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Record W3007245640 · doi:10.1016/j.nurpra.2019.12.016

Update on Treatments for Cognitive Decline in Alzheimer’s Disease

2020· article· en· W3007245640 on OpenAlexaboutno aff
Ann Kriebel-Gasparro

Bibliographic record

VenueThe Journal for Nurse Practitioners · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaDiseaseCognitive declineCognitionMedicineCognitive impairmentAlzheimer's diseaseMemory clinicPsychiatryPsychologyGerontologyPathology

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and a leading cause of dementia in the elderly. AD initially presents as mild cognitive impairment (MCI); later, as AD progresses, memory and cognition are destroyed, preventing the ability to carry out activities of daily living. The primary care provider may be the first to suspect MCI, and screening tests can help with diagnosis. Development of drugs for cognitive decline in AD has been slow; however new therapies are in the pipeline and discovery of biomarkers make early diagnosis and future treatment of AD hopeful.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.067
GPT teacher head0.412
Teacher spread0.345 · 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 designNot applicable
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

Citations3
Published2020
Admission routes1
Has abstractyes

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Same venueThe Journal for Nurse PractitionersSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207