HUBUNGAN ANTARA STATUS GIZI DAN TINGKAT ASUPAN ZAT GIZI DENGAN SIKLUS MENSTRUASI PADA REMAJA PUTRI DI KECAMATAN KEDUNGBANTENG KABUPATEN BANYUMAS
Bibliographic record
Abstract
Background: Menstrual disorders often occur among adolescent girls. Menstrual disorder due to several factor including nutritional status, age, physical activity, nutrients intake, disease, stress and influence of cigarettes . Objective: To examined the association between nutritional status and level of nutrients intake with menstrual cycle among aldolescent in Distric Kedungbanteng Banyumas. Methods: Design research is analytic observation with cross sectional approach. Sampling technique used purposive sampling and obtained 69 respondent adolescent girls. The technique of data colelection used menstrual cycle questionnaire, antropometric, food recall 2x24 jam, food picture and food model. Result: There is 40.6% respondent have an abnormal menstrual cycle. Nutritional status (11.6%) classified abnormal. Energy intake (91.3%), carbohydrate (94.2%) protein intake (89.9%) and fat intake (85.5%) classified an abnormal. Based on analysis of Chi-Square test, there is a significant relation between fat intake with menstrual cycle (p=0.041). Conclusion: Fat intake associated with menstrual cycle..
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".