HUBUNGAN PENGETAHUAN DENGAN SIKAP IBU DALAM PEMBERIAN ASI EKSKLUSIF DI WILAYAH KERJA PUSKESMAS NARAS
Bibliographic record
Abstract
The World Health Organization reported that the incidence of nausea and vomiting in women reached 12.5% in the world with 0.3% in Sweden, 0.5% in California, 0.8% in Canada, 10.8% in China, 0.9% in Norway, 2.2% in Pakistan, 1.9% in Turkey, and in Indonesia reaching 50%-80%. Peppermint aromatherapy containing menthol (35-45%) and menthone (10%-30%) is useful as an antiemetic and antispasmodic on the lining of the stomach and intestines by inhibiting muscle contractions. The ability of peppermint leaves to reduce nausea and vomiting in pregnancy is thought to be related to the content of essential oils such as α-, β-pinenelimonene 1,8- cineole. This study aims to determine the effect of peppermint aromatherapy on reducing nausea and vomiting in pregnant women in the first trimester at the Pauh Kambar Health Center. This research method uses a quasi-experimental design with a one group pretest-posttest design. The population of this study was 70 pregnant women in the first trimester. The number of samples taken was 15 people using purposive sampling technique. Data processing was done using Univariate and Bivariate using t-dependent analysis. The results of the study with the T test showed that there was an effect of peppermint aromatherapy on reducing nausea and vomiting in pregnant women in the first trimester at the Pauh Kambar Health Center (p-value = 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".