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Record W4315779565 · doi:10.1039/d2ce01594c

Accurate and efficient polymorph energy ranking with XDM-corrected hybrid DFT

2023· article· en· W4315779565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystEngComm · 2023
Typearticle
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsDalhousie University
FundersAgencia Estatal de InvestigaciónMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia e InnovaciónGobierno del Principado de Asturias
KeywordsCrystal structure predictionPairingRanking (information retrieval)Dispersion (optics)Crystal (programming language)Energy (signal processing)Density functional theoryCrystal structureMaterials scienceStatistical physicsHybrid functionalComputational physicsComputational chemistryCrystallographyPhysicsMathematicsComputer scienceChemistryStatisticsCondensed matter physicsQuantum mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

Pairing the XDM dispersion model with hybrid density functionals shows significant improvements in the computed crystal energy landscapes for 4 of the 26 compounds appearing in the first six blind tests of crystal structure prediction.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.557
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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