{"id":"W4362588382","doi":"10.1097/gox.0000000000004898","title":"Utilization of a 3D Printed Simulation Training Model to Improve Microsurgical Training","year":2023,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery Global Open","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bespoke; Training (meteorology); Medicine; Curriculum; Medical physics; Microsurgery; Limiting; Medical education; Physical therapy; Surgery; Psychology; Engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000955117,0.0005512136,0.0002582043,0.0005900479,0.000207507,0.0005567812,0.0006474226,0.0003474695,0.004059237],"category_scores_gemma":[0.001626341,0.0002127952,0.0005639416,0.0002174851,0.0002993009,0.0003614832,0.0009269676,0.0003834387,0.0006171992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004445488,"about_ca_system_score_gemma":0.001301195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002142383,"about_ca_topic_score_gemma":0.003939858,"domain_scores_codex":[0.9992471,0.0001736236,0.00004883847,0.00008202228,0.0003601926,0.00008819903],"domain_scores_gemma":[0.999311,0.0001961583,0.0001504717,0.000099844,0.0001159151,0.000126688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003048072,0.009394774,0.07329915,0.001121064,0.0001703602,0.001239456,0.001778838,0.07975432,0.2934038,0.001423364,0.003782755,0.531584],"study_design_scores_gemma":[0.001116446,0.0757153,0.3226421,0.001098313,0.0007915502,0.006475932,0.001597313,0.2602303,0.2605823,0.00162441,0.06757302,0.0005530862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466811,0.000328535,0.04595896,0.000274512,0.0001048056,0.0006428669,0.0002271962,0.0004502132,0.005331737],"genre_scores_gemma":[0.954574,0.0004647323,0.04157756,0.00006819436,0.00001713964,0.0004700778,0.0002505085,0.00003884312,0.002538915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004059237,"threshold_uncertainty_score":0.01357949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.147545215231401,"score_gpt":0.3685099988975798,"score_spread":0.2209647836661788,"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."}}