Bibliographic record
Abstract
Susu adalah sumber gizi utama bagi bayi (hingga 2-3 tahun) sebelum mereka dapat mencerna makanan padat. Susu binatang (biasanya sapi) juga diolah menjadi berbagai produk seperti mentega, yogurt, es krim, keju, susu kental manis, susu bubuk dan lain-lainnya untuk konsumsi manusia. Namun ternyata susu sapi dipaksakan agar bisa dikonsumsi oleh manusia, pengkonsumsian susu sapi berlebih dapat memberi efek samping pada manusia yaitu munculnya berbagai penyakit akibat kelebihan nutrisi. Fakta ini didapat dari hasil konvensi dunia (World Breastfeeding Week, 1-7 Agustus 2006), Elisabeth Sterken, BSc.MSc Nutritionist INFACT Canada/North America. Kemajuan teknologi saat ini telah menemukan berbagai sarana lain pengganti susu sapi yaitu susu yang diolah dari tumbuh-tumbuhan yang memiliki manfaat yang sama dengan susu namun baik dikonsumsi manusia. Maka dari itu munculah gagasan untuk membuat suatu wadah pengetahuan sekaligus area rekreasi keluarga yang dapat dinikmati masyarakat mengenai fakta produk susu sapi yang mereka konsumsi sehari-hari, khususnya untuk anak-anak agar dapat memperbaiki nutrisi dan dapat mengubah pola pikir sejak dini.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.208 | 0.043 |
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".