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Record W7027811338

De Nederlandse versies van de Montreal Cognitive Assessment (MoCA)

2023· article· nl· W7027811338 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRadboud Repository (Radboud University) · 2023
Typearticle
Languagenl
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentVenQualitative analysis
DOInot available

Abstract

fetched live from OpenAlex

In veel settings waar een neuropsychologisch onderzoek niet haalbaar is, worden screeningsinstrumenten gebruikt om cognitieve stoornissen te kunnen vaststellen. De Montreal Cognitive Assessment (MoCA) is een van de meest gebruikte cognitieve screeners, die ook in Nederland populair is. De sensitiviteit en specificiteit van de oorspronkelijke afkapwaarde van ≤ 26 is echter onvoldoende gebleken, en een goede correctie voor leeftijd en opleiding ontbreekt. In dit artikel wordt ingegaan op de Nederlandstalige versies van de MoCA, inclusief de meest recente parallelle versies, en worden recent gepubliceerde normscores toegelicht. Hierbij wordt ook ingegaan op de Geheugenindexscore en op het gebruik van de Reliable Change Index bij herhaalde metingen. De MoCA-totaalscore en de Geheugenindexscore kunnen gebruikt worden om uitspraken te doen over het cognitief functioneren van een patiënt, maar in veel gevallen zal een uitgebreid neuropsychologisch onderzoek toch noodzakelijk zijn.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.275
Teacher spread0.263 · 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