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Record W2317562980 · doi:10.1515/ijfe-2014-0217

Electrolyzed Water Generated Using a Circulating Reactor

2015· article· en· W2317562980 on OpenAlexaff
Tian Ding, Xiaoting Xuan, Donghong Liu, Xingqian Ye, John Shi, Keith Warriner, Sophia Jun Xue, Carol L. Jones

Bibliographic record

VenueInternational Journal of Food Engineering · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsChlorineElectrolysisChemistryDilutionHand sanitizerElectrolytic processEnvironmental chemistryInorganic chemistryFood scienceOrganic chemistryElectrodeElectrolyte

Abstract

fetched live from OpenAlex

Abstract Electrolyzed water offers several advantages over other sanitizers for sanitation of both food contact and non-contact surfaces. However, current electrolyzed water-generating process has low fluid output. To overcome such limitations, a circulating electrolyzed water-generating system has been developed in this study. The effects of NaCl/HCl concentration and electrolysis time were investigated. The free chlorine form (HClO and ClO – ) of circulating electrolyzed water, and NaClO with the available chlorine concentrations of 50, 100, 200 mg/L were analyzed by using an ultraviolet spectrophotometer. The results show that the main chlorine form was HClO when the pH of solution was 6.44–6.53. The only ClO – in NaClO solutions when the pH of solution is 11.90. With the dilution of circulating electrolyzed water, the HClO concentration decreased while its proportion account for total available chlorine concentration increased (from 56.99% to 74.29%). The results indicated the potential application of diluted circulating electrolyzed water with high available chlorine concentration. The developed circulating electrolyzed water system in this study could be considered as a potential sanitizer due to its high stability, strong antimicrobial activity with high concentration of HClO and minimized equipment requirements for production.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.072
GPT teacher head0.304
Teacher spread0.232 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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