{"id":"W3113998447","doi":"","title":"Creating Neonatal Ultrasound Simulations using 3D printing","year":2017,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Ultrasound; Medical physics; Modality (human–computer interaction); 3D printing; Medicine; Ideal (ethics); Computer science; Engineering; Radiology; Human–computer interaction; Mechanical 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":[0.00009866653,0.0001244921,0.0001402817,0.00007077352,0.0005518935,0.0001271637,0.000277459,0.0001499272,0.00006091496],"category_scores_gemma":[0.0006973552,0.0001295444,0.00003568233,0.0000665067,0.0001231402,0.0003816635,0.00007544673,0.0002705271,0.00001394721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005033131,"about_ca_system_score_gemma":0.0000116918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001655064,"about_ca_topic_score_gemma":0.000002949876,"domain_scores_codex":[0.9992421,8.97814e-7,0.0001636943,0.00016501,0.0001259076,0.0003024129],"domain_scores_gemma":[0.999621,0.00003992278,0.00006969131,0.0001375027,0.00005407921,0.00007783556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002804221,0.0001169809,0.2696381,0.001173156,0.0005195394,0.00007105007,0.009163993,0.007656259,0.1735349,0.1046119,0.002003791,0.4314823],"study_design_scores_gemma":[0.001025971,0.00004910103,0.01178198,0.0004770151,0.0001196658,0.0002326876,0.001345102,0.8380999,0.04357984,0.005617892,0.09672862,0.0009422135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9664837,0.0001463119,0.003790255,0.00007441154,0.0002021616,0.0001077788,0.000003117754,0.000618255,0.028574],"genre_scores_gemma":[0.989337,0.00002308889,0.01026379,0.00001998117,0.0002121177,0.000004146458,0.000001774518,0.00002857383,0.0001095256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8304437,"threshold_uncertainty_score":0.5282669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543421520506849,"score_gpt":0.2603122657741221,"score_spread":0.2448780505690536,"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."}}