{"id":"W2108899474","doi":"10.1183/09031936.02.00248202","title":"Computed tomography and magnetic resonance imaging: past, present and future","year":2002,"lang":"en","type":"article","venue":"European Respiratory Journal","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital","funders":"","keywords":"Magnetic resonance imaging; Tomography; Computed tomography; Computed tomography laser mammography; Nuclear magnetic resonance; Preclinical imaging; Physics; Medicine; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003643931,0.000123472,0.0001459539,0.000115133,0.000181337,0.00008263789,0.00009635389,0.00002033289,0.0001660264],"category_scores_gemma":[0.00001066604,0.00009735797,0.0000442005,0.0001497695,0.0001952748,0.00005912106,0.00007236107,0.0004330726,0.00001370998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009069744,"about_ca_system_score_gemma":0.000007797667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.363691e-7,"about_ca_topic_score_gemma":2.383656e-8,"domain_scores_codex":[0.9989784,0.0001375264,0.0002730947,0.0002096683,0.00020904,0.0001922232],"domain_scores_gemma":[0.9992251,0.00002202434,0.00008007172,0.0002166809,0.00007325201,0.0003828811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001533031,0.00009766243,0.03129782,0.0000249097,0.000007762168,0.0005701896,0.0001413528,7.14173e-8,0.001810102,0.0001243538,0.3637446,0.6021658],"study_design_scores_gemma":[0.0006377518,0.0001309198,0.1873327,0.00006888743,0.00002324928,0.001094602,0.00002269512,0.0005277359,0.00004692091,0.00003164184,0.8099978,0.00008509063],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4052553,0.3593142,0.003758742,0.1662032,0.0005558121,0.001394273,0.00002399113,0.0008686615,0.06262585],"genre_scores_gemma":[0.9121915,0.004482069,0.03274805,0.02779957,0.0205956,0.00001964819,0.000004765525,0.0001962216,0.001962605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6020807,"threshold_uncertainty_score":0.3970143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02162035765649177,"score_gpt":0.2593435992728166,"score_spread":0.2377232416163248,"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."}}