{"id":"W3091908572","doi":"10.29007/srn7","title":"Optimal Targeting Display for Navigated Pelvic Screw Insertions","year":2020,"lang":"en","type":"article","venue":"EPiC series in health sciences","topic":"Pelvic and Acetabular Injuries","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Navigation system; Surgical instrument; Surgical procedures; Human–computer interaction; Computer vision; Artificial intelligence; Medicine; Surgery","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":[0.0007045362,0.0001157831,0.0002996531,0.00006418463,0.0004553591,0.00003605994,0.0001612035,0.00004471809,0.0001102833],"category_scores_gemma":[0.0005935559,0.00009258004,0.00005118526,0.000673651,0.0004519443,0.0002700822,0.000048464,0.0001588791,0.00001367784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004100329,"about_ca_system_score_gemma":0.0005108322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001468428,"about_ca_topic_score_gemma":0.00002747352,"domain_scores_codex":[0.9984938,0.00004770135,0.0004315595,0.0003316402,0.0002438939,0.0004513981],"domain_scores_gemma":[0.9994003,0.0001068783,0.0001111971,0.00009531416,0.00004936802,0.0002368999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004010913,0.0009319099,0.7014161,0.009300503,0.0001494462,0.0001678044,0.06973495,0.00718863,0.01004261,0.1059852,0.07033367,0.02073819],"study_design_scores_gemma":[0.009490286,0.01751823,0.2077933,0.003424956,0.0001030383,0.0002528327,0.06874144,0.07888155,0.01404584,0.004271056,0.5935463,0.00193124],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8965622,0.002770968,0.0007624174,0.09820463,0.0002948263,0.0006462324,0.00002102996,0.0001033758,0.0006342854],"genre_scores_gemma":[0.9663523,0.0001899082,0.02532397,0.007689181,0.0002193622,0.00005105828,0.00002909174,0.000009388878,0.0001357456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5232126,"threshold_uncertainty_score":0.3775305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819156336663213,"score_gpt":0.3596844915131252,"score_spread":0.3114929281464931,"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."}}