{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001203953,0.0002516933,0.0002489898,0.00048135,0.0002078825,0.0002952224,0.0005076354,0.0003843813,0.002711564],"category_scores_gemma":[0.0002091103,0.0001225954,0.0001384962,0.0003605751,0.0003241526,0.0005712844,0.0003777675,0.0004006577,0.0002710476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003998446,"about_ca_system_score_gemma":0.0003011192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000914645,"about_ca_topic_score_gemma":0.001344073,"domain_scores_codex":[0.9998691,0.000006845941,0.000003748048,0.00002297609,0.00007982582,0.0000174965],"domain_scores_gemma":[0.9998323,0.00003180208,0.00003816821,0.00002442854,0.00005052128,0.00002279284],"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":[0.000136951,0.00004652451,0.0003515676,0.0002160954,0.00000995704,0.0002742794,0.00007362675,0.000706334,0.9595051,0.001616822,0.00128213,0.03578052],"study_design_scores_gemma":[0.00001598299,0.0001458255,0.002734428,0.00002025524,0.00001164715,0.0008007235,0.00006522783,0.01336928,0.9758235,0.0003981869,0.006590084,0.00002497646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8934761,0.004326026,0.07756297,0.0005340386,0.0003309003,0.0001285721,0.0009803652,0.0008196929,0.02184124],"genre_scores_gemma":[0.9325289,0.001504036,0.05702769,0.000107144,0.00007021389,0.00005186751,0.0004804879,0.0000475115,0.008182188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002711564,"threshold_uncertainty_score":0.009071112,"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."}}