MétaCan
Menu
Back to cohort
Record W2556324700 · doi:10.2166/washdev.2016.024

Inactivation of E. coli by copper and silver wire in the presence of synthetic sunlight for safe drinking water

2016· article· en· W2556324700 on OpenAlexaff
G. J. McLaughlin, Vikramjit Bajwa, Mukund R. Shukla, Kevin Hall, Praveen K. Saxena

Bibliographic record

VenueJournal of Water Sanitation and Hygiene for Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCopperSunlightIrradiationCopper wireSignificant differenceWater treatmentPortable water purificationContaminationChemistryMaterials scienceEnvironmental engineeringNuclear chemistryMetallurgyEnvironmental sciencePhysicsBiologyMathematicsEcologyOptics

Abstract

fetched live from OpenAlex

Bacterially-contaminated water is a major health concern leading to infectious diseases in emerging nations. The use of copper (Cu) and silver (Ag) wire independently, and Cu wire in combination with synthetic sunlight (SySu), were investigated as a low-cost water treatment method. Water inoculated with 1,100 colony forming units/mL of Escherichia coli was treated with one of these four treatments: (1) 50 cm2/L surface area (SA) pure Cu wire; (2) 37.8 W/m2 SySu irradiation; (3) a 50 cm2/L SA pure Cu wire combined with the 37.8 W/m2 SySu irradiation; and (4) 5 cm2/L pure Ag wire. An improved rate of bacterial inactivation was achieved using the combined Cu-SySu treatment method compared to either treatment applied independently. When given independently, the Ag wire treatment was more effective than the Cu wire treatment. Cu and Ag content in the water, tested at the end of the experiment, remained far below the safety limits suggested by the World Health Organization. The Cu-SySu combination method has a great potential to be used as a low-cost, re-useable, low-maintenance method of choice for purification of contaminated drinking water.

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 score0.018
Threshold uncertainty score0.104

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Water Sanitation and Hygiene for DevelopmentSame topicWastewater Treatment and ReuseFrench-language works237,207