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Record W4409324952 · doi:10.1063/4.0000468

LRL_WEB, A Website for a More Thorough Exploration of Bravais Lattice Types of Your Unit Cells

2025· article· en· W4409324952 on OpenAlexaboutno aff
Lawrence C. Andrews, H. J. Bernstein

Bibliographic record

VenueStructural Dynamics · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBravais latticeComputer scienceLattice (music)World Wide WebUnit (ring theory)Theoretical computer scienceMathematicsPhysicsCrystallographyCrystal structureChemistry

Abstract

fetched live from OpenAlex

Even today, the standard programs for determining likely lattice types still sometimes fail to recognize the correct symmetry of a crystal (Le Trong & Stenkamp, 2007). Experience has shown that the programs BGAOL (Andrews & Bernstein, 2014) and the newer program Sella (in preparation) produce more complete results. Sella produces an especially useful map of the hierarchy of lattice types (Grimmer, 2016, described the hierarchy). LRL_WEB allows access to Sella, BGAOL, SAUC (McGill et al., 2014), PlotC3, Delaunay and Niggli reductions. An example of the hierarchy maps is a case cited by Le Trong & Stenkamp, PDB entry 1G2X, as C-centered monoclinic, C 80.95 80.57 57.1 90 90.35 90. Sella produces Figure 1, which of course shows a perfect match to mS (side centered monoclinic), but also a relatively good match to hR (rhombohedral). The example is one of a group of probably identical structures of Krait toxin phospolipase A2. Figure 2 shows two Bravais lattice types, as defined by Delaunay. We can use PlotC3 to learn more about these two orthorhombic types. O3 is described as body-centered, and O4 is side-centered. In Figure 3, the upper panel was produced using O3 data and the lower using O4 data. For each case, CmdGen (on the web site) was used to create 200 random cells of the selected type. Considering the upper panel (O3), there are two panes that show the projections as lines, and the third shows a point. That tells us that the plot is described by a plane, even though we are examining a 6-dimensional plot. The lower panel also shows two projections as lines, but the third is random. In this case we are looking at a 3-space object in the 6-dimensional space S6, one representation of unit cells. So Figure 3 has told us that O3 is a 2-dimensional object, but we know that orthorhombic unit cells have to have 3 parameters. O4 being a 3-space object is what is expected. We learn that O3 is a degenerate type, and we can determine that in a different way using Figure 2. The characteristic of S6 vectors for O3 is (rs0 rs0), and for O4 it is (00r sst). O3 has only 2 available parameters, and O4 has 3, which we expect for orthorhombic. In fact, some additional research shows that O3 is the boundary between two other types.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.443
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0040.006
Open science0.0050.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.4430.231

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 head0.028
GPT teacher head0.272
Teacher spread0.245 · 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.

Study designNot applicable
Domainnot available
GenreSoftware

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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