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Optimizing Modifiable and Lifestyle-related Factors in the Prevention of Dementia Disorders with Special Reference to Alzheimer, Parkinson and Autism Diseases

2019· article· en· W2966195768 on OpenAlexaff
U Gupta, Gupta Sc

Bibliographic record

VenueCurrent Nutrition & Food Science · 2019
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsDementiaAutismDiseaseMedicinePsychiatryParkinson's diseaseDepression (economics)PsychologyPathology

Abstract

fetched live from OpenAlex

Dementia is a syndrome and an umbrella term that encompasses Alzheimer, Parkinson and autism diseases. These diseases are by far the most common cause of dementia; therefore this investigation will chiefly include these disorders, with a limited discussion of few other disorders related to dementia. Alzheimer’s disease (AD) is characterized by the accumulation of cerebral β-amyloid plaques, tau proteins and memory loss; Parkinson by the deterioration of brain cells which regulate the movement of body parts and produce dopamine; and autism by abnormalities of social disorder and difficulty in communicating and forming relationships. Alzheimer’s disease and cognitive impairment in dementia are age-related and manageable only with early diagnosis and prevention. Data based on several decades of research has shown that the major factors responsible for the induction of inflammation in dementia and many chronic diseases are infections, obesity, alcohol, radiation, environmental pollutants, improper nutrition, lack of physical activity, depression, anxiety, genetic factors, and sleep deprivation. There are some studied preventive measures for dementia including continued physical activity and consuming predominantly a plant-based Mediterranean diet comprising olive oil and foods containing flavonoids and other phytochemicals having strong antioxidant and anti-inflammatory properties and along with management of chronic conditions.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.288
Teacher spread0.248 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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