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Record W2530975681

A Population-Based Study Of Depression In Persons With Parkinson's Disease

2013· article· en· W2530975681 on OpenAlexaffvenue
Thomas Johannes Ernert

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2013
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDepression (economics)MedicineParkinson's diseaseDiseaseSuicidal ideationPopulationDemographicsQuality of life (healthcare)PsychiatryPhysical therapyInternal medicinePoison controlInjury preventionDemographyEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Parkinson’s disease (PD) is a chronic neurological condition that degenerates motor skills and degrades cognitive function over time. Depression is commonly associated with PD, and can lead to decreased quality of life and increased health care utilization in persons with PD. The goal of the current project is to estimate the prevalence of depression in PD disease patients and characterize this population in terms of demographics, differing diagnostic criteria and comorbidities. It was found that the prevalence of depression, using both the cutpoint and algorithm scoring methods are higher in PD than in the general population. In addition, a significantly greater proportion of persons with PD report suicidal ideation than the general population. Most persons with PD report poor self-rated health and almost 1 in 5 report their current health state to be worse than dead. Two-thirds of persons report their PD symptoms to be worse or much worse than when they were first diagnosed.

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)0.002
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 score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.042
GPT teacher head0.346
Teacher spread0.304 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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Same venueJournal of undergraduate research in AlbertaSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207