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Record W2247075134 · doi:10.2166/ws.2001.0089

Suspended particles in the drinking water of two distribution systems

2001· article· en· W2247075134 on OpenAlexafffundabout
Vincent Gauthier, Benoît Barbeau, Robert Millette, J. C. Block, Michèle Prévost

Bibliographic record

VenueWater Science & Technology Water Supply · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsPolytechnique MontréalNatural Sciences and Engineering Research Council of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsParticulatesOrganic matterRange (aeronautics)Environmental scienceEnvironmental chemistrySuspended solidsLaminar flowHydrology (agriculture)ChemistryEnvironmental engineeringGeologyMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The concentrations of suspended particles were measured in the drinking water of two distribution systems, and the nature of these particles documented. The concentrations of particulate matter were invariably found to be small (maximum 350 μg/L). They are globally in the very low range in comparison with dissolved matter concentrations, which are measured in several hundreds of mg/L. Except during special water quality events, such as turnover of the raw water resource, results show that organic matter represents the most important fraction of suspended solids (from 40 to 76%) in treated and distributed water. Examination of the nature of the particles made it possible to develop several hypotheses about the type of particles penetrating Montreal's distribution system during the turnover period (algae skeleton, clays). These particles were found to have been transported throughout the distribution systems quite easily, and this could result in the accumulation of deposits if their surface charge were ever even slightly destabilised, or if the particles were to penetrate the laminar flow areas that are fairly typical of remote locations in distribution systems.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.223
Teacher spread0.215 · 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

Citations65
Published2001
Admission routes3
Has abstractyes

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