{"id":"W7133028634","doi":"","title":"Sutura y anudado laparoscópico asistido por robot: estudiocomparativo de la curva de aprendizaje","year":2014,"lang":"en","type":"article","venue":"TSpace","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Knot tying; Learning curve; Laparoscopic surgery; Tying; Scale (ratio)","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":[0.001939188,0.0002301411,0.0002433936,0.0009081629,0.0001525631,0.000334787,0.0002407686,0.000397518,0.001488682],"category_scores_gemma":[0.01586569,0.0001830506,0.000337929,0.0003735537,0.000370221,0.000624845,0.000505942,0.0002967363,0.0002609409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001694946,"about_ca_system_score_gemma":0.0002634547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00073623,"about_ca_topic_score_gemma":0.0006423955,"domain_scores_codex":[0.999201,0.0002841175,0.00005610201,0.0001067652,0.0002605481,0.00009156546],"domain_scores_gemma":[0.9834246,0.009951325,0.003450548,0.0006071314,0.001639038,0.0009273289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00332745,0.001308459,0.9399565,0.0001140082,0.00009220959,0.0002857415,0.001312583,0.0007632312,0.004646465,0.00005550605,0.0001025,0.04803535],"study_design_scores_gemma":[0.00005591009,0.006766784,0.9878913,0.00002465645,0.00003847797,0.0007066026,0.0006627566,0.001514338,0.001756439,0.00006201799,0.0004983951,0.00002228451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993389,0.00008146756,0.0002601203,0.000006421697,0.000002278336,0.00001318383,0.00001755464,0.000004030528,0.0002760276],"genre_scores_gemma":[0.9988647,0.000162943,0.0003906077,0.000009098213,0.000006268604,0.00001872425,0.0000655348,0.000004316232,0.0004777962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001939188,"threshold_uncertainty_score":0.01025558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988624090666846,"score_gpt":0.3817075693376685,"score_spread":0.351821328431,"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."}}