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Record W2056139964 · doi:10.1002/cjce.20306

A net draft tube slurry airlift bioreactor for 2,4‐D (2,4‐dichlorophenoxyacetic acid) pesticide biodegradation

2010· article· en· W2056139964 on OpenAlexvenueno aff
Hussein Znad, Hiroki Ohata, Moses O. Tadé

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsAirliftDraft tubeBiodegradationBioreactorActivated sludgeTube (container)Pulp and paper industryTextileChromatographyWaste managementChemistryMaterials scienceEnvironmental scienceEnvironmental engineeringComposite materialEngineeringWastewaterOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Biodegradation of the pesticides 2,4‐D have been investigated in a net draft tube airlift bioreactor at different concentrations (10–160 ppm) and air flow rates (0.75–4 L min −1 ), employing acclimatised activated sludge. A modification for the glass draft tube airlift bioreactor was proposed in which the draft tube is made of non‐woven polypropylene textile net. The experiments were carried out as well in a bubble column (BC) for comparison. The results confirmed that immobilising the activated sludge on the net of the draft tube could enhance the substrates mass transfers and improve the biodegradation rate. A mathematical model was developed to simulate the biodegradation process. The simulated results were in good agreement with the experiments.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.621

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 integrity0.0000.001
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 head0.005
GPT teacher head0.172
Teacher spread0.168 · 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 teacher head, 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

Citations9
Published2010
Admission routes1
Has abstractyes

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