{"id":"W3129719872","doi":"10.1117/12.2580455","title":"Theoretical optimization of dual-energy x-ray imaging of chronic obstructive pulmonary disease (COPD)","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Figure of merit; COPD; Image quality; X-ray detector; Noise (video); Image resolution; Pulmonary disease; Physics; Optics; Nuclear medicine; Radiology; Medicine; Detector; Computer science; Artificial intelligence; Image (mathematics); 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":[0.001206,0.0009274653,0.0007276238,0.0005854319,0.0002196709,0.001155501,0.000995966,0.001398231,0.001625467],"category_scores_gemma":[0.003715942,0.000761941,0.0006329004,0.0003044847,0.0009987568,0.0009858035,0.001284054,0.0005669298,0.0002718722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001160653,"about_ca_system_score_gemma":0.0007266153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002247505,"about_ca_topic_score_gemma":0.001448886,"domain_scores_codex":[0.9995104,0.0001883068,0.00001815903,0.00008399881,0.0001517119,0.00004750646],"domain_scores_gemma":[0.9988544,0.0007856814,0.0001119388,0.00004762829,0.0001500571,0.00005037463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006822631,0.00002729684,0.0006628013,0.0001174703,0.00002139748,0.00009540489,0.00004458511,0.9740218,0.005849907,0.01322114,0.0002559108,0.005613944],"study_design_scores_gemma":[0.000005972337,0.00001354322,0.0001992963,0.000004648166,0.000004691382,0.00002980106,0.000004893437,0.9970401,0.0003339336,0.00223687,0.0001204719,0.000005646488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0506533,0.0007980415,0.9409109,0.0009045734,0.00002668706,0.00006768173,0.0001165608,0.0001490016,0.006373385],"genre_scores_gemma":[0.7788119,0.001266868,0.2138288,0.0002661285,0.00004305792,0.0003065876,0.0002230018,0.0001543162,0.005099413],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002247505,"threshold_uncertainty_score":0.008421183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003266367711900726,"score_gpt":0.1980923010892512,"score_spread":0.1948259333773505,"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."}}