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Record W1991295438 · doi:10.1021/bp0257776

Naphthalene Biodegradation from Non-Aqueous-Phase Liquids in Batch and Column Systems: Comparison of Biokinetic Rate Coefficients

2003· article· en· W1991295438 on OpenAlexaff
Mohammed Alshafie, Subhasis Ghoshal

Bibliographic record

VenueBiotechnology Progress · 2003
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsMcGill University
Fundersnot available
KeywordsNaphthaleneBiodegradationAqueous solutionChemistryChromatographyPhase (matter)Column (typography)Organic chemistryMathematics

Abstract

fetched live from OpenAlex

The kinetics of microbial degradation of naphthalene from a two-component non-aqueous-phase liquid (NAPL) coated onto uniformly sized nonporous particles were evaluated in a completely mixed batch reactor (CMBR) system and in flow-through column systems to examine the differences in the biodegradation kinetic coefficients, micro(max), the maximum specific growth rate coefficient, and K(s), the half saturation constant in the two systems. The values of these coefficients were estimated by nonlinear least-squares regression of the naphthalene mineralization profiles obtained from both CMBR and column biodegradation experiments. The results show that the range of values for micro(max) and K(s) obtained from column systems are very similar to the range of values obtained from CMBR systems. This suggests that coefficients estimated from CMBR or column systems are equally applicable for modeling studies. The presence of microorganisms and the development of biofilms at the NAPL-water interface reduced the mass transfer rates of naphthalene from the NAPL by 60% in CMBR and by 70% in column systems. If such changes in mass transfer coefficients are not accounted for, significantly erroneous values of biokinetic coefficients may be obtained.

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 categoriesMeta-epidemiology (narrow)
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 score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.324
Teacher spread0.301 · 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.

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

Citations11
Published2003
Admission routes1
Has abstractyes

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