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Record W4408432717 · doi:10.5194/egusphere-egu25-11423

Investigation of fluid-flow and mineral carbonation reaction processes in vesicular basalt by computed x-ray tomography

2025· preprint· en· W4408432717 on OpenAlexaff
Graham D.M. Andrews, Sarah Brown, Ralf Ditscherlein, Dustin Crandall

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsMira Geoscience (Canada)
Fundersnot available
KeywordsCarbonationBasaltX-rayTomographyComputed tomographyMineralGeologyMineralogyFlow (mathematics)Fluid dynamicsMaterials scienceGeochemistryMechanicsPhysicsMetallurgyComposite materialMedicineRadiologyOptics

Abstract

fetched live from OpenAlex

Mineral carbonation of subsurface basalt by CO2-rich fluids is a proven CO2 sequestration method. Aqueous and supercritical CO2 fluids permeate through variably porous lava layers away from the injection well, and somewhere along this flow pathway, mineral carbonation reactions initiate. Mineral carbonation is a two-stage process of dissolution of silicate phases by carbonic acid followed by precipitation of carbonate minerals from solution. Where along the flow pathway and when, relative to the start of injection, mineral carbonation begins is largely unconstrained. Sub-millimetre-scale x-ray tomography reveals the vesicle (i.e. porosity) structure in 3D. Scans reveal a bimodal vesicle size distribution in macroscopically vesicle-rich samples. Small (

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 score0.003
Threshold uncertainty score0.006

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 communication0.0010.000
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 head0.210
Teacher spread0.199 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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