{"id":"W4221090364","doi":"10.1002/rcs.2393","title":"Quality of laparoscopic camera navigation in robot‐assisted versus conventional laparoscopic surgery for rectal cancer: An analysis of surgical videos through a video processing computer software","year":2022,"lang":"en","type":"article","venue":"International Journal of Medical Robotics and Computer Assisted Surgery","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Research Foundation of Korea","keywords":"Laparoscopic surgery; Medicine; Computer science; Artificial intelligence; Computer vision; Robotic surgery; Software; Surgery; Laparoscopy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002648046,0.0001753979,0.0002268733,0.001381407,0.0001313881,0.0006000532,0.0002067386,0.0002094826,0.001046261],"category_scores_gemma":[0.01158084,0.0001288117,0.0003392507,0.0009138554,0.0002513545,0.0003452624,0.0003748787,0.0001414362,0.0001153814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003663618,"about_ca_system_score_gemma":0.0003418439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00154724,"about_ca_topic_score_gemma":0.002057738,"domain_scores_codex":[0.9982664,0.0004240691,0.0003353301,0.000282036,0.0005961025,0.00009605754],"domain_scores_gemma":[0.9910275,0.003184682,0.003546764,0.0003392533,0.001617816,0.0002839943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002496888,0.00006976035,0.9028127,0.0004241633,0.0003116889,0.0001869474,0.0004858004,0.0008304454,0.006934222,0.00008635392,0.0004275239,0.08493347],"study_design_scores_gemma":[0.00002256152,0.000506272,0.9926209,0.00005258167,0.0001352668,0.0007074719,0.0002227709,0.002706375,0.002351089,0.00005715443,0.0005968353,0.00002052738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906239,0.001158205,0.006720866,0.00003532053,0.0000192251,0.00008949437,0.0006262114,0.00006496074,0.0006617309],"genre_scores_gemma":[0.9958917,0.0002422266,0.00318724,0.00001127946,0.00001034646,0.00004301763,0.0004512951,0.00001552096,0.0001474022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002648046,"threshold_uncertainty_score":0.01400435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08202129654330659,"score_gpt":0.3911705531390653,"score_spread":0.3091492565957588,"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."}}