RESEARCH ON THE SEASONAL REGULARITY OF UTILIZATION OF RURAL MUTUAL HEALTH CARE SERVICES
Bibliographic record
Abstract
[Objective]To explore the seasonal regularity of utilization of rural mutual health care services,so as to provide basis for further reforming and improve the rural health service system and rural medical care assurance.[Methods]Time sequential data seasonal index analysis was conducted to analyze data collected from medical establishment of trial towns with rural mutual health care(RMHC)from 2004 and 2006.[Results]The consultation rates form the first quarter to the forth quarter in trial towns with RMHC were 131.57%,109.67%,84.08% and 74.67%,respectively,while the hospitalization rates were 105.85%,94.6%,84.09% and 123.62%,respectively.Meanwhile,the seasonal indexes had significantly difference in different months and different trial towns.[Conclusion]More emphasis from the primary medical establishment should be paid to the seasonal fluctuation of utilization of RMHC.And the allocation of health resources should be adjusted to ensure the high effective utilization of health resources.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".