{"id":"W4405880965","doi":"10.1093/icvts/ivae227","title":"Examining the learning curves in robotic cardiac surgery wet lab simulation training","year":2024,"lang":"en","type":"article","venue":"Interdisciplinary CardioVascular and Thoracic Surgery","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Aalborg Universitetshospital; Aalborg Universitet","keywords":"Training (meteorology); Learning curve; Simulation training; Computer science; Simulation; Artificial intelligence; Operating system; Geography; Meteorology","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":[0.005052907,0.0004218955,0.0002842463,0.001445632,0.0002602038,0.00107505,0.0006700883,0.000423289,0.00286757],"category_scores_gemma":[0.03482619,0.0002040041,0.0005529889,0.0004659742,0.0005245263,0.00122471,0.001670561,0.000622372,0.0006896736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007526083,"about_ca_system_score_gemma":0.001000315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008539448,"about_ca_topic_score_gemma":0.0009245287,"domain_scores_codex":[0.997516,0.0006580987,0.0002216632,0.0002791313,0.001002813,0.0003222666],"domain_scores_gemma":[0.9770547,0.008897732,0.006122776,0.0009956346,0.003751844,0.003177279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001660532,0.002807492,0.8829672,0.0002134606,0.0001430214,0.0001964148,0.003249844,0.006402292,0.002596112,0.0003331791,0.0007943423,0.09863603],"study_design_scores_gemma":[0.00005077825,0.007825184,0.9787093,0.00009978173,0.00002815501,0.0003227741,0.001462775,0.006777255,0.002830929,0.0003819776,0.001462374,0.0000485436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997508,0.00007235125,0.0009507055,0.00003034476,0.000005403343,0.00007243928,0.00006081278,0.00001423223,0.001285755],"genre_scores_gemma":[0.9985103,0.00007502233,0.0007295074,0.0000175344,0.000004504955,0.00009185162,0.0001311181,0.000007450855,0.0004327387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005052907,"threshold_uncertainty_score":0.02672267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08610495465770748,"score_gpt":0.3482005500713976,"score_spread":0.2620955954136901,"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."}}