{"id":"W2972529026","doi":"10.1097/01.gox.0000583840.01091.16","title":"S15-02 SESSION 15: PLANNING/IMAGING - PART I DEVELOPMENT OF BONE CUTTING INSTRUMENTATION IN THE APPLICATION OF ROBOTIC ASSISTED CRANIOSYNOSTOSIS SURGERY USING THE DA VINCI PLATFORM.","year":2019,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery Global Open","topic":"Craniofacial Disorders and Treatments","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Finite element method; Session (web analytics); Software; Computer science; Visualization; Ultrasonic sensor; Engineering drawing; Simulation; Engineering; Artificial intelligence; Acoustics; Structural 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":[],"consensus_categories":[],"category_scores_codex":[0.0005702952,0.0001899975,0.00038836,0.00006926164,0.0001439535,0.00005154083,0.0002074467,0.00007521108,0.00001513892],"category_scores_gemma":[0.0001989436,0.0001373038,0.0001088599,0.0003290013,0.0001037573,0.00004316875,0.0001589186,0.00007084021,0.00000276246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008049739,"about_ca_system_score_gemma":0.0003171524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003150693,"about_ca_topic_score_gemma":0.00007688301,"domain_scores_codex":[0.9984299,0.0001269549,0.0006565919,0.0003276635,0.0002262335,0.000232653],"domain_scores_gemma":[0.998656,0.0004046531,0.0005718544,0.0002420049,0.00009265679,0.00003284939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002068213,0.0001194847,0.9533187,0.00004396312,0.0001041612,0.000001977822,0.0001779296,0.0006183301,0.009474777,0.00004406931,0.0000388319,0.03585095],"study_design_scores_gemma":[0.00101947,0.00004772041,0.9754342,0.0006134305,0.0001146596,0.0001085839,0.005455554,0.002054483,0.01419024,0.0002021156,0.000349783,0.0004097181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995518,0.0001152902,0.003029421,0.00001844451,0.0003477338,0.0006037015,0.00004998925,0.000003863014,0.0003135726],"genre_scores_gemma":[0.9987161,0.00001133951,0.0009497906,0.00003367288,0.0000175345,0.00003719287,0.0002207436,0.0000112162,0.000002378954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03544123,"threshold_uncertainty_score":0.5599085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03423820371019849,"score_gpt":0.2993152341982638,"score_spread":0.2650770304880653,"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."}}