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Record W3135409480 · doi:10.1039/d1ce00052g

New insights into the role of solution additive anions in Mg<sup>2+</sup> dehydration: implications for mineral carbonation

2021· article· en· W3135409480 on OpenAlexaff
Dimitrios Toroz, Fu Song, Gregory A. Chass, Devis Di Tommaso

Bibliographic record

VenueCrystEngComm · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsMcMaster University
FundersAgencia Estatal de InvestigaciónNatural Environment Research CouncilHorizon 2020Engineering and Physical Sciences Research CouncilMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaAgence de l'Environnement et de la Maîtrise de l'EnergieDepartment for Business, Energy and Industrial Strategy, UK Government
KeywordsCarbonationNucleationDehydrationMineralChemistryIonInorganic chemistryChemical engineeringMechanism (biology)Organic chemistryPhysics

Abstract

fetched live from OpenAlex

Computer simulations of the Mg 2+ dehydration mechanism show that solution additives can stabilise undercoordinated Mg 2+ hydration configurations, opening up coordination sites on the central Mg 2+ ion, promoting Mg-carbonates nucleation and growth.

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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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

Citations38
Published2021
Admission routes1
Has abstractyes

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