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Record W2933965401 · doi:10.11159/iceptp19.153

Performance of up-flow anaerobic sludge blanket followed by continuous-flow sequencing batch reactor

2019· article· en· W2933965401 on OpenAlexvenueno aff
Abdelsalam Elawwad, Mohamed Hazem, Hisham Abdel‐Halim

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
Fundersnot available
KeywordsBlanketSequencing batch reactorFlow (mathematics)Waste managementAnaerobic exerciseEnvironmental sciencePulp and paper industryProcess engineeringMaterials scienceSewage treatmentEnvironmental engineeringEngineeringMechanicsBiologyPhysics

Abstract

fetched live from OpenAlex

A system consists of an up-flow anaerobic sludge blanket (UASB) and a continuous flow sequencing batch reactor (contflow SBR) was operated under different retention times.UASB was tested at 2.8, 4.4, then 5.7 hrs.The average chemical oxygen demand (COD) removal in UASB was 51.5 % on average.Cont-flow SBR was tested at 4 to 6 and then at 8 hrs cycle periods.The results indicated that the ability of the pilot plant to work under different retention times with removal efficiencies for COD, TN, and phosphate up to 96.5%, 62.6 %, and 35.9% respectively.The main advantage of the proposed treatment system is the minimization of investment and operational costs as compared to the use of cont-flow SBR systems alone.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental Engineering→Same topicWastewater Treatment and Nitrogen Removal→French-language works237,207→