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Record W1997778803 · doi:10.1021/bp0500720

A Kinetic Model for Suspended and Attached Growth of a Defined Mixed Culture

2005· article· en· W1997778803 on OpenAlexaff
Kawai Tam, Mark R. Matsumoto, John D. Sheppard

Bibliographic record

VenueBiotechnology Progress · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsMcGill University
Fundersnot available
KeywordsSubstrate (aquarium)FermentationBiofilmBiomass (ecology)ChemistryMaltoseWastewaterChromatographyMicrobiologyActivated sludgePulp and paper industryBacteriaFood scienceBiologyEnvironmental scienceEnvironmental engineeringSucroseEcology

Abstract

fetched live from OpenAlex

Kinetic experiments were carried out in a semicontinuous wastewater treatment process called self-cycling fermentation (SCF) using a defined mixed culture and various concentrations of synthetic brewery wastewater. The same consortium, which had been previously identified as Acinetobacter sp., Enterobacter sp., and Candida sp., were used in these experiments. The overall rate of substrate removal was attributable to both suspended microbes and the biofilm that formed during the treatment process. A rate expression was developed for the SCF system for a range of synthetic wastewaters containing glucose and various initial concentrations of ethanol and maltose. The data indicated that substrate removal by the suspended cells was directly related to the biomass concentration. However, substrate removal by the biofilm was apparently not affected by the biofilm thickness and was a function of substrate concentration only.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.014
GPT teacher head0.238
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations2
Published2005
Admission routes1
Has abstractyes

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