Use of Bio-electrochemical Sensors to Inform Enhanced Biological Phosphorus Removal Operation Under RAS Fermentation and A2O Conditions
Bibliographic record
Abstract
Use of Bio-electrochemical Sensors to Inform Enhanced Biological Phosphorus Removal Operation Under RAS Fermentation and A2O ConditionsAbstractThis paper was presented at WEFTEC 2023 in Chicago, IL.This paper summarizes the performance bio-electrochemical sensors deployed at the Clean Water Services Durham WRRF with the following goals to support EBPR operation: 1. Guide RAS-fermentation operation to determine the optimal setpoints to create stable EBPR. 2. Compare anaerobic zone performance during A2O operation between two aeration basins where one basin has an anaerobic zone that is twice as large as the other. 3. Inform plant operations of process influent carbon loadings.SpeakerMenniti, AdriennePresentation time13:30:0014:00:00Session time13:30:0015:00:00SessionConnecting Molecular Biology Sensors to EBPR PerformanceSession locationRoom S502 - Level 5TopicAdvanced Level, Facility Operations and Maintenance, Municipal Wastewater Treatment Design, NutrientsTopicAdvanced Level, Facility Operations and Maintenance, Municipal Wastewater Treatment Design, NutrientsAuthor(s)Menniti, AdrienneAuthor(s)A. Menniti 1; J. Ambler 2 ; J. Mejia Franco 3; R. Cusick 4; A. Menniti 1;Author affiliation(s)Chemical Engineering, Université Laval, 1065 Avenue de la Médecine, Québec, QC, Canada 1; SENTRY Water Technologies 2 ; SENTRY Water Technologies 3; University of Illinois at Urbana-Champaign 4; Clean Water Services 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159084Volume / Issue Content sourceWEFTECCopyright2023Word count18
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".