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Record W4307854912 · doi:10.5194/ejm-34-523-2022

TotBlocks: exploring the relationships between modular rock-forming minerals with 3D-printed interlocking brick modules

2022· article· en· W4307854912 on OpenAlexaff
Derek D.V. Leung, Paige E. dePolo

Bibliographic record

VenueEuropean Journal of Mineralogy · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsLaurentian University
FundersUniversity of Edinburgh
KeywordsDiopsideAluminosilicateGeologyMineralogyMaterials scienceCrystallographyChemistry

Abstract

fetched live from OpenAlex

Abstract. Many rock-forming chain and sheet silicate minerals, i.e., pyroxenes, amphiboles, micas, and clay minerals, are built from shared chemical building blocks known as T-O-T modules. Each module consists of two opposing chains of vertex-sharing silica tetrahedra (T), which vertically sandwich a ribbon of edge-sharing metal–oxygen octahedra (O) in a T-O-T configuration. These minerals are both abundant and diverse in the lithosphere because T-O-T modules are chemically versatile (incorporating common crustal elements, e.g., O, Si, Al, Fe, and Mg) and structurally versatile (varying as a function of module width and linkage type) over a wide range of chemical and physical conditions. Therefore, these minerals lie at the center of understanding geological processes. However, their diversity leads to the minerals developing complex, 3D crystal structures, which are challenging to communicate. Ball-and-stick models and computer visualization software are the current methods for communicating the crystal structures of minerals, but both methods have limitations in communicating the relationships between these complex crystal structures. Here, we investigate the applications of 3D printing in communicating modular mineralogy and crystal structures. The open-source TotBlocks project consists of 3D-printed, T-O-T interlocking bricks, based on ideal polyhedral representations of T and O modules, which are linked by hexagonal pegs and slots. Using TotBlocks, we explore the relationships between modular minerals within the biopyribole (biotite–pyroxene–amphibole) and palysepiole (palygorskite–sepiolite) series. The bricks can also be deconstructed into T and O layer modules to build other mineral structures such as the brucite, kaolinite–serpentine, and chlorite groups. Then, we use the T-O-T modules within these minerals to visually investigate trends in their properties, e.g., habit, cleavage angles, and symmetry/polytypism. In conclusion, the TotBlocks project provides an accessible, interactive, and versatile way to communicate the crystal structures of common rock-forming minerals.

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)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.205
Teacher spread0.143 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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