MétaCan
Menu
Back to cohort
Record W2788331500 · doi:10.3399/bjgp18x695249

Cognitive tests to help diagnose dementia in symptomatic people in primary care and the community

2018· review· en· W2788331500 on OpenAlex
Sam Creavin, Susanna Wisniewski, Anna H Noel-Storr, Sarah Cullum

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

VenueBritish Journal of General Practice · 2018
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersWellcome Trust
KeywordsDementiaPrimary careMedicineCognitionPrimary health careGerontologyPsychiatryFamily medicinePathologyDisease

Abstract

fetched live from OpenAlex

What brief cognitive test should a busy GP use when trying to assess someone who might have dementia? The menu of choices is long; one review found 11 options.<br/><br/>The Cochrane Dementia and Cognitive Improvement Group (CDCIG) is conducting a series of reviews to evaluate the evidence of a range of tests for diagnosing dementia. To date, reviews have been published addressing the accuracy of two tests in primary care: the Informant Questionnaire for Cognitive Disorders in the Elderly (IQCODE) and the Mini Mental State Examination [MMSE]. Reviewers found only one study that investigated the use of the IQCODE in primary care, and six that investigated the use of the MMSE.<br/><br/>A review of the Montreal Cognitive Assessment [MoCA] found no studies that evaluated the accuracy of the test in primary care. Reviews are underway for the Mini-Cog and AD-8 tests (see http://dta.cochrane.org/reviews-and-protocols-crg).

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.032
GPT teacher head0.382
Teacher spread0.349 · 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