Start-Up, Operation and Performance of an Optimized Real time Control System for Wet Weather Pollution Control
Bibliographic record
Abstract
Start-Up, Operation and Performance of an Optimized Real time Control System for Wet Weather Pollution ControlDoes the Real Time Control System really achieve better performance in terms of controlling overflows in combined sewer systems? Is it more efficient than the decisions of a human operator? Is it sufficiently robust? These are some of the questions that will be covered in this paper on the implementation and the performance of the RTC system installed for the Quebec Urban Community (QUC).Author(s)Pierre LavalléeRichard BoninBruno RoyGenevieve PelletierMartin PleauSourceProceedings of the Water Environment FederationSubjectSession 2 - CS OperationsDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jan, 2000ISSN1938-6478SICI1938-6478(20000101)2000:4L.36;1-DOI10.2175/193864700785140944Volume / Issue2000 / 4Content sourceCollection Systems ConferenceFirst / last page(s)36 - 49Copyright2000Word count80
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".