{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000563692,0.0002352917,0.0002122833,0.0007825229,0.0001200524,0.0003523874,0.000218784,0.0003708332,0.0004271248],"category_scores_gemma":[0.001995774,0.0001247159,0.0002012107,0.000245963,0.0002022569,0.0002153574,0.0003231754,0.0001398203,0.000154846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001416231,"about_ca_system_score_gemma":0.0001559166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007703658,"about_ca_topic_score_gemma":0.001191287,"domain_scores_codex":[0.9996055,0.0001458924,0.00002507648,0.00007693957,0.0001205082,0.00002625152],"domain_scores_gemma":[0.9993219,0.0002833525,0.0001519006,0.00007917365,0.0001271751,0.00003644832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001160321,0.0001078126,0.4907541,0.0003215043,0.0001563026,0.00100977,0.0003561763,0.01240196,0.2321237,0.0003577092,0.0007548804,0.2604958],"study_design_scores_gemma":[0.00003578648,0.0003750121,0.8872976,0.00006799422,0.00007457975,0.004126722,0.0001055838,0.08112762,0.02506688,0.0004420211,0.001239603,0.00004070883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801273,0.0007799599,0.01837307,0.00003578763,0.000007435973,0.00002483563,0.0001563062,0.0002032006,0.0002921479],"genre_scores_gemma":[0.9844065,0.0001359587,0.01503776,0.00002697062,0.00001366981,0.00001997305,0.0002360491,0.0000185806,0.0001045815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007825229,"threshold_uncertainty_score":0.002981126,"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."}}