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Record W2895977240 · doi:10.1016/j.jalz.2018.06.627

P1‐614: ALZHEIMER DISEASE RISK ASSESSMENT AND MANAGEMENT IN CANADA

2018· article· en· W2895977240 on OpenAlexaffabout
Ambreen Bano

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDementiaDiseaseMedicineAlzheimer's diseasePsychological interventionIntervention (counseling)GerontologyPsychiatryPathology

Abstract

fetched live from OpenAlex

Worldwide around 47 million people have dementia as reported by WHO and in Canada, there are 564,000 people living with dementia. By 2031, that number is expected to rise to 937,000, an increase of 66 percent as per Alzheimer's Society Canada. Alzheimer's disease (AD) is the most common type of dementia. Alzheimer's disease is an irreversible, progressive disorder that slowly deteriorates memory and thinking skills and, eventually, the ability to carry out the trivial tasks. Increasing number of AD patient has devastating impacts on their individual life, their family, caregiver and economic burden as a whole. In this report, the literature review was performed. Relevant studies were identified by searching electronic databases (Medline, Embase Pubmed) Alzheimer society Canada, Alzheimer association and bibliographies published on Alzheimer disease. Majority of studies suggested that the symptomatic treatment and common intervention towards the optimal control of risk factors which includes the maintenance of socially active lifestyle, mentally stimulating activities, and physical exercise. These interventions are expected to reduce the risk or postpone the clinical onset of dementia including AD. Role of vaccine and importance of an early diagnostic tool like retinal bio-marker is also considered. Symptomatic treatment and lifestyle modification are playing the crucial role in the management of Alzheimer disease. However, adequate research needs to be done to come up with a treatment like a vaccine which is not only cost-effective but also causes minimal side effects. Moreover, an early diagnostic tool like retinal bio-markers as it is non-invasive technique should be more focused and further research need to be done.

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)0.001
metaresearch head score (Gemma)0.009
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: Other · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0030.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.003

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 head0.023
GPT teacher head0.321
Teacher spread0.298 · 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
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

Citations0
Published2018
Admission routes2
Has abstractyes

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