{"id":"W4405483598","doi":"10.1021/acsphotonics.4c01680","title":"Enhanced Detection Rate and High Photon-Number Efficiencies with a Scalable Parallel SNSPD","year":2024,"lang":"en","type":"article","venue":"ACS Photonics","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center of Competence in Research Quantum Science and Technology; Staatssekretariat für Bildung, Forschung und Innovation; H2020 Marie Skłodowska-Curie Actions; National Research Council Canada; Innosuisse - Schweizerische Agentur für Innovationsförderung","keywords":"Photon; Materials science; Optoelectronics; Scalability; Photonics; Photon counting; Optics; Physics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007970228,0.0001798824,0.0001730848,0.00003630307,0.0001389572,0.00013101,0.0000958812,0.00006153485,0.00004716539],"category_scores_gemma":[0.00001372557,0.0001391041,0.00003020581,0.0003093257,0.0001974971,0.0001717457,0.00008340958,0.0002533244,0.00006525928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003646495,"about_ca_system_score_gemma":0.0000366167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001365267,"about_ca_topic_score_gemma":0.00001733446,"domain_scores_codex":[0.9990798,0.00001343708,0.0001319217,0.0003560474,0.0001108864,0.0003078679],"domain_scores_gemma":[0.9995304,0.0001003568,0.00003646632,0.00023894,0.00004638896,0.00004742924],"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":[0.0003307888,0.0002910511,0.0009801061,0.0001819529,0.0004610797,0.00007229097,0.000955919,0.007469666,0.622554,0.1740622,0.0002132666,0.1924277],"study_design_scores_gemma":[0.0004396797,0.0001485922,0.0003273549,0.0001060721,0.00005603611,0.00001050884,0.0002851983,0.02379405,0.9346818,0.03631292,0.003457471,0.0003802601],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9238691,0.0001031033,0.07294498,0.00009087513,0.0001044728,0.0001888339,0.000008008827,0.0003626379,0.002327946],"genre_scores_gemma":[0.985581,0.00003102593,0.01384584,0.00003095376,0.00002369469,0.00003521006,0.000005247387,0.00002752124,0.0004194764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3121278,"threshold_uncertainty_score":0.5672499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005693332737490284,"score_gpt":0.2262098524039334,"score_spread":0.2205165196664431,"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."}}