PEMBERDAYAAN MASYARAKAT MELALUI KEMANDIRIAN PENGUKURAN TEKANAN DARAH UNTUK MENGENDALIKAN HIPERTENSI DI DESA CIPARAY RW 07 KABUPATEN BANDUNG
Bibliographic record
Abstract
Health problems of Non-Communicable Diseases (NCDs), especially hypertension, which is a condition of abnormal blood pressure increase that occurs in the arteries. Referring to the results of Basic Health Research in 2018, Indonesian people who have an age of more than 18 years have a percentage of 34.1% and a percentage of 8.8% were diagnosed with hypertension. Hypertensive disease is a disease that must be handled appropriately and appropriately, the higher the blood pressure of the patient, the higher the risk of being received by the patient. This community service aims to implement preventive and promotive health efforts related to hypertension with mechanisms to increase public knowledge to prevent and control hypertension. This method of community service begins with the Training and Formation of Special Cadres of PTM Posbindu, distribution of Pre-test, counseling, and activities of PTM Posbindu, ending with the distribution of Post-test. With a target of cadres and 33 residents with hypertension. The whole series of community service activities have been carried out. Counseling, training, and the formation of special cadres of PTM Posbindu were successfully implemented, formed, and activated. After community service, there are differences in increasing residents' knowledge about hypertension. At the time of pre-test measurement, 24% of citizens were well informed, increasing when post-test measurements were carried out with results of 70% of citizens with good knowledge. Community service activities are carried out according to the plan agreed upon at MMRW. This community service has succeeded in increasing residents' knowledge about hypertension.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.014 |
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".