Pengaruh pemberian dimsum boster (brokoli, sapi, dan teri) terhadap status gizi kurang pada balita stunting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Latar Belakang: Salah satu target SDGs (Sustainable Development Goals) adalah sistem kesehatan nasional pada tahun 2030, seluruh negara berupaya untuk menurunkan angka kematian balita sebesar 25/1.000 kelahiran hidup. Selain itu pada target gizi masyarakat tahun 2030, seluruh negara berupaya untuk mengakhiri segala bentuk malnutrisi, termasuk mencapai target Internasional 2025 yang bertujuan untuk menurunkan stunting dan wasting pada balita dan mengatasi kebutuhan gizi remaja perempuan, wanita hamil dan menyusui, serta lansia.Metode: Jenis penelitian yang digunakan adalah Quasi Eksperimen, menggunakan rancangan one group pretest and post-test. dan pengumpulan data menggunakan pengukuran dengan prosedur Antropometri. Jumlah sampel pada penelitian ini adalah balita stunting dengan status gizi kurang sebanyak 24 orang. Uji statistik yang digunakan adalah Uji Unpaired sampel t-test.Hasil: Analisis bivariat menunjukkan bahwa terdapat pengaruh status gizi kurang pada balita stunting sebelum dan sesudah pemberian dimsum boster (p-value 0,000 < 0,005).Kesimpulan: Adanya pengaruh pemberian dimsum boster (brokoli, daging sapi, dan ikan teri) terhadap status gizi kurang pada balita stunting di Wilayah Puskesmas Kawalu Kota Tasikmalaya.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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