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Record W2958983479 · doi:10.1093/hmg/ddz162

Inherited and Sporadic Amyotrophic Lateral Sclerosis and Fronto-Temporal Lobar Degenerations arising from Pathological Condensates of Phase Separating Proteins

2019· review· en· W2958983479 on OpenAlexafffund
Michael S. Fernandopulle, GuoZhen Wang, Jonathon Nixon‐Abell, Seema Qamar, Varun Balaji, Ryuta Morihara, Peter St George‐Hyslop

Bibliographic record

VenueHuman Molecular Genetics · 2019
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchAlzheimer SocietyWellcome TrustWellcome
KeywordsAmyotrophic lateral sclerosisFrontotemporal lobar degenerationPathologicalPathogenesisMissense mutationNeuroscienceBiologyMutationMedicinePathologyGeneticsDiseaseGeneFrontotemporal dementiaDementia

Abstract

fetched live from OpenAlex

Recent work on the biophysics of proteins with low complexity, intrinsically disordered domains that have the capacity to form biological condensates has profoundly altered the concepts about the pathogenesis of inherited and sporadic neurodegenerative disorders associated with pathological accumulation of these proteins. In the present review, we use the FUS, TDP-43 and A11 proteins as examples to illustrate how missense mutations and aberrant post-translational modifications of these proteins cause amyotrophic lateral sclerosis (ALS) and fronto-temporal lobar degeneration (FTLD).

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)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.158
GPT teacher head0.396
Teacher spread0.238 · 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

Citations19
Published2019
Admission routes2
Has abstractyes

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