Analysis of the Characteristics of Diarrhea Patients at Bojong 1 Health Center in the First Quarter of 2024
Bibliographic record
Abstract
Diarrhea is a disease of changes in the shape and consistency of stool, as well as an increase in the frequency of bowel movements from 1 time a day to 3 or more times a day. According to the Central Java Province Diarrhea Program Data (2021) Diarrhea cases in Central Java Province in 2021 in the category of all ages served in health facilities were 279,484 cases. In the under-five category, there were 83,665 or 23.4% of the estimated under-five diarrhea in health facilities. Pekalongan Regency is in the top 10 of the highest number of cases in 2021 as much as 40%. The purpose of this study was to determine the characteristics of diarrhea patients in the first quarter of 2024 at the Bojong 1 Health Center including gender, occupation, age, and BMI. This study used a descriptive research design with secondary data and analysis of the spss version 21 application using a total sampling of 201 diarrhea patients at the Bojong 1 Health Center. The results of the study found that women were more infected with diarrhea 123 people (61.2%) than men 78 people (38%), the most patient jobs were found to be unemployed 132 people (65. 7%), while the least as a trader was 6 people (3.0%), the most infected age was the infant and toddler group <5 years as many as 99 children (49.3%) and the least elderly age >60 years as many as 7 people (3.5%), the most BMI category in severe thin <17.0 as many as 101 people (50.2%), the least category of mild fat 25.1-27.1 as many as 6 people (3.0%). In conclusion, women were more infected with diarrhea than men, with a status of not working. The age range that is mostly infected in the toddler category, the majority of IMT patients with diarrhea are in the severe thin category.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".