Faktor-Faktor yang Berhubungan dengan Kejadian Demam Berdarah Dengue (DBD) di Puskesmas Selatpanjang Kabupaten Kepulauan Meranti
Bibliographic record
Abstract
Incidence og dengue in the region of the district health center island Selatpanjang Meranti as 129 cases. Of 2 and 6 rural villages, urban villages, especially the city Selatpanjang RW 09 and RW 10 and RW particular village east Selatpanjang 01 and RW 02 includes areas with the highest cases of health centers in the region of Selatpanjang. The purpose of the study to determine the factors associated with the incidence of dengue in Selatpanjang Meranti Islands. Quantitative research conducted with cross-sectional research design. The sample in the study of 167 respondents. The sampling technique using simple random sampling. Data collection using questionnaires and direct observation. Test statistics with chi square test at 95% confidence level. The results showed no relationship between respondents knowledge of dengue, the presence of aedes aegypti larvae in containers, the shelter is closed on the availability of water and frequency of draining water reservoirs daily use with the incidence of dengue in the district health center island Meranti Selatpanjang 2012. While the habit of hanging clothes no association with the incidence of dengue in the district health center island Selatpanjang Meranti of 2012. It is expected that further intensify the health center larva periodic inspection activities, as well as for the community to pay more attention to the activities and the implementation of PSN plus 3M-DBD independently and regularly
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".