Use of primary health care services according to the di¡erent degrees of obesity in the Girona Health Region, Spain
Bibliographic record
Abstract
Our main hypothesis in this paper was that, once controlled for age and gender, the use of primary health care services of people in each of the groups defined by their degree of obesity (i.e. normal weight, overweight and obese) did not correspond to the need for care implied by the level of risk of the group he/she belonged to. This fact could reflect some inequity in the utilisation of such services. Using a survey of the general population from the Girona Health Region, Spain, carried out during the fourth quarter of 2002, we have found that: first, the probability of primary health care use decreased with income for GPs (until 1200h) and increased for specialists (from 1500h). Second, we could conclude by confirming our hypothesis, i.e. there was more probability of obese individuals using general practice care, public in particular, and less probability of them using specialists, private in particular, than the rest of individuals. Third, we conclude that the use of multilevel (also hierarchical or mixed) models could
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".