MODELLING OF HYDROLYSIS OF MUNICIPAL PRIMARY SLUDGE IN ANAEROBIC DIGESTION
Bibliographic record
Abstract
下水処理施設の最初沈澱汚泥や生ごみをはじめとする有機固形物は，バクテリアを主体とする活性汚泥と比べて消化されやすく，メタン発酵によってエネルギー資源に転換しやすいと考えられている．このような有機固形物の分解挙動を数学モデルで整理すればプロセスの効率化検討に有用な情報になる．代表的な有機固形物である最初沈澱汚泥の加水分解を回分的呼吸速度試験装置で調べた結果，生物分解される成分は，（1）活性汚泥モデルの遅分解性成分（XS）と類似で速く消化する物質，（2）最初沈澱汚泥中の微生物（XH）と考えられる消化速度が遅い物質，（3）基質の生成に先立ち微細化反応が起きる物質，の三種類に分類することができた．これらの状態変数を組み合わせれば，さまざまな固形物の消化反応を定量的に考察することができると考えられる．
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 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".