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Record W2074305395 · doi:10.4236/jwarp.2015.75031

Impact of Water Chemistry on Lead Carbonate Dissolution in Drinking Water Distribution Systems

2015· article· en· W2074305395 on OpenAlex

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

VenueJournal of Water Resource and Protection · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsWestern UniversityCarleton University
FundersCanadian Water Network
KeywordsAlkalinityDissolutionChemistryCarbonateEnvironmental chemistrySolubilityChlorineCorrosionMetalInorganic chemistry

Abstract

fetched live from OpenAlex

Elemental lead is a known toxic metal that can pose threats to human health and can be found in a variety of sources including drinking water at very low level concentrations (i.e. μg/L range). Destabilization of the corrosion scale at the inner layer of pipeline is the major source of lead in drinking water. Chemical properties of the water passing through the distribution system such as pH, alkalinity, chlorine content, oxidation reduction potential (ORP) and natural organic matters will affect the formation and/or destabilization of the corrosion scale. This research examines the impact of pH values (7.0 - 9.5), temperatures (5°C vs 20°C) and alkalinity levels (moderate vs low), in the presence of chlorine, on dissolution of hydrocerussite and cerussite in drinking water by various sets of batch dissolution experiments. The results showed dissolution of cerussite and hydrocerussite was not impacted significantly by pH ranging 7.0 - 9.5. In addition, and somewhat surprisingly, cold temperature (5°C) and moderate alkalinity showed a great influence on decreasing the solubility of lead species.

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 score0.013
Threshold uncertainty score0.215

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 head0.020
GPT teacher head0.237
Teacher spread0.217 · 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