{"id":"W4386874115","doi":"10.1038/s42005-023-01383-x","title":"Tera-sample-per-second arbitrary waveform generation in a synthetic dimension","year":2023,"lang":"en","type":"article","venue":"Communications Physics","topic":"Advanced Fiber Laser Technologies","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Key Research and Development Program of China","keywords":"Photonics; Tera-; Dimension (graph theory); Waveform; Ranging; Computer science; Algorithm; Mathematics; Optics; Physics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002796151,0.0001450537,0.0001273567,0.0001860989,0.0001261119,0.0004914192,0.000302627,0.0002924683,0.001537626],"category_scores_gemma":[0.000593535,0.0001083707,0.0001019255,0.0001907077,0.0005408259,0.0005220275,0.0003980485,0.0004124852,0.0002245735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002159257,"about_ca_system_score_gemma":0.0001326506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009271102,"about_ca_topic_score_gemma":0.00009435125,"domain_scores_codex":[0.9998715,0.00002465689,0.000005163309,0.00002515054,0.00005451376,0.00001909158],"domain_scores_gemma":[0.9996729,0.0001036022,0.00005948899,0.00007429249,0.00005349291,0.0000362054],"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":[0.0002792107,0.000085922,0.001184383,0.00008355721,0.00001696359,0.0001759176,0.0001812261,0.007699729,0.8758744,0.07263871,0.001117802,0.04066228],"study_design_scores_gemma":[0.00007310549,0.0004767168,0.001601577,0.00001654208,0.00001064396,0.0002637078,0.00008928305,0.1806832,0.7802848,0.01111691,0.02533007,0.00005350537],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8179305,0.0004959818,0.1603262,0.0006091076,0.0003542909,0.00007799552,0.0002455566,0.0007372741,0.01922308],"genre_scores_gemma":[0.9676558,0.000084826,0.03029083,0.00006396667,0.00002158032,0.00002416089,0.00005732989,0.00003002223,0.001771475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001537626,"threshold_uncertainty_score":0.005143881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04748110376885126,"score_gpt":0.2954885580719001,"score_spread":0.2480074543030488,"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."}}