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Record W4255792266 · doi:10.32920/ryerson.14666307.v1

Biodegradation of Diesel Contaminated Wastewater Using a Three-Phase Fluidized Bed Reactor

2021· preprint· en· W4255792266 on OpenAlexaff
Gisselly Anania Muñoz

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDiesel fuelFluidized bedWaste managementWastewaterEffluentEnvironmental scienceContaminationEnvironmental engineeringEngineeringEcology

Abstract

fetched live from OpenAlex

The use of petroleum-derived products has given rise to environmental concerns regarding hydrocarbon pollution. Therefore, the development of innovative techologies for the clean-up of contaminated sites is a challenge. This thesis is an investigation of a three-phase fluidized bed biofilm reactor, as an effective technology for biological treatment of diesel-contaminated wastewater. The three-phase fluidized bed utilized in this research consists of support media (diameter of 600 um) with biofilm, and gas phase (air at 1.0 cm/s) in up flowing liquid (feedwater at 0.02 cm/s). The reactor influent is synthetic wastewater varying in COD concentrations in the range of 550-1300 mg/l and diesel concentrations between 70 and 200 mg/L. The results indicate that diesel fuel can be removed in the reactor with efficiencies up to 100% at a hydraulic detention time of 4 hours. Good quality effluent means a good reactor performance, where 55% of the diesel fuel was removed due to biological process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.036
GPT teacher head0.276
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2021
Admission routes1
Has abstractyes

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