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Record W2083846077 · doi:10.5004/dwt.2009.465

Seeded crystallization of calcite and aragonite in seawater as a pretreatment scale control process, a study of supersaturation limits

2009· article· en· W2083846077 on OpenAlexfundno aff
Waid Omar, Habis Al‐Zoubi, Joachim Ulrich

Bibliographic record

VenueDesalination and Water Treatment · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsnot available
FundersUniversity of Lethbridge
KeywordsAragoniteCalciteSupersaturationSeawaterCalcium carbonateCrystallizationSeedingSeed crystalArtificial seawaterChemistryCarbonateChemical engineeringMineralogyInorganic chemistryGeologyCrystallographyOceanographyThermodynamicsSingle crystalOrganic chemistry

Abstract

fetched live from OpenAlex

The seeding crystallization of calcite and aragonite in seawater was evaluated theoretically and experimentally. The level of supersaturation with respect to calcium carbonate, which is the driving force for the crystal growth, was found to be influenced by the pH value of seawater, the temperature and the seed morphology. It was proven experimentally and theoretically that the level of supersaturation in seawater with respect to calcium carbonate is more sensitive to pH than to temperature. The growth process of calcite or aragonite cannot start if the pH value of seawater is not adjusted to be higher than 8.0 in the basic medium. An initial pH value of 8.2 is found to be enough to initiate the growth process of both calcite and aragonite seeds. Calcite seeds were found to be subjected to higher levels of supersaturation than aragonite.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.259
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2009
Admission routes1
Has abstractno

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