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Record W1972349970 · doi:10.1016/j.jalz.2007.07.013

Mild cognitive impairment and cognitive impairment, no dementia: Part A, concept and diagnosis

2007· article· en· W1972349970 on OpenAlexafffundabout
Howard Chertkow, Ziad Nasreddine, Yves Joanette, Valérie Drolet, John Kirk, Fadi Massoud, Sylvie Belleville, Howard Bergman

Bibliographic record

VenueAlzheimer s & Dementia · 2007
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversité de MontréalUniversité de SherbrookeCentre Hospitalier de l’Université de MontréalHôpital Charles-Le MoyneMcGill UniversityInstitut Universitaire de Gériatrie de MontréalJewish General Hospital
FundersCanadian Institutes of Health ResearchLundbeck CanadaAlzheimer SocietyMcGill University
KeywordsDementiaCognitive impairmentMontreal Cognitive AssessmentCognitionPsychologyMedicineGerontologyPsychiatryDiseasePathology

Abstract

fetched live from OpenAlex

Mild cognitive impairment (MCI) and cognitive impairment, no dementia (CIND) are controversial emerging terms that encompass the clinical state between elderly normal cognition and dementia. This article reviews recent work on the classification of MCI and CIND, their prognosis, and diagnostic approaches and presents evidence-based recommendations approved at the meeting of the Third Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD3) held in Montreal in March, 2006. New short tools such as the Montreal Cognitive Assessment are making it easier for family physicians to confidently attach the label of MCI.

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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0020.009
Scholarly communication0.0040.005
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations112
Published2007
Admission routes3
Has abstractyes

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