Applying a Seasonal Adjustment Method to Continuous Dissolved Nitrous Oxide Data in a Carrousel Reactor
Bibliographic record
Abstract
本研究では, 生物反応槽の亜酸化窒素 (N2O) 連続データにおいて, 今まで短期的な変動が大きいために把握できなかった数日程度の中期的変動を抽出することを目的とした。2019年に下水処理場の無終端水路反応槽において取得した溶存態N2O濃度の約一カ月間の連続データを使用し, そのデータ特性を確認した上で, ノンパラメトリックな季節調整法であるSTL分解のアプローチを適用した。その結果, 溶存態N2O濃度の短期的な日内変動を排除しつつも時系列データとしての連続性を保持した中期的変動を観測することができた。また, この変動における特徴的なピークは, 直前の降雨の有無によって異なる流入量変動で説明することができた。したがって, 統計学的な亜酸化窒素生成モデルの構築を見すえた場合は, 降雨の影響を考慮する必要があることが示された。
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".