Figure data for "High Parametric Efficiency in Laser Cavity-Soliton Microcombs"
Bibliographic record
Abstract
Figure data for: <strong>High Parametric Efficiency in Laser Cavity-Soliton Microcombs</strong> Antonio Cutrona<sup>1,2</sup>, Maxwell Rowley<sup>2</sup>, Debayan Das<sup>1,2</sup> , Luana Olivieri <sup>1,2</sup>, Luke Peters <sup>1,2</sup>, Sai T. Chu<sup>3</sup>, Brent E. Little<sup>4</sup>, Roberto Morandotti<sup>5</sup>, David J. Moss<sup>6</sup>, Juan Sebastian Totero Gongora<sup>1,2</sup>, Marco Peccianti<sup>1,2</sup>, and Alessia Pasquazi<sup>1,2,*</sup> <sup>1</sup> Emergent Photonics Research Centre, Dept. of Physics, Loughborough University, Loughborough, LE11 3TU, England, UK <sup>2</sup>Emergent Photonics Lab (Epic), Department of Physics and Astronomy, University of Sussex, Brighton, BN1 9QH, UK <sup>3</sup> Department of Physics, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China SAR <sup>4</sup> State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, CAS, Xi’an, China <sup>5</sup> INRS-EMT, 1650 Boulevard Lionel-Boulet, Varennes, J3X 1S2, Québec, Canada <sup>6</sup> Optical Sciences Centre, Swinburne University of Technology, Hawthorn, VIC 3122, Victoria, Australia *a.pasquazi@lboro.ac.uk <strong>Acknowledgements </strong> EPSRC UKRI (EP/S001018/1). ERC (851758 TELSCOMBE). DSTL (DSTLX1000142078). INNOVATE UK (IUK project 77087 and 10004412). Leverhulme Trust (ECF-2020-537). ERC (TIMING 725046). NSERC (Alliance and Discovery Grants Schemes), Canada Research Chair and MESI PSR-SIIRI Initiatives in Quebec. Strategic Priority Research Program of the Chinese Academy of Sciences (grant number XDB24030300). <br>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.412 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".