{"id":"W4392266678","doi":"10.1016/j.jacadv.2024.100893","title":"3D Printed Models in Cardiology Training","year":2024,"lang":"en","type":"editorial","venue":"JACC Advances","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cardiology; Internal medicine; Medical physics; 3d printed; Training (meteorology); Medicine; Computer science; Biomedical engineering; Geography","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":[0.0001490602,0.0002448509,0.0005911882,0.0002351302,0.00001399565,0.00000917258,0.0002773702,0.001168593,0.00001579227],"category_scores_gemma":[0.0002703044,0.0002264301,0.00007985573,0.000209233,0.00009410792,0.0001105634,0.00006580936,0.001732215,0.00004339994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136061,"about_ca_system_score_gemma":0.00007880091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004897656,"about_ca_topic_score_gemma":0.00004217502,"domain_scores_codex":[0.9987827,0.0000182129,0.0002926798,0.000327935,0.000194842,0.0003836121],"domain_scores_gemma":[0.9994326,0.0002733619,0.00002570805,0.0001933999,0.0000221042,0.00005278008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001095677,0.000004353938,0.000001107167,0.0004579891,0.00009161308,0.0003333765,0.0003107002,0.019433,0.000003658227,0.001159802,0.7423911,0.2358023],"study_design_scores_gemma":[0.0001463389,0.00002018953,2.546377e-7,0.0002232518,0.00001786471,0.000004160469,0.000133784,0.01214461,0.000009205016,0.02056583,0.9665185,0.0002160311],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0000685693,0.04307384,0.008880693,0.00004198964,0.919559,0.0001356135,0.00004791288,0.001011713,0.02718066],"genre_scores_gemma":[0.01016139,0.04143951,0.002549882,0.00002208143,0.944366,0.0002343293,0.0001629034,0.0001485478,0.0009153364],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.2355863,"threshold_uncertainty_score":0.9233553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097843614758045,"score_gpt":0.2643507822210441,"score_spread":0.2533723460734637,"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."}}