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Record W1893927200 · doi:10.19175/recom.v0i0.151

Perfil demográfico da população idosa de Montes Claros, Minas Gerais e Brasil

2011· article· pt· W1893927200 on OpenAlexaboutno aff
Diego Dias de Araújo, Raquel Souza Azevedo, Tânia Couto Machado Chianca

Bibliographic record

VenueRevista de Enfermagem do Centro-Oeste Mineiro · 2011
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyDemographicsPopulationDemographySociology

Abstract

fetched live from OpenAlex

This is a descriptive study on the profile of elderly in Montes Claros, Minas Gerais, Brazil, conducted a source of secondary data, with information obtained from the Brazilian Institute of Geography and Statistics, whose objective was to know the aging population from demographics of the population. In relation to Brazil in 2000, 10.54% represents the total population of Minas Gerais and 0.18% of the Hills course. In 2010 the population represented 10.3% and 0.2%. In 2000 the elderly population, accounted for 11.18% in Ontario and 0.14% in Montes Claros. In 2010 this was 11.22% and 0.16% respectively. It is noted that in all demographers studied there is a conformity with the aging process. Descriptors: Demographic transition; Aging population; Elderly.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.309

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.390
Teacher spread0.267 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2011
Admission routes1
Has abstractyes

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