MétaCan
Menu
Back to cohort
Record W2045755987 · doi:10.2166/wst.2007.274

A biofilm model for engineering design

2007· article· en· W2045755987 on OpenAlex
I. Takács, Christopher M. Bye, K. Chapman, Peter Dold, P.M. Fairlamb, Richard M. Jones

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsEnviroSim (Canada)
Fundersnot available
KeywordsActivated sludge modelSolverBioreactorSewage treatmentBiochemical engineeringProcess (computing)BiofilmProcess engineeringWastewaterEngineering design processAnoxic watersActivated sludgeEngineeringEnvironmental scienceEnvironmental engineeringComputer scienceChemistryMechanical engineering

Abstract

fetched live from OpenAlex

A biofilm model is presented for process engineering purposes--wastewater treatment plant design, upgrade and optimisation. The model belongs in the 1D dynamic layered biofilm model category, with modifications that allow it to be used with one parameter set for a large range of process situations. The biofilm model is integrated with a general activated sludge/anaerobic digestion model combined with a chemical equilibrium, precipitation and pH module. This allows the model to simulate the complex interactions that occur in the aerobic, anoxic and anaerobic layers of the biofilm. The model has been tested and is shown to match a variety of design guidelines, as well as experimental results from batch testing and full-scale plant operation. Both moving bed bioreactors (MBBR) and integrated fixed film activated sludge (IFAS) systems were simulated using the same model and parameter set. A new steady-state solver generates fast solutions and allows interactive design work with the complex model.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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