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Record W2914530644 · doi:10.1080/01677063.2019.1566326

High diagnostic yield and novel variants in very late-onset spasticity

2019· article· en· W2914530644 on OpenAlexaff
Momen Almomen, Kristina Martens, Asfia Quadir, Carly Sabine Pontifex, Alexandra Hanson, Lawrence Korngut, Gerald Pfeffer

Bibliographic record

VenueJournal of Neurogenetics · 2019
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCohortGenetic testingGeneticsGenotypeBiologyPhenotypeMutationDNA sequencingMedicineInternal medicineGene

Abstract

fetched live from OpenAlex

Hereditary spastic paraplegias (HSPs) are a diverse group of genetic conditions with variable severity and onset age. From a neurogenetic clinic, we identified 14 patients with very late-onset HSP, with symptoms starting after the age of 35. In this cohort, sequencing of known genetic causes was performed using clinically available HSP sequencing panels. We identified 4 patients with mutations in SPG7 and 3 patients with SPAST mutations, representing 50% of the cohort and indicating a very high diagnostic yield. In the SPG7 group, we identified novel variants in two patients. We have also identified two novel mutations in the SPAST group. We present sequencing data from cDNA and RT-qPCR to support the pathogenicity of these variants, and provide observations regarding the poor genotype-phenotype correlation in these conditions that should be the subject of future study.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.240
Teacher spread0.207 · 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 designObservational
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

Citations9
Published2019
Admission routes1
Has abstractyes

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