{"id":"W4230994571","doi":"10.1016/j.jvir.2009.04.050","title":"Emerging Technologies Subcommittee","year":2009,"lang":"en","type":"article","venue":"Journal of Vascular and Interventional Radiology","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Realm; Emerging technologies; Government (linguistics); Medicine; Engineering ethics; Public relations; Translational research; Political science; Computer science; Engineering; Pathology","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":[0.0001787094,0.00005563667,0.0001274917,0.0001298835,0.00001527941,0.000006916014,0.00007865352,0.00006569293,0.00002778498],"category_scores_gemma":[0.0000401881,0.00004448283,0.0001244696,0.00006223236,0.00002933801,0.00007018262,0.000005977708,0.0001581194,0.000001762066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001901281,"about_ca_system_score_gemma":0.000004419375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.962091e-7,"about_ca_topic_score_gemma":1.663089e-7,"domain_scores_codex":[0.9995888,0.00001019591,0.0002113249,0.00003895667,0.0000662242,0.00008448111],"domain_scores_gemma":[0.9998545,0.00001534864,0.00003046331,0.00004469589,0.00002554281,0.00002945032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004334538,0.0003926287,0.002942998,0.0005376273,0.001240012,0.00006952917,0.0004612137,0.004595513,0.02194622,0.04286633,0.1050532,0.8198514],"study_design_scores_gemma":[0.003409644,0.003507555,0.4795661,0.001017722,0.0002857746,0.006153245,0.0008605049,0.0203137,0.004741223,0.1461354,0.3330404,0.0009687639],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8011513,0.04679785,0.1448347,0.00454408,0.001717108,0.00005247613,0.000001929545,0.0001859574,0.000714569],"genre_scores_gemma":[0.9978077,0.0008467778,0.001186846,0.00002214882,0.0001172506,5.487061e-7,0.000001590782,0.000003537052,0.00001359806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8188826,"threshold_uncertainty_score":0.1813957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005669601106395832,"score_gpt":0.2267190810683039,"score_spread":0.221049479961908,"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."}}