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Record W4388125017 · doi:10.1021/acsestwater.3c00428

Comparison of <i>Legionella pneumophila</i> and <i>Pseudomonas fluorescens</i> Quantification Methods for Assessing UV LED Disinfection

2023· article· en· W4388125017 on OpenAlex
Jaser Lara de Larrea, Sean A. MacIsaac, Kyle D. Rauch, Amina K. Stoddart, Graham A. Gagnon

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS ES&T Water · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPseudomonas fluorescensLegionella pneumophilaBiofilmUltravioletMicrobiologyLegionellaMaterials scienceChemistryBiologyOptoelectronicsBacteria

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide This study assesses the efficacy of ultraviolet light-emitting diodes (UV LEDs) for deactivating Legionella pneumophila (pure culture) and Pseudomonas fluorescens (pure culture and biofilms) on relevant drinking water distribution system surfaces (cast iron and stainless steel). UV LED treatment at 280 nm demonstrated superior performance compared to that at 365 nm, achieving a 4.8 log reduction value (LRV) for P. fluorescens pure cultures and, for biofilms, 4.02 LRV for stainless steel and 2.96 LRV for cast iron at 280 nm. Conversely, the results were less effective at 365 nm, with suspected photolytic reactions on cast iron. Quantification of L. pneumophila yielded varying results: 4 LRV using standard plate counts, 1.8 LRV with Legiolert, and 1 LRV with quantitative polymerase chain reaction at 280 nm, while the results were less than 1.5 LRV at 365 nm. This study provides insights into managing opportunistic pathogens and biofilms, emphasizing the need for improved quantification tools to better assess treatment efficacy.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.015
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.050
GPT teacher head0.404
Teacher spread0.354 · 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