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Record W2564558365 · doi:10.1101/cshperspect.a024117

Clinical Spectrum of Amyotrophic Lateral Sclerosis (ALS)

2016· review· en· W2564558365 on OpenAlexaff
Leslie I. Grad, Guy A. Rouleau, John Ravits, Neil R. Cashman

Bibliographic record

VenueCold Spring Harbor Perspectives in Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsAmyotrophic lateral sclerosisProgressive muscular atrophyPhenotypeUpper motor neuronLower motor neuronAtrophyMotor neuronNeuroscienceMutationDiseaseBiologyPathologyGeneMedicineGenetics

Abstract

fetched live from OpenAlex

Amyotrophic lateral sclerosis (ALS) is primarily characterized by progressive loss of motor neurons, although there is marked phenotypic heterogeneity between cases. Typical, or "classical," ALS is associated with simultaneous upper motor neuron (UMN) and lower motor neuron (LMN) involvement at disease onset, whereas atypical forms, such as primary lateral sclerosis and progressive muscular atrophy, have early and predominant involvement in the UMN and LMN, respectively. The varying phenotypes can be so distinctive that they would seem to have differing biology. Because the same phenotypes can have multiple causes, including different gene mutations, there may be multiple molecular mechanisms causing ALS, implying that the disease is a syndrome. Conversely, multiple phenotypes can be caused by a single gene mutation; thus, a single molecular mechanism could be compatible with clinical heterogeneity. The pathogenic mechanism(s) in ALS remain unknown, but active propagation of the pathology neuroanatomically is likely a primary component.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.147
GPT teacher head0.424
Teacher spread0.277 · 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
GenreReview

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

Citations311
Published2016
Admission routes1
Has abstractyes

Explore more

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