{"id":"W3086234072","doi":"10.1002/lpor.202000122","title":"Single‐Shot Ultraviolet Compressed Ultrafast Photography","year":2020,"lang":"en","type":"article","venue":"Laser & Photonics Review","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Axis Photonique (Canada); Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; National Science Foundation","keywords":"Digital micromirror device; Photography; Computer science; Ultrashort pulse; Streak; Optics; Computer vision; Shot (pellet); Image quality; Encoding (memory); Pixel; Photocathode; Image resolution; Artificial intelligence; Computational photography; Encoder; Iterative reconstruction; Computer graphics (images); Laser; Physics; Image processing; Materials science; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007378484,0.0003217108,0.0006083386,0.00002641155,0.00009457367,0.00004825243,0.0004452284,0.00006040753,0.0005801333],"category_scores_gemma":[0.00005232288,0.0002832593,0.0003007966,0.0005830901,0.0001524515,0.000111377,0.0001055769,0.0004202866,0.0001958034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001692797,"about_ca_system_score_gemma":0.0000241021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001609821,"about_ca_topic_score_gemma":0.000001131142,"domain_scores_codex":[0.998385,0.00004789437,0.0004299562,0.0004844754,0.0002279147,0.0004247566],"domain_scores_gemma":[0.9989148,0.0001047447,0.0001728868,0.0005254475,0.00008608408,0.0001960126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002346658,0.00320189,0.008107873,0.007892146,0.001506371,0.0001701521,0.0006235357,0.001182602,0.5900771,0.06149679,0.04107656,0.2844303],"study_design_scores_gemma":[0.0007118561,0.0001958962,0.00006471311,0.002186519,0.0002449095,0.00000390746,0.00008142549,0.0008401524,0.3666453,0.003242771,0.6249258,0.000856796],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4088693,0.1369045,0.05160947,0.03986994,0.001452971,0.0134667,0.001753222,0.007755592,0.3383182],"genre_scores_gemma":[0.9805749,0.004704908,0.008376089,0.005977089,0.00007680748,0.00006375372,0.0001280726,0.00006347989,0.00003487671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5838492,"threshold_uncertainty_score":0.999962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388019674004112,"score_gpt":0.2708771581521214,"score_spread":0.2320751907517102,"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."}}