MétaCan
Menu
Back to cohort
Record W2150569660 · doi:10.1017/s0714980813000299

Perspective écologique sur les déterminants de la vitalité cognitive des aînés

2013· review· fr· W2150569660 on OpenAlexaff
Anne-Marie Belley, Manon Parisien, Kareen Nour, Nathalie Bier, Guylaine Ferland, Danielle Guay, П. Л. Попов, Sophie Laforest

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2013
Typereview
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité de MontréalSanté MontérégieCentre de Santé et de Services Sociaux Cavendish
Fundersnot available
KeywordsHumanitiesPsychologyPerspective (graphical)PhilosophyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Cognitive aging is a heterogeneous reality among the senior population. Studies have recently identified certain factors that may contribute to maintaining the cognitive health of seniors. To date, these research studies have primarily focused on individual determinants, namely: health conditions and lifestyle habits. A review of the literature was conducted in order to explore the socio-environmental factors that may influence the cognitive vitality of seniors. This review demonstrates that studies that have examined this potential link are very rare. Only the type and socioeconomic level of the neighbourhood of the residence, as well as the size of the social network, were identified as influential factors. However, studies have shown that the environment could modulate certain lifestyle habits which, in turn, can influence cognition. This article uses an ecological approach to illustrate individual and socio-environmental targets for the promotion of the cognitive health of seniors.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.046
GPT teacher head0.350
Teacher spread0.304 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicAging, Elder Care, and Social IssuesFrench-language works237,207