HUBUNGAN KOMPRES BAWANG MERAH (ALLIN ESENSIAL OIL) DENGAN PENURUNAN DEMAM PADA BALITA DI KAMPUNG HASIK JAYA SORONG SELATAN
Bibliographic record
Abstract
Shallots can be used to compress, this is because onions contain organic sulfur compounds, namely allycysteine ??sulfoxide (aliin) which functions to destroy blood clots. Other ingredients of shallots that can lower body temperature are phlorogusin, cycloaliin, methylaliin, and kaemferol. The purpose of this study was the effect of compressing shallots (allin essential oil) on reducing fever in children under five in Hasik Jaya Village, Moswaren District, South Sorong Regency. This type of research is a quasi-experimental research with pre-test and post-test with control group design. The number of samples is 31 respondents. The results showed most of the age of toddlers with fever in Hasik Jaya Village, Moswaren District, South Sorong Regency were 13-24 months as many as 20 toddlers (64,5%), female as many as 18 toddlers (58,1%). Some of the toddlers' temperature before being given red onion compresses (allin essential oil) was 37,80C for 10 toddlers (32,3%). Some of the toddlers' temperature after being given an onion compress (allin essential oil) was 37,50C for 12 toddlers (38,7%). There is a relationship between shallot compresses (allin essential oil) and fever reduction in children under five in Hasik Jaya Village, Moswaren District, South Sorong Regency with p value of 0,000.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.012 | 0.001 |
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".