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Mild Cognitive Impairment

2015· other· en· W2803094532 on OpenAlexaff
Nicole D. Anderson

Bibliographic record

VenueThe Encyclopedia of Adulthood and Aging · 2015
Typeother
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementiaCognitionCognitive impairmentGerontologyMedicineDepression (economics)Cognitive declinePopulationClinical psychologyPsychiatryPsychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Mild cognitive impairment (MCI) refers to the transitional stage between normal aging and dementia. Interest in identifying people with MCI is mounting, in efforts to thwart dementia onset. Diagnosis of MCI involvesa combined medical and cognitive assessment, in order to rule out treatable conditions contributing to cognitive impairment, identify symptoms consistent with preclinical dementia, and confirm the presence of mild cognitive difficulties. Prevalence rates of MCI vary from 3% to 42% of the population over the age of 65 worldwide. The risk factors for MCI (e.g., higher age, lower education, the E4 allele of the apolipoprotein gene, conditions such as hypertension and diabetes, and depression) overlap with those for dementia. While there are no approved pharmacological treatments for MCI, a growing body of evidence is identifying lifestyle factors that can reduce either the risk of MCI or its progression to dementia, including exercise and cognitive interventions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.298
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations43
Published2015
Admission routes1
Has abstractyes

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