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Record W4392269411 · doi:10.1111/jfs.13107

Effect of gas ultrafine bubbles on the potency of antimicrobials against <i>Escherichia coli</i><scp>O157</scp>:<scp>H7</scp> biofilms on various food processing surfaces

2024· article· en· W4392269411 on OpenAlex
Phoebe Unger, Amninder Singh Sekhon, Sonali Sharma, Alexander Lampien, Minto Michael

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

VenueJournal of Food Safety · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsAgropur cooperative
Fundersnot available
KeywordsPotencyEscherichia coliAntimicrobialBiofilmFood scienceChemistryMicrobiologyFoodborne pathogenBacteriaBiologyIn vitroBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This study investigated the impact of incorporating gas [air, carbon dioxide (CO 2 ), and nitrogen (N 2 )] UFB on the potency of chlorine (Cl 2 ; 50, 100, and 200 ppm) and peracetic acid (PAA; 20, 40, and 80 ppm) antimicrobial (AM) solutions against fresh (3 days) and aged (30 days) E. coli O157:H7 biofilms on polypropylene, silicone, and stainless‐steel surfaces. The biofilms were statically grown on polypropylene, silicone, and stainless‐steel coupons (7.62 × 2.54 cm) at 25°C for 3 or 30 days by immersing in a 3‐strain cocktail of E. coli . The incorporation of air, CO 2 , and N 2 UFB in AM solutions resulted in significantly increased log reductions (2.1–3.7 logs) in fresh and aged E. coli biofilms on all surfaces compared to solutions without UFB, except for N 2 UFB on aged stainless‐steel biofilms and air UFB on aged polypropylene biofilms, which resulted in similar log reductions as solutions without UFB (1.5–2.1 logs).

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)0.002
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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