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Record W1978711337 · doi:10.1139/s06-062

Impact on water distribution system biofilm densities from reverse osmosis membrane treatment of supply water

2007· article· en· W1978711337 on OpenAlexvenueno aff
Mark C. Meckes, Roy C. Haught, Keith C. Kelty, Janet C. Blannon, David Cmehil

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsReverse osmosisEnvironmental scienceTotal organic carbonNutrientWater qualityWater treatmentEnvironmental engineeringBiofilmPopulationHeterotrophEnvironmental chemistryChemistryPulp and paper industryEcologyBacteriaBiologyMembrane

Abstract

fetched live from OpenAlex

The quality of potable water is such that the concentration of nutrients available for growth of microorganisms within distribution systems is limited. In such systems carbon is often the growth limiting nutrient. Research conducted in the Netherlands has indicated that low levels (<10 μg/L) of available organic carbon in water is sufficient to maintain an actively growing population of heterotrophic, or organic carbon utilizing, bacteria in aquatic systems. However, the ability of commercially available and cost effective technologies to achieve such low concentrations of assimilable organic carbon in full-scale water systems is doubtful. Reverse osmosis (RO) systems have been used for many years to effectively remove contaminants from source waters. We challenged a water distribution system simulator (DSS) with water from a municipal system and water that was treated using an RO system under two concentrations of residual free chlorine to evaluate the effect of this disinfectant on biofilms in contact with low nutrient water. Our results showed that biofilm densities in the DSS carrying low nutrient RO treated water were lower than biofilm densities taken from the DSS when it carried water directly obtained from a municipal system.Key words: water distribution systems, reverse osmosis, biofilms, heterotrophic plate count, HPC, chlorine, assimilable organic carbon.

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 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 score0.263
Threshold uncertainty score0.321

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)0.0000.000

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 head0.004
GPT teacher head0.180
Teacher spread0.176 · 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.

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
Published2007
Admission routes1
Has abstractyes

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