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Record W2017628807 · doi:10.1080/10934529.2015.987550

Role of iron and aluminum coagulant metal residuals and lead release from drinking water pipe materials

2015· article· en· W2017628807 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsNova scotiaAlkalinityChlorideMetallurgyEnvironmental scienceEnvironmental chemistryChemistryMaterials scienceGeologyOceanography

Abstract

fetched live from OpenAlex

Bench-scale experiments investigated the role of iron and aluminum residuals in lead release in a low alkalinity and high (> 0.5) chloride-to-sulfate mass ratio (CSMR) in water. Lead leaching was examined for two lead-bearing plumbing materials, including harvested lead pipe and new lead: tin solder, after exposure to water with simulated aluminum sulfate, polyaluminum chloride and ferric sulfate coagulation treatments with 1-25-μM levels of iron or aluminum residuals in the water. The release of lead from systems with harvested lead pipe was highly correlated with levels of residual aluminum or iron present in samples (R(2) = 0.66-0.88), consistent with sorption of lead onto the aluminum and iron hydroxides during stagnation. The results indicate that aluminum and iron coagulant residuals, at levels complying with recommended guidelines, can sometimes play a significant role in lead mobilization from premise plumbing.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.305

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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