REDUCING DISPOSAL COSTS THROUGH ADVANCED ELECTRO-DEWATERING
Bibliographic record
Abstract
REDUCING DISPOSAL COSTS THROUGH ADVANCED ELECTRO-DEWATERINGThe City of Victoriaville (Quebec, Canada) has been using an innovative dewatering process using the principle of electro-osmosis since March 2005. The electro-dewatering machine is fed with dewatered sludge cake at an average16% TS concentration. Solids concentration at the outlet is in an average of 36% TS, with a volume reduction of 57%. Pathogen destruction has been documented. Effect of...Author(s)Scott F. McKayRoger ParadisMartin BlanchetteSourceProceedings of the Water Environment FederationSubjectSession 21: DewateringDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jan, 2007ISSN1938-6478SICI1938-6478(20070101)2007:3L.1167;1-DOI10.2175/193864707787975750Volume / Issue2007 / 3Content sourceResiduals and Biosolids ConferenceFirst / last page(s)1167 - 1179Copyright2007Word count122
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".