{"id":"W3016434062","doi":"10.1109/jlt.2020.2986479","title":"Non-Classical Semiconductor Photon Sources Enhancing the Performance of Classical Target Detection Systems","year":2020,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Defence Research and Development Canada","keywords":"Photon; Noise (video); Intensity (physics); Signal-to-noise ratio (imaging); Detection theory; Semiconductor; Quantum optics; Photon counting; Quantum; Quantum channel","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007634338,0.0003350708,0.000276794,0.0003230417,0.0002359648,0.0005810977,0.0005712743,0.0004149288,0.001612462],"category_scores_gemma":[0.001085075,0.0001379937,0.0001131254,0.0003744205,0.0007496864,0.0007534638,0.0007954839,0.0004394016,0.0003191321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004951998,"about_ca_system_score_gemma":0.0003418102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001774442,"about_ca_topic_score_gemma":0.0002800782,"domain_scores_codex":[0.9994757,0.00009201691,0.00001842071,0.00006220116,0.0002733267,0.00007832093],"domain_scores_gemma":[0.998963,0.0004574386,0.0002591505,0.0001082517,0.0001432796,0.00006895463],"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":[0.0003363417,0.000112091,0.001525269,0.0001399155,0.000027631,0.0001928396,0.0001278317,0.009083791,0.9545054,0.01877292,0.0001894419,0.01498645],"study_design_scores_gemma":[0.00001961217,0.0005286782,0.001516759,0.00001041023,0.00002102775,0.0001528686,0.00002569812,0.08439756,0.9110429,0.001487892,0.0007674358,0.00002902353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9452675,0.0003134323,0.04856441,0.0001227632,0.00002214561,0.0000361648,0.00003383956,0.0001833121,0.005456363],"genre_scores_gemma":[0.9912039,0.00009971855,0.008159488,0.00002698615,0.00001142559,0.00001062753,0.00001233015,0.000009453284,0.0004660871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001612462,"threshold_uncertainty_score":0.00539422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003812448610317,"score_gpt":0.210204724992476,"score_spread":0.2001666005063729,"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."}}