{"id":"W2412244584","doi":"10.1364/optica.3.001148","title":"Far-field linear optical superresolution via heterodyne detection in a higher-order local oscillator mode","year":2016,"lang":"en","type":"article","venue":"Optica","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Heterodyne (poetry); Superresolution; Local oscillator; Heterodyne detection; Optics; Mode (computer interface); Physics; Computer science; Laser; Acoustics; Phase noise; Artificial intelligence; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000841455,0.0001602517,0.0001359395,0.00005083974,0.00004343623,0.000009131052,0.0001383091,0.0002820816,0.00003692296],"category_scores_gemma":[0.0001031888,0.0001270859,0.00005276555,0.0001027419,0.0001445156,0.0000113245,0.0001079133,0.0001141568,0.00002888885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006571149,"about_ca_system_score_gemma":0.00002936565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002819845,"about_ca_topic_score_gemma":0.0001351223,"domain_scores_codex":[0.9989206,0.00003191582,0.0002069324,0.0004007964,0.0001093088,0.000330408],"domain_scores_gemma":[0.9994698,0.00001932664,0.00003075826,0.0003305137,0.000066759,0.00008285345],"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":[0.0001709818,0.00004677738,0.0002397135,0.000004784772,0.000006461363,0.000003647819,0.000004833697,0.00003501626,0.9740981,0.000120997,0.00005687264,0.02521184],"study_design_scores_gemma":[0.0003975408,0.0004064126,0.0004124297,0.00002630243,0.000005519831,0.0000115245,0.000004874438,0.001058365,0.9885973,0.0001163362,0.008764204,0.0001991981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2136609,0.00008807683,0.7851059,0.0004368406,0.0001223769,0.000153815,0.000004975884,0.00004564264,0.0003814973],"genre_scores_gemma":[0.9538796,0.0001102366,0.04534661,0.0002043617,0.0001371815,0.00003999479,0.00000847194,0.0000270205,0.0002465444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7402187,"threshold_uncertainty_score":0.5182412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008314360972742761,"score_gpt":0.2719737035402853,"score_spread":0.2636593425675425,"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."}}