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Record W3029972914 · doi:10.1111/wej.12596

Inhibition of nucleation and crystal growth of calcium carbonate in hard waters using <i>Paronychia arabica</i> in an arid desert region

2020· article· en· W3029972914 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.

Bibliographic record

VenueWater and Environment Journal · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCalciteCalcium carbonateNucleationPrecipitationChronoamperometryAridChemistryGroundwaterDielectric spectroscopyMineralogyEnvironmental chemistryChemical engineeringElectrochemistryGeologyCyclic voltammetryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The formation of CaCO 3 of groundwater has important implications in the industry. Many conventional scale inhibitors are considered environmentally unfriendly. In this study, we investigate the effect of aqueous extract of Paronychia arabica (PA) as new green antiscalant agents on the precipitation of CaCO 3 in an arid desert region. The antiscaling properties of these extracts towards CaCO3 formation were tested using chronoamperometry (CA), electrochemical impedance spectroscopy (EIS) and Fast Controlled Precipitation methods. Electrochemical and chemical analysis of Mkhadma groundwater shows a high calcium concentration and the deposit is a pure calcite. The nucleation and formation time were identified. At 32°C, a complete scaling inhibition was obtained using a concentration of 150 mg/L of green extract. The scale inhibitor effect was analysed by an optical microscopic examination.

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)0.000
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 score0.024
Threshold uncertainty score0.343

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 head0.032
GPT teacher head0.220
Teacher spread0.188 · 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