MétaCan
Menu
Back to cohort

Interactions between humic matter and bacteria when disinfecting water with UV light

2008· article· en· W2120979240 on OpenAlexafffund
Raymond E. Cantwell, Ron Hofmann, Michael R. Templeton

Bibliographic record

VenueJournal of Applied Microbiology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsUniversity of Toronto
FundersCanadian Water Network
KeywordsHumic acidOrganic matterNatural organic matterBacillus subtilisChemistryEscherichia coliEnvironmental chemistryReagentUltravioletUltraviolet lightBacteriaBiologyPhotochemistryBiochemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

AIMS: To investigate the impact of aquatic humic matter on the inactivation of Escherichia coli and Bacillus subtilis by ultraviolet (UV) light. METHODS AND RESULTS: A bench-scale study investigated the potential for Aldrich((R)) humic acid (AHA) and Suwannee River natural organic matter (SR-NOM) to coat the surface of E. coli and B. subtilis and offer protection from low-pressure UV light. UV doses of 5 and 14 mJ cm(-2) were applied using a collimated beam at four concentrations of humic matter (0, 10, 50 and 120 mg l(-1)) in reagent grade water. Both AHA and SR-NOM were found to offer statistically significant protection of both E. coli and B. subtilis at concentrations of 50 and 120 mg l(-1) for a UV dose of 14 mJ cm(-2). CONCLUSIONS: Both E. coli and B. subtilis are susceptible to coating by humic matter which can reduce the sensitivity of the cells to UV light. SIGNIFICANCE AND IMPACT OF THE STUDY: Micro-organisms in the environment may acquire characteristics through interaction with humic matter that render them more resistant to UV disinfection than would be predicted based on laboratory inactivation studies using clean cells.

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 categoriesInsufficient 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 score0.107
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.185
Teacher spread0.179 · 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

Citations54
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Applied MicrobiologySame topicWater Treatment and DisinfectionFrench-language works237,207