Combined Modeling of a Flume-Gravel-Trench System and Surrounding Unsaturated Soils
Bibliographic record
Abstract
Ongoing and intensive land development over several decades has led to increasing imperviousness of urban areas.This is particularly true for town and city centres.Precipitation cannot infiltrate into the ground and this reduces groundwater renewaL Instead, stonnwater is conveyed by separate and combined sewer systems to the next treatment plant or receiving water.Frequently, problems occur when further development is planned in suburban areas to be connected to the main sewer system.According to traditional technology, existing parts of the sewer system become overloaded and must be replaced by larger diameter sewers to convey additional sewerage and storm water.In some cases some existing treatment plants become overloaded and must be rebuilt or modified to fulfil existing water quality standards.Investment costs for these modifications and extensions of the drainage system are distributed among the users connected to the system.Internationally a broad consensus exists that the re-routing of stonnwater back into the natural water cycle is compulsory from the ecological and economical point of view.It is well known that onsite infiltration of stonnwater can contribute to considerably reducing stonnwater peaks and volumes.Several infiltration technologies have been developed for this purpose, such as drainage wells, gravel trenches and pervious pipes that include subsurface storage, as well as depression and reservoir infiltration including surface storage.The BIRCO Company in Baden-Baden has developed a new drainage Schaffner, J. and M.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".