MétaCan
Menu
Back to cohort
Record W2312662113 · doi:10.2166/wst.2011.462

Wastewater as a resource: a unique approach to achieving energy sustainability

2011· article· en· W2312662113 on OpenAlexaff
Paul M. Sutton, Bruce E. Rittmann, Oliver Schraa, James E. Banaszak, A. Paul Togna

Bibliographic record

VenueWater Science & Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsHydromantis Environmental Software Solutions (Canada)
Fundersnot available
KeywordsWastewaterAnaerobic digestionWaste managementEnvironmental scienceResource recoverySewage treatmentReuseEnergy recoverySlurryBioreactorOrganic matterEnvironmental engineeringMethaneChemistryEngineeringEnergy (signal processing)

Abstract

fetched live from OpenAlex

A wastewater-treatment flowsheet was developed to integrate uniquely designed biological processes with physical-chemical unit processes, allowing conversion of the organic carbon in the wastewater to methane, the removal and recovery of phosphorus and nitrogen from the wastewater, and the production of water suitable for reuse. In the flowsheet, energy is derived from the wastewater by first shunting a large fraction of the organic carbon in the wastewater to a solids slurry which is treated via anaerobic digestion. The anaerobic digestion system consists of focused pulsed (FP) pretreatment coupled to anaerobic membrane bioreactors (MBRs). Computer modelling and simulation results are used to optimize design of the system. Energy generation from the system is maximized and costs are reduced by using modest levels of recycle flow from the anaerobic MBRS to the FP pretreatment step.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.011
GPT teacher head0.205
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueWater Science & TechnologySame topicWater-Energy-Food Nexus StudiesFrench-language works237,207