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Record W3032410216 · doi:10.1137/18m1234096

Multiscale Flux-Based Modeling of Biofilm Communities

2020· article· en· W3032410216 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMultiscale Modeling and Simulation · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersFields Institute for Research in Mathematical SciencesNational Science Foundation
KeywordsMicroscale chemistryContext (archaeology)Biological systemBiofilmFlux balance analysisFlux (metallurgy)ComputationFlexibility (engineering)Biochemical engineeringStatistical physicsComputer scienceScale (ratio)PhysicsMathematicsChemistryBiologyEngineeringAlgorithmBioinformaticsStatistics

Abstract

fetched live from OpenAlex

Models of microbial community dynamics generally rely on a subscale description for microbial metabolisms. In systems such as distributed multispecies communities like biofilms, where it may not be reasonable to simplify to a small number of limiting substrates, tracking the large number of active metabolites likely requires measurement or estimation of large numbers of kinetic and regulatory parameters. Alternatively, a largely kinetics-free framework is proposed combining cellular level constrained, steady state flux analysis of metabolism with macroscale microbial community models. This multiscale setup naturally allows coupling of macroscale information, including measurement data, with cell scale metabolism. Further, flexibility in methodology is stressed: choices at the microscale (e.g., flux balance analysis or elementary flux modes) and at the macroscale (e.g., physical-chemical influences relevant to biofilm or planktonic environments) are available to the user. Illustrative computations in the context of a biofilm, including comparisons of systemic and Nash equilibration as well as an example of coupling experimental data into predictions, are provided.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.488

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 integrity0.0000.000
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 head0.031
GPT teacher head0.251
Teacher spread0.220 · 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