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Record W2964084254 · doi:10.1088/1361-6455/ab26e0

Roadmap on photonic, electronic and atomic collision physics: II. Electron and antimatter interactions

2019· article· en· W2964084254 on OpenAlexaff
S. Schippers, Emma Sokell, F. Aumayr, H. R. Sadeghpour, Kiyoshi Ueda, Igor Bray, Klaus Bartschat, Andrew James Murray, Jonathan Tennyson, Alexander Dorn, Masakazu Yamazaki, Masahiko Takahashi, N. J. Mason, A. Wolf, Léon Sanche, Martin Centurion, Y. Yamazaki, G. Laricchia, C. M. Surko, James P. Sullivan, G. F. Gribakin, D. W. Savin, Yuri Ralchenko, R. Hoekstra, G. O’Sullivan

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversité de Sherbrooke
FundersBasic Energy SciencesDivision of Astronomical SciencesScience Foundation IrelandEngineering and Physical Sciences Research CouncilScience Mission DirectorateDeutsche ForschungsgemeinschaftNational Science FoundationU.S. Department of EnergyCALIPSOplusAstrophysics DivisionJapan Society for the Promotion of ScienceOffice of ScienceMinistry of Education, Culture, Sports, Science and TechnologyNational Aeronautics and Space Administration
KeywordsPhysicsAntimatterCollisionField (mathematics)ElectronPhotonicsNuclear physicsPositronQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract We publish three Roadmaps on photonic, electronic and atomic collision physics in order to celebrate the 60th anniversary of the ICPEAC conference. In Roadmap II we focus on electron and antimatter interactions. Modern theoretical and experimental approaches provide detailed insight into the many body quantum dynamics of leptonic collisions with targets of varying complexity ranging from neutral and charged atoms to large biomolecules and clusters. These developments have been driven by technological progress and by the needs of adjacent areas of science such as astrophysics, plasma physics and radiation biophysics. This Roadmap aims at looking back along the road, explaining the evolution of the field, and looking forward, collecting contributions from eighteen leading groups from the field.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0060.007
Open science0.0020.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0300.011

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 head0.004
GPT teacher head0.237
Teacher spread0.234 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2019
Admission routes1
Has abstractyes

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