MétaCan
Menu
Back to cohort
Record W1939231954 · doi:10.21083/surg.v5i1.1257

Determining a Bioventing Scale-Up Factor

2011· article· en· W1939231954 on OpenAlexafffundvenue
Michael A. Beswick, Richard G. Zytner

Bibliographic record

VenueSURG Journal · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGasolineEnvironmental scienceSoil waterGroundwater remediationBioremediationEnvironmental remediationEnvironmental engineeringContaminationSoil scienceEnvironmental chemistryWaste managementChemistryEngineeringEcology

Abstract

fetched live from OpenAlex

Bioventing is an increasingly popular means of removing hazardous petroleum products from sites contaminated by industry and underground gasoline storage tanks. A mesoscale bioventing reactor system was used to determine the rate of bioremediation and compared to previous work completed on smaller scale reactors. Ten 4kg reactors with two different soil types were spiked with synthetic gasoline to an initial concentration of 4000mg/kg soil. Vacuum was then applied at a rate of 1mL/min, with sufficient water levels monitored and maintained to induce bioventing conditions. Gas chromatography was used to determine concentrations of synthetic gasoline in soil every two days for each soil type. Results indicate a smaller scale up factor for sandy soils (Delhi), than for clayey soils (Elora). Furthermore it was observed that slower decay rates exist as reactor size increases, suggesting that conservative estimates are needed when transferring lab results to the field.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0200.001

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 head0.038
GPT teacher head0.221
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations0
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueSURG JournalSame topicMicrobial bioremediation and biosurfactantsFrench-language works237,207