{"id":"W2527348349","doi":"10.1038/lsa.2017.13","title":"Digital spiral object identification using random light","year":2017,"lang":"en","type":"article","venue":"Light Science & Applications","topic":"Orbital Angular Momentum in Optics","field":"Physics and Astronomy","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Key Research and Development Program of China; China Scholarship Council; Tsinghua University; National Natural Science Foundation of China","keywords":"Physics; Angular momentum; Orbital angular momentum multiplexing; Photon; Optics; Quantum imaging; Noise (video); Orbital angular momentum of light; Computer science; Total angular momentum quantum number; Quantum; Artificial intelligence; Quantum information; Quantum mechanics; Quantum network","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":[0.0003721079,0.0003175209,0.0003294114,0.0006485275,0.0002589298,0.0006017559,0.0004642451,0.000394257,0.0013103],"category_scores_gemma":[0.001837573,0.0002335096,0.0001608328,0.0005589079,0.0009273434,0.001228733,0.001156209,0.0004042283,0.0003170805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004140855,"about_ca_system_score_gemma":0.0003600863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002329221,"about_ca_topic_score_gemma":0.0003258643,"domain_scores_codex":[0.9995558,0.00009451444,0.00001866375,0.0001065038,0.0001757942,0.00004872704],"domain_scores_gemma":[0.9991378,0.0002357322,0.0002610348,0.0002248902,0.00008251793,0.00005798148],"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":[0.001000925,0.0001546891,0.003508764,0.0002074668,0.00004220117,0.0005438784,0.0004807018,0.04825732,0.4955854,0.1382848,0.001374309,0.3105596],"study_design_scores_gemma":[0.00005645196,0.0003358163,0.001700326,0.00004877786,0.00002202183,0.0009148768,0.0001442092,0.5931714,0.358055,0.03994281,0.005530436,0.00007792213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3205083,0.0002627914,0.6701924,0.0002955668,0.0000596435,0.00009068357,0.000112679,0.0006195461,0.00785848],"genre_scores_gemma":[0.8213626,0.0001777403,0.1760083,0.00007463499,0.00002115923,0.00005563141,0.00008869753,0.00003224401,0.002179034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0013103,"threshold_uncertainty_score":0.004383326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322039086581739,"score_gpt":0.2816195762372125,"score_spread":0.2683991853713951,"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."}}