Utilization of Fermented Dry Food Waste Feed by Fattening Swine
Bibliographic record
Abstract
食品残渣から調製した乾燥飼料を100%肥育豚に給与する試験を実施した。乾燥飼料は米飯類, パン屑・麺類, ライ麦糠, トウフ粕, 野菜屑, 魚腸骨等を原料に低エネルギー・高蛋白飼料 (飼料1), 中エネルギー・高蛋白質・高脂肪飼料 (飼料2), 高エネルギー・低蛋白質・低脂肪飼料 (飼料3) の3種を調製した。試験はLWD交雑種去勢雄5頭, 雌7頭を使用して平均体重約50kgから約105kg到達時まで不断給餌により実施した。試験区の設定はA区 (前期に飼料1, 中期に飼料1および3, 後期に飼料3), B区 (前期に飼料2, 中期に飼料2および3, 後期に飼料3), C区対照区 (配合飼料給与区) の3区とし, 発育・増体, 肉質等について検討を行った。その結果, 両試験区は前期に採食量が少なく, DGも低い値であったが, 中期では対照区と同等の発育を示した。肉質検査の結果, 水分, pH, 脂肪色, ドリップロス等に差は認められなかったが, 筋肉内脂肪は対照のC区に比べ, A区が有意に多く, B区も多い傾向を示した。また, 試験区は対照区に比べ背脂肪融点がやや高く, 特にA区の背脂肪内層で顕著であった。食味に関する官能検査ではB区の赤肉が対照区に比べ好まれる傾向を示すが, 有意差はみられなかった。以上のことから, 発育は若干遅延するものの, 食品残渣のみで調製した飼料においても, 配合飼料と同等の肉質を持つ肉豚の生産が可能なことが示された。
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".