Perfil demográfico da população idosa de Montes Claros, Minas Gerais e Brasil
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".