{"id":"W2964110549","doi":"10.1097/tp.0000000000002771","title":"Lung Density Analysis Using Quantitative Chest CT for Early Prediction of Chronic Lung Allograft Dysfunction","year":2019,"lang":"en","type":"article","venue":"Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Lung; Lung transplantation; Receiver operating characteristic; Radiology; Retrospective cohort study; Cohort; Lung volumes; Nuclear medicine; Surgery; Internal medicine","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":[0.001631413,0.0004015095,0.0002620801,0.001201223,0.0001391217,0.0005694322,0.0003013225,0.0003685914,0.0006614595],"category_scores_gemma":[0.005861497,0.0001762336,0.0002396832,0.0003975613,0.0003005748,0.0003495329,0.0003099473,0.0003501267,0.0001963473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002659035,"about_ca_system_score_gemma":0.0002203785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009142198,"about_ca_topic_score_gemma":0.001160293,"domain_scores_codex":[0.9994971,0.0002232182,0.00005763653,0.00007111381,0.0001116957,0.00003926023],"domain_scores_gemma":[0.9960526,0.001751869,0.001275524,0.000166698,0.0004700361,0.0002831458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000150136,0.00001836194,0.996381,0.000006563713,0.00001390058,0.00002505719,0.000008573835,0.0001705628,0.0008273737,0.000008610372,0.00004213923,0.002347699],"study_design_scores_gemma":[0.00001857658,0.0003729683,0.985763,0.00001671011,0.00004637473,0.001209405,0.00004975206,0.01059865,0.001640419,0.0000668191,0.0002082704,0.000009207894],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976572,0.0004518547,0.001323243,0.00003595732,0.000006140805,0.00001402682,0.0001325211,0.00002234816,0.0003565907],"genre_scores_gemma":[0.9991042,0.00003807249,0.0007365157,0.000008591808,0.000005466189,0.000004869483,0.00007540971,0.00000177234,0.00002502001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001631413,"threshold_uncertainty_score":0.008627832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03391115765971717,"score_gpt":0.3319094128620646,"score_spread":0.2979982552023475,"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."}}