MétaCan
Menu
Back to cohort
Record W2023069468 · doi:10.1089/ees.2008.0350

Estimation of Carbon Recovery and Biomass Yield in the Biofiltration of Octane

2009· article· en· W2023069468 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.

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

Bibliographic record

VenueEnvironmental Engineering Science · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBiofilterBiomass (ecology)OctaneBiodegradationYield (engineering)RespirometryChemistryCarbon fibersPulp and paper industryEnvironmental chemistryCarbon dioxideEnvironmental scienceEnvironmental engineeringMaterials scienceOrganic chemistryEcologyBiology

Abstract

fetched live from OpenAlex

Octane was eliminated from contaminated air in a biofilter at concentrations ranging from 500–2,000 ppm, with a maximum elimination capacity of 90 g/m3 h. After periods of shutdown of up to 30 days, the biofilter rapidly reacclimated, recovering its destruction and removal efficiency (overall octane removal) within 1–2 h of restart; this recovery was shown to be due to biodegradation and not simply adsorption of the octane. Carbon recovery during restart was estimated to be approximately 0.25 mol CO2/mol C, based on on-line carbon dioxide monitoring, corresponding to a nonsteady state biomass yield of 1.19 g biomass/g octane. In separate respirometry experiments, carbon recovery was estimated to be 0.85 mol CO2/mol C, corresponding to a biomass yield of 0.24 g biomass/g octane. These results, together with literature values for other systems, suggest that for biofilter modeling purposes a steady-state value of biomass yield in the range 0.17–0.43 g biomass/g carbon source would be appropriate, but dynamic models will require more detailed analysis of the biodegradation pathway.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.173

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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