{"id":"W2776231324","doi":"","title":"Analysis of abnormal CT scans using medical imaging software ‘Invivo5.4 Medical Design Suite’ by Anatomage","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Medical imaging; Medicine; Medical physics; Suite; Software; Radiology; Computed tomography; Medical diagnosis; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003590186,0.0007182299,0.0006301107,0.003403673,0.0002498923,0.001047272,0.0005705998,0.0005339251,0.02700586],"category_scores_gemma":[0.006637135,0.0006116171,0.0008381144,0.0008473708,0.0004706718,0.0009124328,0.00103232,0.0008360752,0.003828975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002302245,"about_ca_system_score_gemma":0.0006920908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003921932,"about_ca_topic_score_gemma":0.0005973655,"domain_scores_codex":[0.9989935,0.0002165081,0.0002164144,0.0001614056,0.0003488385,0.00006348517],"domain_scores_gemma":[0.9968258,0.001686205,0.0002516442,0.0003561748,0.0007455882,0.000134653],"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":[0.00318474,0.0003443978,0.04546906,0.001908968,0.0003216134,0.003854809,0.00177071,0.00471464,0.1415279,0.008662397,0.09712622,0.6911145],"study_design_scores_gemma":[0.0006712739,0.001821593,0.1430081,0.0007514817,0.0005907309,0.03679909,0.0008745995,0.1195493,0.2009219,0.008159537,0.4863022,0.0005501761],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2214099,0.002162059,0.6561174,0.001409694,0.0006757392,0.002415662,0.01053802,0.06401381,0.04125766],"genre_scores_gemma":[0.3167491,0.00123988,0.6384326,0.0003851781,0.0001938509,0.001978109,0.01224709,0.01238724,0.01638703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02700586,"threshold_uncertainty_score":0.09034359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171712075273634,"score_gpt":0.2747404002785533,"score_spread":0.263023279525817,"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."}}