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Record W2024910959 · doi:10.2166/wst.2008.013

Characterization of sludges for predicting anaerobic digester performance

2008· article· en· W2024910959 on OpenAlex
Richard M. Jones, Wayne J. Parker, Zahid Khan, Sudhir Murthy, Mark Rupke

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Science & Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of WaterlooEnviroSim (Canada)
Fundersnot available
KeywordsAnaerobic digestionBiodegradationAnaerobic exerciseSewage sludgeActivated sludgeChemistryInertWaste managementBioreactorPulp and paper industryWastewaterSewageEnvironmental scienceEnvironmental engineeringMethaneBiologyEngineering

Abstract

fetched live from OpenAlex

Batch anaerobic digestion tests of primary sludge and waste activated sludge were conducted for a duration of 123 days to determine the ultimate degradability of the sludges. For primary sludges the inert fraction of the particulate COD that was predicted by the wastewater models could be employed to predict their biodegradability under anaerobic conditions. The degradation of waste activated sludge was adequately characterized for the first 60 days of digestion using a model that assumed equivalent biodegradability of particulate COD components under aerobic and anaerobic conditions. However after 60 days of anaerobic digestion it appeared that decay of the endogenous products was occurring. This could be described with a first order decay function with a coefficient of 0.0075 d(-1). For continuous flow digesters operating at SRTs of 30-60 days, the predicted VSS destruction with the modified model was approximately 10% higher than that predicted on the basis of inert endogenous decay products.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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