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Record W2760902440 · doi:10.1159/000480496

Montreal Cognitive Assessment in a 63- to 65-year-old Norwegian Cohort from the General Population: Data from the Akershus Cardiac Examination 1950 Study

2017· article· en· W2760902440 on OpenAlex
Håkon Ihle‐Hansen, Thea Vigen, Trygve Berge, Gunnar Einvik, Dag Aarsland, Ole Morten Rønning, Bente Thommessen, Helge Røsjø, Arnljot Tveit, Hege Ihle‐Hansen

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

VenueDementia and Geriatric Cognitive Disorders Extra · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCohortMedicineConfidence intervalPopulationNorwegianInternal medicineCohort studyCognitionGerontologyDemographyPsychologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

AIMS: To investigate Montreal Cognitive Assessment (MoCA) test scores in a cohort aged 63-65 years from a general population in relation to the proposed cut-off score of 26 for mild cognitive impairment (MCI) and to explore the impact of education. METHODS: MoCA scores were assessed in the Akershus Cardiac Examination 1950 Study, a cross-sectional cohort study of all men and women born in 1950 living in Akershus County, Norway. The participants were aged 63-65 at the time of data collection. RESULTS: MoCA scores were available in 3,413 participants, of which 47% had higher education (>12 years). The mean MoCA score was 25.3 (95% confidence interval [CI] 25.2-25.4), and 49% had a score below the suggested cut-off of 26 points. Those with higher education had significantly higher scores (mean 26.2, 95% CI 26.1-26.3 vs. 24.4, 95% CI 24.3-24.6, p < 0.001). CONCLUSIONS: Approximately 50% scored below the cut-off score of 26 points, suggesting that the cut-off score may have been set too high to distinguish normal cognitive function from MCI. Educational level had a significant impact on MoCA scores.

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)0.001
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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.338
Teacher spread0.314 · 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