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Record W2783087730 · doi:10.14802/jmd.17066

PSEN1 p.Met233Val in a Complex Neurodegenerative Movement and Neuropsychiatric Disorder

2018· article· en· W2783087730 on OpenAlexafffund
Silke Appel‐Cresswell, Ilaria Guella, Anna Lehman, Dean Foti, Matthew J. Farrer

Bibliographic record

VenueJournal of Movement Disorders · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of British Columbia
FundersCanada Excellence Research Chairs, Government of CanadaGenome British ColumbiaConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsMedicinePSEN1Exome sequencingDystoniaMyoclonusProbandMovement disordersBioinformaticsDiseasePresenilinGeneticsPsychiatryMutationAlzheimer's diseasePathologyBiology

Abstract

fetched live from OpenAlex

p.Met233Val mutation with an exceptionally early and severe presentation that includes a wide range of atypical symptoms, including prominent ataxia, Parkinsonism, spasticity, dystonia, action tremor, myoclonus, bulbar symptoms, seizures, hallucinations and behavioral changes. Whole-exome sequencing (WES) was performed on the affected proband after many assessments over several years proved diagnostically inconclusive. The results were analyzed using the AnnEx "Annotated Exomes" browser (http://annex.can.ubc.ca), a web-based platform that facilitates WES variant annotation and interpretation. High-throughput sequencing can be especially informative for complex neurological disorders, and WES warrants consideration as a first-line clinical test. Data analyses facilitated by web-based bioinformatics tools have great potential for novel insight, although confirmatory, diagnostically accredited Sanger sequencing is recommended prior to reporting.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations15
Published2018
Admission routes2
Has abstractyes

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