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Record W3000326939 · doi:10.1088/1361-6455/ab69a8

Roadmap on quantum light spectroscopy

2020· article· en· W3000326939 on OpenAlexaff
Shaul Mukamel, Matthias Freyberger, Wolfgang P. Schleich, Marco Bellini, Alessandro Zavatta, Gerd Leuchs, Christine Silberhorn, Robert W. Boyd, L. L. Sánchez-Soto, André Stefanov, Marco Barbieri, Anna V. Paterova, Leonid A. Krivitsky, S. Shwartz, Kenji Tamasaku, Konstantin E. Dorfman, Frank Schlawin, Vahid Sandoghdar, Michael G. Raymer, Andrew H. Marcus, Oleg Varnavski, Theodore Goodson, Zhi‐Yuan Zhou, Bao‐Sen Shi, Shahaf Asban, Marlan O. Scully, G. S. Agarwal, Tao Peng, Alexei V. Sokolov, Zhedong Zhang, M. Suhail Zubairy, Ivan A. Vartanyants, Elena del Valle, Fabrice P. Laussy

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2020
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsMax Planck - University of Ottawa Centre for Extreme and Quantum Photonics
FundersDivision of ChemistryOffice of Naval ResearchOverseas Expertise Introduction Project for Discipline InnovationCollege of Agriculture and Life Sciences, Texas A and M UniversityHagler Institute for Advanced Study, Texas A&M UniversityOffice of ScienceBasic Energy SciencesKing Abdulaziz City for Science and TechnologyMax-Planck-GesellschaftNational Natural Science Foundation of ChinaU.S. Department of EnergyEuropean CommissionRussian Science FoundationAir Force Office of Scientific ResearchTexas A and M UniversityTexas AgriLife ResearchJohn Templeton FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungChemical Sciences, Geosciences, and Biosciences DivisionNational Science Foundation
KeywordsSpectroscopyPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.601

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 communication0.0000.001
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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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 designTheoretical or conceptual
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

Citations174
Published2020
Admission routes1
Has abstractyes

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