{"id":"W2524887677","doi":"10.1259/bjr.20160480","title":"Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research","year":2016,"lang":"en","type":"review","venue":"British Journal of Radiology","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Digital Enhanced Cordless Telecommunications; Imaging phantom; Effective atomic number; Nuclear medicine; Radiation; Calibration; Biomedical engineering; Materials science; Optics; Medicine; Physics; Computer science; Attenuation","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":[0.005152933,0.0012968,0.0006097581,0.001275714,0.0003178962,0.001238079,0.000984165,0.001005185,0.001687719],"category_scores_gemma":[0.006528463,0.0006557854,0.0003685257,0.0008486353,0.0005958737,0.001499878,0.0007755141,0.0008825879,0.0007765153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005957704,"about_ca_system_score_gemma":0.001360561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004215681,"about_ca_topic_score_gemma":0.0009964174,"domain_scores_codex":[0.9984173,0.0004927705,0.0001543676,0.000215155,0.0006479811,0.00007246154],"domain_scores_gemma":[0.9962836,0.001417184,0.0007166813,0.0004528254,0.001048373,0.00008147761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003107784,0.0002257701,0.002530301,0.0008529486,0.00004643348,0.00009412502,0.00008275762,0.003828964,0.9521967,0.0005170581,0.0003999024,0.03891434],"study_design_scores_gemma":[0.00009144425,0.001607156,0.01254233,0.000295124,0.0002090543,0.000841936,0.0001341859,0.024475,0.9488771,0.0008839825,0.009946644,0.00009613831],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2766002,0.01507343,0.7005991,0.0005682366,0.0001835663,0.001656683,0.0005011993,0.001236621,0.003580952],"genre_scores_gemma":[0.2621917,0.005926449,0.7281338,0.0002815913,0.00005560493,0.00104287,0.0005705371,0.0005888654,0.001208575],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005152933,"threshold_uncertainty_score":0.0272516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0673055005066329,"score_gpt":0.4046384051101456,"score_spread":0.3373329046035127,"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."}}