{"id":"W2017383529","doi":"10.1097/prs.0b013e3181b17bf5","title":"Rhinoplasty: A Hands-On Training Module","year":2009,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Covenant Health; Misericordia Community Hospital","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta; Plastic Surgery Foundation","keywords":"Rhinoplasty; Medicine; Silicone; Computed tomographic; Nose; Learning curve; Margin (machine learning); Orthodontics; Surgery; Biomedical engineering; Medical physics; Computed tomography; Computer science; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005721876,0.001130309,0.0004413059,0.0004095788,0.0003502008,0.0003319925,0.001104912,0.0007637474,0.05572621],"category_scores_gemma":[0.000982349,0.0002770635,0.0006247271,0.0001146846,0.0002693173,0.0004398614,0.001514747,0.0007019005,0.01322341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002745104,"about_ca_system_score_gemma":0.0007711014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002271473,"about_ca_topic_score_gemma":0.0005927947,"domain_scores_codex":[0.9996899,0.00003700578,0.00001586917,0.00006630156,0.0001173568,0.00007358874],"domain_scores_gemma":[0.9994957,0.0001105395,0.00003057548,0.00007375977,0.0000442323,0.0002450934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001475134,0.03139392,0.006931135,0.0005090631,0.00003845702,0.002456487,0.0008017833,0.007651527,0.07291225,0.000803139,0.03366616,0.8413608],"study_design_scores_gemma":[0.004983071,0.09213322,0.1376362,0.001370581,0.0002371025,0.09439287,0.001702882,0.08514495,0.1563029,0.01046001,0.4148839,0.0007522531],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7781314,0.0004691358,0.121972,0.001970301,0.0006017717,0.004681216,0.0009808759,0.005918627,0.08527464],"genre_scores_gemma":[0.6313215,0.001158404,0.2477801,0.00188505,0.0005451122,0.003538664,0.001633816,0.0004154306,0.111722],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05572621,"threshold_uncertainty_score":0.1864227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04988640188076682,"score_gpt":0.2758989507004962,"score_spread":0.2260125488197294,"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."}}