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Record W2167119829 · doi:10.3109/21678421.2012.754044

Familial amyotrophic lateral sclerosis in Alberta, Canada

2013· article· en· W2167119829 on OpenAlexaffabout
Ted Pfister, Ramnik Sekhon, Mitchell White, Patrick Scott, Susan Munro, Megan Johnston, Sanjay Kalra, Lawrence Korngut

Bibliographic record

VenueAmyotrophic Lateral Sclerosis and Frontotemporal Degeneration · 2013
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsHotchkiss Brain InstituteUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsAmyotrophic lateral sclerosisSOD1EpidemiologyMedicineGenotypePediatricsRetrospective cohort studyDemographyInternal medicineDiseaseGeneticsBiology

Abstract

fetched live from OpenAlex

Systematic review data demonstrate that 5% of ALS cases are familial (FALS). Causative superoxide dismutase-1 (SOD1) mutations are identified in 10-20% of FALS. Few reports of FALS epidemiology exist in Canada. We completed a retrospective review of all FALS cases within the province of Alberta between 2002 and 2011. Descriptive summaries of genotypes identified and calculation of prevalences were performed. We reviewed 946 clinic database records and 49 subjects with FALS were identified (5.2%). Clinic charts for 47/49 were available and reviewed. Causative SOD1 mutations were observed in 17/47 (36%). The SOD1 I113T mutation was identified in 11/47 unrelated patients and was associated with a less variable survival than previously reported. The period and point prevalences of FALS in Alberta are approximately 2.05 per 100,000 (95% CI 1.51-2.73) and 4.68 per 1,000,000 (95% CI 2.42-8.18), respectively. In conclusion, we report 47 cases of FALS in Alberta over the past decade. The proportion of SOD1-positive FALS cases is higher than reported elsewhere. The high proportion of I113T mutations is comparable to that previously observed in the adjacent province of British Columbia.

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)0.003
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.054
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.029
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.227
Teacher spread0.201 · 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

Citations12
Published2013
Admission routes2
Has abstractyes

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