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Record W2036461492 · doi:10.1080/09593330903527898

Performance and fouling characteristics of a submerged anaerobic membrane bioreactor for kraft evaporator condensate treatment

2010· article· en· W2036461492 on OpenAlex

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

VenueEnvironmental Technology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of GuelphLakehead University
Fundersnot available
KeywordsSpargingMembrane foulingBiogasFoulingChemical oxygen demandChemistryPulp and paper industryMembrane bioreactorBioreactorWaste managementAnaerobic digestionKraft paperMethaneMembraneChemical engineeringEnvironmental engineeringSewage treatmentEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Submerged anaerobic membrane bioreactor (SAnMBR) technology was studied for kraft evaporator condensate treatment at 37 +/- 1 degrees C over a period of 9 months. Under tested organic loading rates of 1-24 kg COD/m3/day, a chemical oxygen demand (COD) removal efficiency of 93-99% was achieved with a methane production rate of 0.35 +/- 0.05 L methane/g COD removed and a methane content of 80-90% in produced biogas. Bubbling of recycled biogas was effective for in-situ membrane cleaning, depending on the biogas sparging rate used. The membrane critical flux increased and the membrane fouling rate decreased with an increase in the biogas sparging rate. The scanning electron microscopy images showed membrane pore clogging was not significant and sludge cake formation on the membrane surface was the dominant mechanism of membrane fouling. The results suggest that the SAnMBR is a promising technology for energy recovery from kraft evaporator condensate.

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 score0.063
Threshold uncertainty score0.914

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 studies0.0000.001
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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