Perbandingan Jumlah Camilan Yang Dikonsumsi Oleh Orang Obese dan Non Obese
Bibliographic record
Abstract
Latar belakang Kelebihan berat badan (overweight) sampai kegemukan (obese) telah menjadi isu hangat dalam 1-2 dekade terakhir ini di negara – negara berkembang. Salah satu kebiasaan yang menyebabkan obesitas adalah kebiasaan suka makan camilan. Keadaan obesitas ini juga berkaitan dengan meningkatnya insidensi berbagai penyakit, termasuk penyakit kardiovaskular, varises vena, kerusakan sendi dan kandung empedu serta diabetes. Tujuan Untuk mengetahui apakah jumlah camilan yang dimakan orang obese lebih banyak dari non obese. Metode Desain penelitian yang digunakan adalah penelitian eksperimental sungguhan, di mana 20 orang laki-laki obese dan 20 orang laki-laki non obese disuruh makan kenyang kemudian diberi camilan yang disukai sambil dibiarkan menonton film selama 30 menit. Sebelum dan sesudah menonton film jumlah kalori camilan dihitung. Hasil Rata-rata jumlah kalori camilan yang dimakan pada orang obese adalah 311 kkal(SD = 84.713) dan rata-rata jumlah kalori camilan yang dimakan pada orang non obese adalah 136 kkal(SD =49.058) (p = 0.000)**. Kesimpulan Orang obese makan jumlah camilan lebih banyak dari orang non-obese
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".