{"id":"W3022638146","doi":"10.1103/physreva.101.053808","title":"Multidimensional quantum-enhanced target detection via spectrotemporal-correlation measurements","year":2020,"lang":"en","type":"article","venue":"Physical review. A/Physical review, A","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; National Research Council Canada","funders":"Defence Research and Development Canada","keywords":"Photon; Quantum; Noise (video); Physics; Quantum correlation; Parametric statistics; Quantum sensor; Computer science; Quantum network; Quantum mechanics; Quantum information; Mathematics; Quantum discord; Quantum entanglement; Artificial intelligence; Statistics","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":[0.000533509,0.0002452719,0.0003189408,0.0003087605,0.0001918871,0.0005726382,0.0006254799,0.0005240684,0.0008516581],"category_scores_gemma":[0.0008844214,0.000179733,0.0002158047,0.000422052,0.0007179849,0.001133799,0.0007823525,0.0004827098,0.0002039681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003772065,"about_ca_system_score_gemma":0.0002473524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001871193,"about_ca_topic_score_gemma":0.0003252451,"domain_scores_codex":[0.9995149,0.0001362958,0.00001460258,0.00009996595,0.0001959072,0.00003830316],"domain_scores_gemma":[0.9994627,0.0002353714,0.0001446835,0.00008433512,0.00004758617,0.00002543837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002763078,0.0002195022,0.002234808,0.00025417,0.00005383542,0.0004322899,0.0001934936,0.01364637,0.8912563,0.06031127,0.0002766316,0.03084495],"study_design_scores_gemma":[0.00003640658,0.0005318997,0.002847953,0.00002493129,0.00003187569,0.0008660253,0.00007197218,0.2919861,0.6930811,0.00752181,0.00292598,0.00007385891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6472239,0.001713178,0.3433679,0.0003481756,0.0000956896,0.0001112628,0.0001450214,0.0002121056,0.006782793],"genre_scores_gemma":[0.9280872,0.0005861871,0.07010217,0.0000854508,0.00002436425,0.00003631243,0.00004558801,0.00001110037,0.001021618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008516581,"threshold_uncertainty_score":0.002849102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02783167363579074,"score_gpt":0.3209722949989183,"score_spread":0.2931406213631276,"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."}}