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Record W4377292669 · doi:10.1021/acs.jctc.3c00182

The OpenMolcas <i>Web</i> : A Community-Driven Approach to Advancing Computational Chemistry

2023· article· en· W4377292669 on OpenAlexfundno aff
Giovanni Li Manni, Ignacio Fdez. Galván, Ali Alavi, Flavia Aleotti, Francesco Aquilante, Jochen Autschbach, Davide Avagliano, Alberto Baiardi, Jie J. Bao, Stefano Battaglia, Letitia Birnoschi, Alejandro Blanco-González, Sergey I. Bokarev, Ria Broer, Roberto Cacciari, Paul B. Calio, Rebecca K. Carlson, Rafael C. Couto, Luis Cerdán, Liviu F. Chibotaru, Nicholas F. Chilton, Jonathan R. Church, Irene Conti, Sonia Coriani, Juliana Cuéllar-Zuquin, Razan E. Daoud, Nike Dattani, Piero Decleva, Coen de Graaf, Mickaël G. Delcey, Luca De Vico, Werner Dobrautz, Sijia S. Dong, Rulin Feng, Nicolas Ferré, Michael Filatov, Laura Gagliardi, Marco Garavelli, Leticia González, Yafu Guan, Meiyuan Guo, Matthew R. Hennefarth, Matthew R. Hermes, Chad E. Hoyer, Miquel Huix‐Rotllant, Vishal Kumar Jaiswal, Andy Kaiser, Danil Kaliakin, Marjan Khamesian, Daniel S. King, Vladislav Kochetov, Marek Krośnicki, Arpit Arun Kumaar, Ernst D. Larsson, Susi Lehtola, Marie-Bernadette Lepetit, Hans Lischka, Pablo López Ríos, Marcus Lundberg, Dongxia Ma, Sebastian Mai, Philipp Marquetand, Isabella C. D. Merritt, Francesco Montorsi, Maximilian Mörchen, Artur Nenov, Nguyen Vu Ha Anh, Yoshio Nishimoto, Meagan S. Oakley, Massimo Olivucci, Markus Oppel, Daniele Padula, Riddhish Pandharkar, Quan Manh Phung, Felix Plasser, Gerardo Raggi, Elisa Rebolini, Markus Reiher, Ivan Rivalta, Daniel Roca‐Sanjuán, Thies Romig, Arta Anushirwan Safari, Aitor Sánchez-Mansilla, Andrew M. Sand, Igor Schapiro, Thais R. Scott, Javier Segarra‐Martí, Francesco Segatta, Dumitru‐Claudiu Sergentu, Prachi Sharma, Ron Shepard, Yinan Shu, Jakob K. Staab, Tjerk P. Straatsma, Lasse Kragh Sørensen, Bruno Nunes Cabral Tenorio, Donald G. Truhlar, Liviu Ungur, Morgane Vacher, Valera Veryazov, T. Voß, Oskar Weser, Dihua Wu, Xuchun Yang, David R. Yarkony, Chen Zhou, J. Patrick Zobel, Roland Lindh

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsBasic Energy SciencesDivision of ChemistryNational Supercomputer Centre, Linköpings UniversitetAir Force Office of Scientific ResearchNarodowe Centrum Badań i RozwojuHORIZON EUROPE Framework ProgrammeMinnesota Supercomputing Institute, University of MinnesotaUniversity of California, IrvineOffice of ScienceAlliance de recherche numérique du CanadaFundación Bancaria Caixa d'Estalvis i Pensions de BarcelonaGrand Équipement National De Calcul IntensifNovo Nordisk FondenEuropean CommissionUniversità di BolognaEuropean Regional Development FundAcademy of FinlandCentre National de la Recherche ScientifiqueKnut och Alice Wallenbergs StiftelseArgonne National LaboratoryUppsala UniversitetH2020 European Research CouncilLunds UniversitetMinistero dell’Istruzione, dell’Università e della RicercaAgencia Estatal de InvestigaciónHebrew University of JerusalemUppsala Multidisciplinary Center for Advanced Computational ScienceJapan Society for the Promotion of ScienceLinköpings UniversitetMinistero dell'Università e della RicercaButler UniversityEidgenössische Technische Hochschule ZürichU.S. Department of EnergyCarl Tryggers Stiftelse för Vetenskaplig ForskningUniversität WienUniversitat Rovira i VirgiliPartnership for Advanced Computing in Europe AISBLSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungÉcole Normale Supérieure de LyonDeutsche ForschungsgemeinschaftNational University of SingaporeMinistry of Defence, SingaporeStiftelsen Olle Engkvist ByggmästareGeneralitat de CatalunyaTrinity College DublinUniversity of ManchesterMinisterul Cercetării, Inovării şi DigitalizăriiUniversität RostockUniversità degli Studi di SienaChemical Sciences, Geosciences, and Biosciences DivisionETH Zürich FoundationDanmarks Frie ForskningsfondMinisterio de Ciencia, Innovación y UniversidadesUniversity of ChicagoRoyal Society“la Caixa” FoundationMinisterio de Ciencia e InnovaciónBowling Green State UniversityHelsingin YliopistoEuropean Cooperation in Science and TechnologyTexas Tech UniversityOak Ridge National LaboratoryNational Science CouncilNational Science FoundationHorizon 2020 Framework ProgrammeVetenskapsrådetUniversity of MinnesotaNovo NordiskLoughborough University
KeywordsComputer scienceFocus (optics)Electronic structureComputational scienceSoftwareMolecular dynamicsNanotechnologyChemistryData scienceComputational chemistryPhysicsMaterials science

Abstract

fetched live from OpenAlex

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0060.006
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0400.019

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 head0.013
GPT teacher head0.280
Teacher spread0.267 · 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".

Quick stats

Citations342
Published2023
Admission routes1
Has abstractyes

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