{"id":"W1976926329","doi":"10.1097/rti.0b013e3182765785","title":"Automatic Airway Analysis on Multidetector Computed Tomography in Cystic Fibrosis","year":2012,"lang":"en","type":"article","venue":"Journal of Thoracic Imaging","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Cystic fibrosis; Airway; Air trapping; Lumen (anatomy); Computed tomography; Lung volumes; Radiology; Multidetector computed tomography; Pulmonary function testing; Lung; High-resolution computed tomography; Airway resistance; Internal medicine; Cardiology; Nuclear medicine; Surgery","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":[0.001315453,0.0001960394,0.0007159468,0.002522391,0.00006072998,0.00005037598,0.0001846188,0.00003869379,0.0002061527],"category_scores_gemma":[0.0009794862,0.0001516803,0.000452313,0.00221939,0.00008466042,0.000456268,0.00005033073,0.0005404362,0.00002557537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002481214,"about_ca_system_score_gemma":0.00007169652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002037635,"about_ca_topic_score_gemma":0.000003950249,"domain_scores_codex":[0.9974842,0.0002190743,0.0007599241,0.0001596486,0.0008306223,0.0005465188],"domain_scores_gemma":[0.9980332,0.000664237,0.0004093629,0.0002873323,0.00022927,0.0003766037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008322756,0.0006448648,0.7599795,0.0004398811,0.0007129694,0.0002377684,0.0005846123,0.001060661,0.01965657,0.000005624686,0.000368521,0.2154768],"study_design_scores_gemma":[0.001129446,0.0004187942,0.8870944,0.001761562,0.001135731,0.0003671466,0.0003499545,0.09215182,0.01465653,0.00005479389,0.0006225418,0.0002572713],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843746,0.003207993,0.01113064,0.0006155721,0.0002614031,0.0002142268,0.000006259138,0.00003744806,0.0001518811],"genre_scores_gemma":[0.9326549,0.00001588116,0.06692968,0.0001174386,0.0002306218,0.000005963745,0.000003615902,0.00002298458,0.00001897776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2152195,"threshold_uncertainty_score":0.6185343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335453525397509,"score_gpt":0.3478884294257635,"score_spread":0.3345338941717885,"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."}}