{"id":"W2921696836","doi":"10.1117/12.2512849","title":"Development and evaluation of pulmonary imaging multi-parametric response maps for deep phenotyping of chronic obstructive pulmonary disease","year":2019,"lang":"en","type":"article","venue":"","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Image registration; Voxel; Nuclear medicine; Magnetic resonance imaging; Pulmonary disease; Medical imaging; Medicine; Artificial intelligence; Physics; Computer science; Radiology; 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":[0.002458388,0.0006767971,0.0003894902,0.001170665,0.0001716268,0.000879817,0.0005216544,0.0006094156,0.0008781307],"category_scores_gemma":[0.004657351,0.0002071838,0.0005363063,0.0003096431,0.0002813594,0.0005151562,0.0007342415,0.0005053527,0.000289411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002795492,"about_ca_system_score_gemma":0.0004409132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005608118,"about_ca_topic_score_gemma":0.0007526876,"domain_scores_codex":[0.9994887,0.0002060948,0.00002754324,0.00009428475,0.0001495359,0.00003385852],"domain_scores_gemma":[0.9984713,0.0007487931,0.0002012657,0.0001575543,0.0003309528,0.00009015077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001163315,0.0004703815,0.0505792,0.000514661,0.0003064727,0.0005071153,0.0003703665,0.08268284,0.4310592,0.002290501,0.001341671,0.4287142],"study_design_scores_gemma":[0.00007798446,0.001413811,0.09555687,0.00009930656,0.0002407677,0.002191457,0.0002201351,0.6350119,0.2560654,0.00312264,0.005866076,0.0001335732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4471367,0.001046086,0.5468509,0.0003467394,0.00004243383,0.0002859617,0.0008721226,0.001779152,0.001639884],"genre_scores_gemma":[0.7291756,0.0003300048,0.2684282,0.00007837935,0.00002600962,0.0003420617,0.0006937876,0.0001967312,0.0007292512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002458388,"threshold_uncertainty_score":0.01300138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02960991244183625,"score_gpt":0.3124621744883843,"score_spread":0.282852262046548,"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."}}