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Record W2152760285 · doi:10.1088/1367-2630/15/6/065015

Focus on correlation effects in radiation fields

2013· article· en· W2152760285 on OpenAlexaff
D. Bauer, Thomas Brabec, Holger Fehske, Stefan Lochbrunner, R. Redmer

Bibliographic record

VenueNew Journal of Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhysicsFocus (optics)RadiationFemtosecondStatistical physicsCover (algebra)LaserComputational physicsEngineering physicsTheoretical physicsOptics

Abstract

fetched live from OpenAlex

Many processes in nature are governed by the interaction of electro-magnetic radiation with matter. New tools such as femtosecond and free-electron lasers allow one to study the interaction in unprecedented detail with high temporal and spatial resolution. In addition, much work is devoted to the exploration of novel target systems that couple to radiation in an effective and controllable way or that could serve as efficient sources of energetic particles when being subjected to intense laser fields. The interaction between matter and radiation fields as well as their mutual modification via correlations constitutes a rich field of research that is impossible to cover exhaustively. The papers in this focus issue represent a selection that largely reflects the program of the international conference on 'Correlation Effects in Radiation Fields' held in 2011 in Rostock, Germany.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.002

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 head0.007
GPT teacher head0.247
Teacher spread0.241 · 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 designSimulation or modeling
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

Citations5
Published2013
Admission routes1
Has abstractyes

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