INTERVAL FINITE VOLUME METHOD FOR UNCERTAINTY SIMULATION OF TWO-DIMENSIONAL RIVER WATER QUALITY
Bibliographic record
Abstract
Under the interval uncertainties, by incorporating the discretization form of finite volume method and interval algebra theory, an Interval Finite Volume Method (IFVM) was developed to solve water quality simulation issues for two-dimensional river when lacking effective data of flow velocity and flow quantity. The IFVM was practically applied to a segment of the Xiangjiang River because the Project of Hunan Inland Waterway Multipurpose must be started working after the environmental impact assessment for it. The simulation results suggest that there exist rather apparent pollution zones of BOD 5 downstream the Dongqiaogang discharger and that of COD downstream Xiaoxiangjie discharger, but the pollution sources have no impact on the safety of the three water plants located in this river segment. Although the developed IFVM is to be perfected, it is still a powerful tool under interval uncertainties for water environmental impact assessment, risk analysis, and water quality planning, etc. besides water quality simulation studied in this paper.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".