{"id":"W3017164893","doi":"10.1364/translational.2020.jth2a.13","title":"Real Time & 3D Photoacoustic Remote Sensing","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Photoacoustic imaging in biomedicine; Computer science; Frame rate; Frame (networking); Operator (biology); Real-time computing; Computer vision; Optics; Telecommunications; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005356082,0.0008975659,0.0009586878,0.0002388157,0.0003537821,0.0003099332,0.0007278849,0.0006438731,0.0009091818],"category_scores_gemma":[0.000489751,0.0009709627,0.0003403069,0.001199612,0.0007911487,0.0002911136,0.000127634,0.00110837,0.0008033835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001813098,"about_ca_system_score_gemma":0.0005901225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005897917,"about_ca_topic_score_gemma":0.00000972593,"domain_scores_codex":[0.9949932,0.000108885,0.001315178,0.001095715,0.001161128,0.001325966],"domain_scores_gemma":[0.9968876,0.0009033494,0.0002136587,0.0006567779,0.0002578693,0.001080713],"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":[0.0001222833,0.00007048383,0.00001788348,0.0004961398,0.000334336,0.0002175609,0.0008052083,0.003630377,0.9665969,0.00004700312,0.02442505,0.003236789],"study_design_scores_gemma":[0.001909086,0.00009052904,0.00005533304,0.0003134666,0.0002304146,0.0001673825,0.00007181762,0.8977358,0.0154218,0.0002157535,0.08261911,0.001169456],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2811123,0.004399614,0.6649265,0.0199997,0.00717965,0.003384541,0.004954621,0.00469596,0.009347136],"genre_scores_gemma":[0.3872267,0.003321489,0.5919322,0.008098656,0.002508079,0.00002117605,0.004395084,0.000942047,0.001554545],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9511751,"threshold_uncertainty_score":0.9999746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163312268472825,"score_gpt":0.246438152502531,"score_spread":0.2348050298178027,"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."}}