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Record W3001608709 · doi:10.1016/j.prdoa.2020.100034

Characterization of cognition in mild cognitive impairment with and without Parkinson's disease

2020· article· en· W3001608709 on OpenAlexafffund
Noémie Auclair‐Ouellet, Sophie Mandl, Mekale Kibreab, Angela Haffenden, Alexandru Hanganu, Jenelle Cheetham, Iris Kathol, Justyna R. Sarna, Davide Martino, Oury Monchi

Bibliographic record

VenueClinical Parkinsonism & Related Disorders · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité de MontréalMcGill UniversityUniversity of CalgaryInstitut Universitaire de Gériatrie de MontréalHotchkiss Brain InstituteCentre for Research on Brain Language and Music
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsNeuropsychologyCognitive impairmentCognitionParkinson's diseasePsychologyMedicineAudiologyDiseasePhysical medicine and rehabilitationPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

•Screening tests can diagnose PD-MCI but do not give detailed cognitive profiles.•Criteria based on a complete neuropsychological battery identify more PD patients with MCI.•The overall cognitive profile is similar in PD-MCI and MCI.•Neuropsychological batteries and definition of impairment cut-offs should be refined.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.299
Teacher spread0.275 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes2
Has abstractyes

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