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Record W2518072455 · doi:10.1002/ppap.201600098

LXCat: an Open‐Access, Web‐Based Platform for Data Needed for Modeling Low Temperature Plasmas

2016· article· en· W2518072455 on OpenAlexafffund
Leanne C. Pitchford, L. L. Alves, Klaus Bartschat, S. Biagi, Marie‐Claude Bordage, Igor Bray, C.E. Brion, M. J. Brunger, L. Campbell, Alise Chachereau, Bhaskar Chaudhury, Loucas G. Christophorou, E. Carbone, N. A. Dyatko, Christian M. Franck, Dmitry V. Fursa, Reetesh Kumar Gangwar, Vasco Guerra, Pascal Haefliger, Gerjan Hagelaar, Andreas Hoesl, Yukikazu Itikawa, И. В. Кочетов, R P McEachran, W. L. Morgan, Anatoly P. Napartovich, Vincent Puech, Mohamed Rabie, Lalita Sharma, Rajesh Srivastava, A D Stauffer, Jonathan Tennyson, J. de Urquijo, Jan van Dijk, Larry A. Viehland, Mark C. Zammit, Oleg Zatsarinny, Sergey Pancheshnyi

Bibliographic record

VenuePlasma Processes and Polymers · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsYork UniversityUniversity of British Columbia
FundersFundação para a Ciência e a TecnologiaAustralian Research CouncilTechnische Universiteit EindhovenCentre National de la Recherche ScientifiqueScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaBranco Weiss Fellowship – Society in ScienceInternational Atomic Energy AgencyBoard of Research in Nuclear SciencesNational Science Foundation
KeywordsPlasmaSwarm behaviourIonScatteringComputer scienceOpen sourceMaterials scienceDatabaseWorld Wide WebPhysicsOperating systemNuclear physicsOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

LXCat is an open‐access platform ( www.lxcat.net ) for curating data needed for modeling the electron and ion components of technological plasmas. The data types presently supported on LXCat are scattering cross sections and swarm/transport parameters, ion‐neutral interaction potentials, and optical oscillator strengths. Twenty‐four databases contributed by different groups around the world can be accessed on LXCat. New contributors are welcome; the database contributors retain ownership and are responsible for the contents and maintenance of the individual databases. This article summarizes the present status of the project.

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)0.005
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 score0.997
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0040.005
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0470.044

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 head0.054
GPT teacher head0.323
Teacher spread0.269 · 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

Citations325
Published2016
Admission routes2
Has abstractyes

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