{"id":"W3041646086","doi":"10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a4572","title":"Normative Lung CT Density Metrics Updated for Low Dose Imaging in a Healthy Never-Smoking Multiethnic Population: The MESA Lung Study","year":2020,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Mesa; Medicine; Population; Lung; Normative; Computed tomography; Medical physics; Computer science; Environmental health; Radiology; Internal medicine; Political 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":[0.0016005,0.000437769,0.0005015525,0.001606885,0.0005752314,0.001567261,0.0011896,0.0007952205,0.001102398],"category_scores_gemma":[0.005554893,0.0003446949,0.0003911751,0.001416231,0.0003545895,0.0007707542,0.0008994507,0.0004796302,0.0005439986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006790931,"about_ca_system_score_gemma":0.000485809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01945601,"about_ca_topic_score_gemma":0.02853985,"domain_scores_codex":[0.9994839,0.0000995797,0.00007134151,0.0001654865,0.0001513944,0.00002820577],"domain_scores_gemma":[0.9977297,0.0002338453,0.0003781139,0.000574775,0.0009341769,0.0001494425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005816917,0.0001428607,0.9661941,0.0000771363,0.0004098173,0.0002580474,0.0004973573,0.001088709,0.003201422,0.0005243068,0.004585426,0.02243915],"study_design_scores_gemma":[0.00002732458,0.00005950551,0.991137,0.00002472979,0.0001966155,0.0006820958,0.000374471,0.002442281,0.0008841989,0.0003436511,0.003807134,0.00002100494],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826818,0.000540826,0.003827734,0.000124068,0.00002853925,0.00009162632,0.009155448,0.0002148598,0.003335152],"genre_scores_gemma":[0.987322,0.00020156,0.003320897,0.00008323159,0.00002018485,0.0001058,0.008140649,0.0001024429,0.0007031938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01945601,"threshold_uncertainty_score":0.0386855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03976081570268592,"score_gpt":0.3708366320786952,"score_spread":0.3310758163760093,"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."}}