{"id":"W3160929282","doi":"10.21203/rs.3.rs-536844/v1","title":"Microwave and radio frequency fractional differentiation with a 49GHz Kerr soliton crystal microcomb source","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Fiber Laser Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Chinese Academy of Sciences; Australian Research Council; 1000 Talents Sichuan Program; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Differentiator; Bandwidth (computing); Physics; Reconfigurability; Radio frequency; Microwave; Frequency comb; Computer science; Optics; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002018098,0.0001854634,0.0001734469,0.0002029974,0.0001705376,0.0002490475,0.0002492119,0.0002698841,0.001122259],"category_scores_gemma":[0.0003537285,0.0001026552,0.0001038232,0.0001940203,0.0003546402,0.0002456045,0.0002321621,0.0002670942,0.0002519404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003512939,"about_ca_system_score_gemma":0.0001709658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003082017,"about_ca_topic_score_gemma":0.0003727709,"domain_scores_codex":[0.9998198,0.00001821161,0.000006650317,0.00003412275,0.0000973902,0.00002387014],"domain_scores_gemma":[0.999756,0.00007535449,0.00008271361,0.00003155601,0.00003015814,0.00002421985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008766729,0.00003086521,0.0003209597,0.00002013181,0.000003496683,0.00006830278,0.00003660834,0.0006271041,0.9926518,0.001486167,0.00007700418,0.004589968],"study_design_scores_gemma":[0.00002155703,0.0001852259,0.001172801,0.000003258514,0.000005134269,0.0001481827,0.00001090016,0.0171264,0.9791256,0.0002060986,0.001983656,0.00001108678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799218,0.0002965627,0.01583248,0.0001584861,0.00003635772,0.00002432346,0.00006503415,0.0001876825,0.003477356],"genre_scores_gemma":[0.9786832,0.00006961697,0.01946077,0.0000304577,0.0000132146,0.00001506947,0.00003208132,0.00002283161,0.001672695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001122259,"threshold_uncertainty_score":0.003754377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02203293055256821,"score_gpt":0.3141074591670344,"score_spread":0.2920745286144662,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}