{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004973541,0.0002547753,0.0007258024,0.00007855414,0.0001888239,0.0001172171,0.0001857557,0.0001453052,0.005280272],"category_scores_gemma":[0.002958987,0.0002199882,0.0001928624,0.0005233417,0.0004248242,0.0002980167,0.0002011516,0.0001778603,0.0006943819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002081266,"about_ca_system_score_gemma":0.0003940628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002861363,"about_ca_topic_score_gemma":0.00005187833,"domain_scores_codex":[0.9979549,0.0001192264,0.0005792351,0.0005519867,0.0003360886,0.0004585832],"domain_scores_gemma":[0.9963281,0.002313392,0.0001899737,0.0003222656,0.0004075375,0.0004387061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002159648,0.0001776685,0.8745349,0.00002750198,0.0003323907,0.0001185095,0.00005091866,0.00007919551,0.00001778034,0.005614302,0.00131913,0.1155681],"study_design_scores_gemma":[0.004103619,0.0002237988,0.9665641,0.0003138282,0.0001583125,0.0003053145,0.0002202247,0.003363405,0.0001526808,0.005536003,0.01856885,0.0004898663],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644675,0.00001387427,0.0007916075,0.0001505145,0.002164234,0.0004520997,0.0001140828,0.0001147919,0.03173131],"genre_scores_gemma":[0.9969494,0.000003068749,0.001674313,0.0007017228,0.0004981662,0.00001331845,0.00004146223,0.00001783696,0.0001006583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1150782,"threshold_uncertainty_score":0.995629,"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."}}