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Record W4378905952 · doi:10.2533/chimia.2023.355

Dynamic Materials, Crystals, and Phenomena Conference

2023· article· en· W4378905952 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCHIMIA International Journal for Chemistry · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMachine Learning in Materials Science
Canadian institutionsnot available
FundersNational Center of Competence in Research Bio-Inspired Materials, University of FribourgSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsMaterials scienceEngineering physicsNanotechnologyPhysics

Abstract

fetched live from OpenAlex

addressed essential experimental and theoretical techniques for assessing the structural and dynamic properties of this unique class of materials at a spatial-temporal level.The hybrid conference format involved sessions both on-site and online, providing attendees with insights into the dynamic materials, crystals, and phenomena.The program consisted of a series of keynote and invited talks, contributing presentations, and a poster session that covered a wide range of related topics (Fig. 3).The first day of the conference began with a keynote address by Stephen Loeb (University of Windsor, Canada) on designing mechanically interlocked molecules to function in the solid state, which provided a historical perspective on solid-state dynamics.The focus was on macrocyclic ring rotation, large amplitude translation, molecular switching, and the precise placement and interaction between components with different dynamics.This was followed by an invited talk by Angiolina Comotti (University of Milano-Bicocca, Italy) on rotor dynamics and light-driven motors in 3D porous architectures.In the afternoon, invited lectures covered topics such as pressure-driven phase transitions for solidstate refrigeration by Claire Hobday (University of Edinburgh, UK), non-crystallinity and disorder in dynamic metal-organic frameworks by Sebastian Henke (Technische Universität Dortmund, Germany), and static and dynamic conformational freedom by Stefano Canossa (Max Planck Institute for Solid-

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.039
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.297
Teacher spread0.283 · 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