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Record W2319387468 · doi:10.1021/es502133k

Role of Pb(II) Defects in the Mechanism of Dissolution of Plattnerite (β-PbO<sub>2</sub>) in Water under Depleting Chlorine Conditions

2014· article· en· W2319387468 on OpenAlexafffund
Daoping Guo, C. E. Robinson, José E. Herrera

Bibliographic record

VenueEnvironmental Science & Technology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsWestern University
FundersCanadian Water NetworkCanada Foundation for InnovationUniversity of Oklahoma
KeywordsDissolutionChlorineChemistryCarbonateOxideEnvironmental chemistryInorganic chemistryCorrosionLead oxideLead dioxideElectrochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Destabilization of lead corrosion scales present in plumbing materials used in water distribution systems results in elevated lead concentrations in drinking water. Soluble lead release caused by changes in water chemistry has been linked to dissolution of lead carbonate and/or lead oxide solid phases. Although prior studies have examined the effects of varying water chemistry on the dissolution of plattnerite (β-PbO2), β-PbO2 dissolution under depleting chlorine conditions is poorly understood. This paper reports results obtained for long-term batch dissolution experiments for solid phase β-PbO2 under depleting chlorine conditions. Results indicate that the initial availability of free chlorine effectively depresses dissolved lead concentrations released from β-PbO2. However, the dissolved lead levels remained low (∼4 μg/L) even after free chlorine was depleted. Detailed spectroscopic characterization of solid samples collected during the β-PbO2 experiments indicates that changes in the electronic structure of PbO2 occurred during the dissolution. This further points out that Pb2+ defects present in crystalline β-PbO2 play a dominant role in the dissolution of this solid phase.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.515

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 communication0.0000.000
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 head0.188
Teacher spread0.184 · 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

Citations32
Published2014
Admission routes2
Has abstractyes

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