{"id":"W2889947886","doi":"10.1097/gox.0000000000001871","title":"A High Fidelity Cleft Lip Simulator","year":2018,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery Global Open","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Computer science; Simulation; High fidelity; Fidelity; Computer graphics (images); Engineering; Electrical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009972636,0.0004556845,0.0001998953,0.0002997743,0.0002078363,0.0004174741,0.001077995,0.0005596858,0.009144559],"category_scores_gemma":[0.00203832,0.0002576863,0.0004518285,0.0001310923,0.0003449995,0.0004211839,0.001290156,0.0004851029,0.001331344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295533,"about_ca_system_score_gemma":0.001117686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380866,"about_ca_topic_score_gemma":0.001095292,"domain_scores_codex":[0.9996563,0.00008821051,0.00003922662,0.0000330229,0.0001495836,0.00003369278],"domain_scores_gemma":[0.9988888,0.00048974,0.00006261547,0.000159437,0.0002057612,0.0001936298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002265588,0.003673718,0.03806727,0.00149131,0.0001414088,0.003164603,0.002589619,0.259126,0.3846174,0.005624976,0.01070039,0.2885377],"study_design_scores_gemma":[0.001164659,0.009274777,0.03027734,0.0003889451,0.0002530343,0.008101054,0.00086975,0.6651197,0.1715769,0.003921736,0.1087593,0.0002927433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6634324,0.000230123,0.3153412,0.0003681495,0.0001683318,0.002344143,0.001676952,0.002705082,0.01373364],"genre_scores_gemma":[0.7883514,0.0003373277,0.1997501,0.0001012693,0.00002391034,0.00146542,0.001593065,0.0001672812,0.008210246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009144559,"threshold_uncertainty_score":0.03059155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04179315196339264,"score_gpt":0.3202848117543712,"score_spread":0.2784916597909786,"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."}}