Hubungan Karakteristik Demografi Terhadap Pengetahuan SIBAT Di Bantaran Sungai Bengawan Solo
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACTBackground: Climate change in Indonesia is strongly influenced by 3 basic climate patterns: monsoon, equatorial and local climate systems which cause dramatic differences in rainfall patterns, tending to give rise to a high potential for various types of hydrometeorological disasters, such as floods, flash floods, droughts, weather extreme, extreme waves. The community-based early warning system for flood disaster preparedness (SIBAT) is one of the means for preventing flood disasters.The aim of this research is to describeThe relationship between the characteristics of sibat cadres and knowledge about community-based early warning system strategies for flood disaster preparedness (sibat) on the banks of the Bengawan Solo River, Blora Regency. Research methods This is a quantitative approachcross sectional  with a total sample of 110 SIBAT cadres selected using the Slovin method. Data was collected using a questionnaire sheet, then analyzed usingChi Square. The research results show that from3 The independent variable is significantly related to the dependent variable, the age variable with pvalue 0.013, gender variable with pvalue 0.071, education level variable with pvalue 0.013. which means that each variable has a strong relationship with the dependent variable, namely with knowledge about the Community-based Disaster Information System on the banks of the Bengawan Solo River.Keywords: SIBAT cadres, disaster preparedness, floods
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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