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Record W1987929160 · doi:10.1002/bit.21050

On‐line estimation of dissolved methane concentration during methanotrophic fermentations

2006· article· en· W1987929160 on OpenAlexaff
Yinghao Yu, Juliana A. Ramsay, Bruce A. Ramsay

Bibliographic record

VenueBiotechnology and Bioengineering · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsQueen's University
Fundersnot available
KeywordsMethaneBioreactorChemistryAqueous solutionMethanotrophAnaerobic oxidation of methaneEnvironmental chemistryAqueous two-phase systemPhase (matter)Organic chemistry

Abstract

fetched live from OpenAlex

Knowledge of the aqueous phase methane concentration is critical to understanding and controlling process kinetics in methanotrophic bioreactors. Unfortunately since no dissolved methane probe is commercially available, this data must be obtained off-line by the time-consuming gas-liquid partition method. In this study we demonstrate how knowledge of the reactor's k(L)a for oxygen combined with gas phase methane analysis can be used to continuously estimate the aqueous phase concentration of dissolved methane. The on-line estimation was verified in two reactor systems with greatly different values of k (L)a. In both systems the measured and calculated dissolved methane concentrations were in good agreement although dissolved methane was underestimated in both cases. The utility of this methodology was demonstrated by revealing a possible metabolic bottleneck in the model system.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.212
Teacher spread0.207 · 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

Citations48
Published2006
Admission routes1
Has abstractyes

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