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Record W2090026968 · doi:10.5604/12321966.1129943

Biological psychological and social determinants of old age: Bio-psycho-social aspects of human aging

2014· review· en· W2090026968 on OpenAlexaff
Małgorzata Dziechciaż, Rafał Filip

Bibliographic record

VenueAnnals of Agricultural and Environmental Medicine · 2014
Typereview
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsMoodPsychologyAgeingCognitionProcess (computing)PerceptionDevelopmental psychologySocial psychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

The aging of humans is a physiological and dynamic process ongoing with time. In accordance with most gerontologists' assertions it starts in the fourth decade of life and leads to death. The process of human aging is complex and individualized, occurs in the biological, psychological and social sphere. Biological aging is characterized by progressive age-changes in metabolism and physicochemical properties of cells, leading to impaired self-regulation, regeneration, and to structural changes and functional tissues and organs. It is a natural and irreversible process which can run as successful aging, typical or pathological. Biological changes that occur with age in the human body affect mood, attitude to the environment, physical condition and social activity, and designate the place of seniors in the family and society. Psychical ageing refers to human awareness and his adaptability to the ageing process. Among adaptation attitudes we can differentiate: constructive, dependence, hostile towards others and towards self attitudes. With progressed age, difficulties with adjustment to the new situation are increasing, adverse changes in the cognitive and intellectual sphere take place, perception process involutes, perceived sensations and information received is lowered, and thinking processes change. Social ageing is limited to the role of an old person is culturally conditioned and may change as customs change. Social ageing refers to how a human being perceives the ageing process and how society sees it.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.141
GPT teacher head0.432
Teacher spread0.291 · 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

Citations322
Published2014
Admission routes1
Has abstractyes

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