{"id":"W1995258416","doi":"10.1007/s00464-014-3442-9","title":"Development of force-based metrics for skills assessment in minimally invasive surgery","year":2014,"lang":"en","type":"article","venue":"Surgical Endoscopy","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Lawson Health Research Institute","funders":"","keywords":"Haptic technology; Task (project management); Measure (data warehouse); Position (finance); Computer science; Set (abstract data type); Task force; Invasive surgery; Artificial intelligence; Simulation; Medical physics; Machine learning; Data mining; Human–computer interaction; Medicine; Surgery; Engineering; Systems engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00111609,0.0001553275,0.0006019631,0.0003497201,0.0000373726,0.000009426326,0.00006205842,0.0001100768,0.0002376728],"category_scores_gemma":[0.001100456,0.0001280561,0.0002009167,0.0005056769,0.00004994288,0.00003673022,0.00002053541,0.0001408761,0.000006472562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001036919,"about_ca_system_score_gemma":0.0005704206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003796037,"about_ca_topic_score_gemma":0.0000107087,"domain_scores_codex":[0.9982606,0.00007425917,0.0006923262,0.0002648829,0.0003936511,0.0003142538],"domain_scores_gemma":[0.9934013,0.005970364,0.0001538846,0.0001543558,0.0001371561,0.0001828837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006959126,0.004602592,0.7445565,0.001784622,0.0003679699,0.0002582375,0.001221198,0.001798785,0.002733603,0.01021854,0.0001640079,0.2253348],"study_design_scores_gemma":[0.204567,0.001474456,0.3529329,0.002311662,0.0002397253,0.00001979899,0.0006494515,0.03836174,0.1777649,0.001357016,0.2188466,0.001474695],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902259,0.00003518975,0.002940178,0.0002197434,0.0001315806,0.0004310858,0.00000511524,0.00003688392,0.005974374],"genre_scores_gemma":[0.9648858,0.000006815497,0.03452594,0.0002448195,0.00005182489,0.00006927912,0.00008910876,0.00001937267,0.0001070133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3916236,"threshold_uncertainty_score":0.5221975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03835054601891581,"score_gpt":0.3376179278010285,"score_spread":0.2992673817821127,"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."}}