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Record W174983118 · doi:10.2175/106143007x176004

Performance of Anaerobic Waste Activated Sludge Digesters After Microwave Pretreatment

2007· article· en· W174983118 on OpenAlexaff
Çiğdem Eskicioğlu, Ronald L. Droste, Kevin J. Kennedy

Bibliographic record

VenueWater Environment Research · 2007
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChemistryAnaerobic digestionMesophileChemical oxygen demandBiogasVolatile suspended solidsActivated sludgeTotal dissolved solidsPulp and paper industryBiogas productionFood scienceWaste managementWastewaterBacteriaEnvironmental engineeringMethaneOrganic chemistryBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Effects of microwave pretreatment on waste activated sludge (WAS) in mesophilic semicontinuous digesters with acclimatized inoculum at solids retention times (SRTs) of 5, 10, and 20 days are presented. Batch digesters determined optimum microwave temperature, intensity, WAS concentration, and percentage of WAS pretreated for highest WAS solubilization (soluble to total chemical oxygen demand ratio [SCOD:TCOD]) and biogas production. Pretreatment results indicated the potential to damage floc structure and release 4.2-, 4.5-, and 3.6-fold higher soluble proteins, sugars, and SCOD:TCODs compared with controls, with nucleic acid release. Pretreatment increased dewaterability and bioavailability of WAS with 20% higher biogas production compared with controls in batch digestion. In semicontinuous digesters, relative (to control) improvements in removals dramatically increased, as SRT was shortened from 20 to 10 to 5 days, with 23 and 26% higher volatile solids removals for WAS pretreated to 96 degrees C by microwave and conventional heating at a 5-day SRT.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.236
Teacher spread0.219 · 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 designBench or experimental
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

Citations76
Published2007
Admission routes1
Has abstractyes

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