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Record W4240745220 · doi:10.32920/ryerson.14643972

Photochemical treatment of organic constituents and bacterial pathogens from synthetic slaughterhouse wastewater by combining vacuum-UV and UV-C

2021· preprint· en· W4240745220 on OpenAlexafffund
Mauricio Barrera

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUltravioletWastewaterChemistryDegradation (telecommunications)Total organic carbonIrradiationMolar ratioBacteriaPhotochemistryNuclear chemistryEnvironmental chemistryMaterials scienceOrganic chemistryEnvironmental engineeringCatalysisEnvironmental scienceBiologyOptoelectronics

Abstract

fetched live from OpenAlex

The reduction and degradation of total organic carbon (TOC) and bacteria inactivation efficiency using Vacuum-Ultraviolet (VUV) oxidation process Ultraviolet-C (UV-C) photolytic process, and their combination (UV-C/VUV and VUV/UV-C) from synthetic slaughterhouse wastewater was investigated. TOC removal rates achieved during continuous mode operation were 6.2%, 5.5%, 5.8%, and 6.1%, respectively. In a second stage, H₂O₂ was added to both processes, UV-C/H₂O₂ and VUV/H₂O₂, and it was found that TOC removal rates were increased twice as much during continious flow operation to 10.8% and 12.2%, respectively. The optimum molar ration of H₂O₂/TOC was found to be 2.5 and 1.5 for each process respectively. Finally, it was observed that all photochemical processes achieved over 99.999% (five logs) of bacteria inactivation in a short period of irradiation time, 27.6 sec.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.225
Teacher spread0.210 · 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 teacher head, not a consensus.

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

Citations5
Published2021
Admission routes2
Has abstractyes

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