Spatial Patterns of Pulmonary Tuberculosis Analysing Rainfall Patterns in Visual Formation
Why this work is in the frame
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Bibliographic record
Abstract
Management sustainability related tuberculosis patient treatment was limited. Tuberculosis analysis was still in the form of data aggregation. This is cross sectional survey using geographical information system, analyzed by descriptive methods, the sample included 162 pulmonary tuberrculosis patient in 2014. The variables were pulmonary tuberrculosis patients and isohyet data. Mycrobacterium tuberculosis will be survive and multiply during rainy season. Rainfall data was an increasing pattern from first quarter to fourth quarter in 2014, however data in 2011, 2012 and 2013, which each quarter was largely experiencing sustained increase and decline. Pulmonary tuberrculosis patients were most prevalent in 2014. It was increase in the rainy season. The most high rainfall intensity (> 2400 mm) in east of Lendah and western of Kokap areas, while the lowest intensity (< 1500 mm) in east of Nanggulan, in the south of Panjatan and Galur areas. It was mostly located in areas with high rainfall intensity (2200 - 2400 mm) which spreads and stretches in Sentolo, Wates, and Panjatan areas. Pulmonary tuberrculosis occurred over the rainy season. Spatial pattern distribution of pulmonary tuberrculosis patients in high rainfall intensity spreads and stretches from east to west areas. Active case monitoring program should be performed by tuberculosis program that concerned in areas of high rainfall intensity.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| 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 it