{"id":"W3017511415","doi":"10.1364/oe.402873","title":"100,000 frames-per-second compressive imaging with a conventional rolling-shutter camera by random point-spread-function engineering","year":2020,"lang":"en","type":"article","venue":"Optics Express","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science, Technology and Space; H2020 Excellent Science; Azrieli Foundation; Israel Science Foundation; Human Frontier Science Program","keywords":"Frame rate; Diffuser (optics); Compressed sensing; Iterative reconstruction; Frame (networking); Sampling (signal processing); Pupil; Coded aperture","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006162022,0.0003720347,0.0003882446,0.00008224029,0.0000885585,0.0001773978,0.000241857,0.0001077069,0.0003013008],"category_scores_gemma":[0.00001867314,0.0003678024,0.0001077612,0.0001241781,0.00006009555,0.0003168717,0.00006743045,0.0004514589,0.0000276725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003966937,"about_ca_system_score_gemma":0.00001304896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001197437,"about_ca_topic_score_gemma":8.649654e-7,"domain_scores_codex":[0.9985796,0.00002846088,0.000323974,0.0003800568,0.000288108,0.0003997795],"domain_scores_gemma":[0.9991997,0.0001168832,0.00007966207,0.0002984164,0.0001173301,0.0001880134],"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":[0.0005937328,0.0001008391,0.0007316065,0.0002444303,0.0006334054,0.0001382947,0.001217576,0.2926666,0.6256523,0.0006088214,0.07595982,0.001452593],"study_design_scores_gemma":[0.002757832,0.0001285058,0.0001006703,0.0003164087,0.0001222698,0.0000399833,0.0001179626,0.7746568,0.1840256,0.0001408212,0.03678292,0.0008102357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1200284,0.001271169,0.8730016,0.0002773068,0.0003761967,0.0004590769,0.0001096837,0.001542555,0.002934051],"genre_scores_gemma":[0.9858296,0.00003751344,0.01294842,0.0005698007,0.00026794,0.00005812334,0.00008733685,0.0001204588,0.00008084583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8658012,"threshold_uncertainty_score":0.9998774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007537924490767427,"score_gpt":0.1947909279820104,"score_spread":0.187253003491243,"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."}}