{"id":"W3016427020","doi":"10.1007/s11548-020-02142-x","title":"Augmented reality simulator for ultrasound-guided percutaneous renal access","year":2020,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Face validity; Construct validity; Simulation; Likert scale; Medicine; Psychology; Surgery; Psychometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006354243,0.0001665711,0.0004354689,0.0002002659,0.0001148037,0.0002117492,0.001210286,0.0001210925,0.00001238655],"category_scores_gemma":[0.0002854419,0.0001469363,0.0002602081,0.0001860675,0.0001204597,0.0004885872,0.0001929625,0.0002385118,0.000002139775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008003793,"about_ca_system_score_gemma":0.000203741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006566243,"about_ca_topic_score_gemma":0.000001377295,"domain_scores_codex":[0.9980901,0.0002138775,0.0008432491,0.0003164104,0.0003262815,0.000210063],"domain_scores_gemma":[0.995988,0.002319947,0.0006106676,0.0001924283,0.000661299,0.0002276569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001913949,0.001174698,0.02621816,0.0001742849,0.006816931,0.002365406,0.002804972,0.0720689,0.02061967,0.03723609,0.6329007,0.1957062],"study_design_scores_gemma":[0.003369674,0.0006253245,0.07205797,0.0002201094,0.0001949912,0.06744371,0.00004497133,0.7560629,0.001627783,0.009387944,0.08791745,0.001047154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03933673,0.0001306151,0.9355553,0.02367863,0.001034359,0.0001391948,0.00002427664,0.00005477139,0.00004611457],"genre_scores_gemma":[0.9760227,0.0001314533,0.01732071,0.005437338,0.001022991,0.000007248183,0.00003481446,0.00001125133,0.00001144565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.936686,"threshold_uncertainty_score":0.5991889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06830246921009771,"score_gpt":0.3313560924955697,"score_spread":0.263053623285472,"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."}}