MétaCan
Menu
Back to cohort
Record W2758240413 · doi:10.1021/acs.cgd.7b00874

The Water–Amorphous Calcium Carbonate Interface and Its Interactions with Amino Acids

2017· article· en· W2758240413 on OpenAlexaff
Riccardo Innocenti Malini, Aaron R. Finney, Sebastian Hall, Colin L. Freeman, John H. Harding

Bibliographic record

VenueCrystal Growth & Design · 2017
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsNational Research Council Canada
FundersEngineering and Physical Sciences Research Council
KeywordsAmorphous calcium carbonateAmorphous solidCalciteCalcium carbonateChemistryCarbonateAnhydrousCrystallizationAmino acidCalciumCrystallographyChemical engineeringInorganic chemistryMineralogyOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Amorphous calcium carbonate is often the first phase to precipitate from solution during the mineralization of calcium carbonate, before the formation of one of the crystalline polymorphs. In vivo, this phase is believed to be essential for the manufacture of minerals displaying nonequilibrium morphologies. The precipitation of this, usually transient, phase and its subsequent transformation into one of the crystalline polymorphs can be controlled by organic molecules. Here, we present a series of molecular dynamics simulations that explore the amorphous calcium carbonate?water interface, the attachment of amino acids onto both hydrous and anhydrous amorphous calcium carbonate, and their effect on the surface. The results show that surface ions have a different coordination number distribution from bulk ions and can diffuse up to two orders of magnitude faster than their bulk counterparts, suggesting that crystallization is much more likely to occur in this region. All the amino acids investigated bind to the amorphous calcium carbonate surfaces. However, acidic amino acids have a clear preference for the surface of amorphous CaCO3?H2O. The favored mode of interaction of the amino acids is through amine and/or guanidine moieties. The important ramifications of the results for our understanding of protein?mineral interactions are discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.268
Teacher spread0.234 · 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

Citations33
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCrystal Growth & DesignSame topicCalcium Carbonate Crystallization and InhibitionFrench-language works237,207