotemporal lobar degeneration (FTLD). In order to provide a common framework within which to discuss the characteristics of the cognitive and behavioural syndromes of ALS, and with which to conduct clinical and neuropathological research, an international research workshop on frontotemporal dementia (FTD) and ALS was held in London, Canada in June 2007. The recommendations arising from this research workshop address the requirement for a concise clinical diagnosis of the underlying motor neuron disease (Axis I), defining the cognitive and behavioural dysfunction (Axis II), describing additional non-motor manifestations (Axis III) and identifying the presence of disease modifiers (Axis IV).

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)0.037
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0080.005
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0080.004
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.003

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 head0.112
GPT teacher head0.334
Teacher spread0.221 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations539
Published2009
Admission routes2
Has abstractyes

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