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Preface

2023· article· en· W4389920892 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Physics Conference Series · 2023
Typearticle
Languageen
FieldChemistry
TopicInorganic Fluorides and Related Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsCzechPhysicsLibrary sciencePhilosophyComputer science

Abstract

fetched live from OpenAlex

This volume contains contributions to the XII. International Symposium on Quantum Theory and Symmetries (QTS12) was at Czech Technical University in Prague, Czech Republic, from Monday July 24 until Friday July 28, 2023. The Symposium series “Quantum Theory and Symmetries” (QTS) is a biannual meeting intended for physicists and mathematicians who are either applying symmetries to some physical model, or are studying mathematical objects that are relevant for physical applications. The first Symposium of this series was held in Goslar (Germany) in 1999, QTS-1, then it was held in Cracow (2001) QTS-2, Cincinnati (2003) QTS-3, Varna (2005) QTS-4, Valladolid (2007) QTS-5, Lexington (2009) QTS-6, Prague (2011) QTS-7, Mexico-city (2013) QTS-8, Yerevan (2015) QTS-9, Varna (2017) QTS-10, Montreal (2019) QTS-11. The Symposium QTS-12 was first planned to be in Moscow at the Moscow Institute of Physics and Technology in 2021, but was postponed by one year due to Covid-19, then it was postponed to 2023, July 24-28, and was held in Prague at the Czech Technical University (Department of Mathematics, Faculty of Nuclear Sciences and Physical Engineering, CTU in Prague) QTS-12. The Symposium QTS-13 is planned for the 2nd half of July 2025 to be held in Yerevan, Armenia. The volume is organised as follows: it starts with notes in memory of H. D. Doebner. Then the invited talks at the plenary sessions and the public lecture are published followed by contributions in the parallel and poster sessions in alphabetical order. List of Editors, Advisory committee are available in this Pdf.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.422

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 head0.019
GPT teacher head0.235
Teacher spread0.216 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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