{"id":"W1923826647","doi":"10.3109/0284186x.2015.1061212","title":"A simulation study on proton computed tomography (CT) stopping power accuracy using dual energy CT scans as benchmark","year":2015,"lang":"en","type":"article","venue":"Acta Oncologica","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"H. Lundbeck A/S; Aarhus Universitet","keywords":"Medicine; Computed tomography; Stopping power; Tomography; Nuclear medicine; Benchmark (surveying); Proton; Radiology; Physics; Nuclear physics; Optics; Detector","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":[0.001668385,0.0006272609,0.0004502042,0.0007694077,0.0003067623,0.0007554599,0.0008603488,0.001321094,0.001069936],"category_scores_gemma":[0.00624385,0.0003430031,0.0006743541,0.0009382305,0.0004649417,0.0005077791,0.0004127102,0.0004698208,0.0001430615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043856,"about_ca_system_score_gemma":0.000552633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009330407,"about_ca_topic_score_gemma":0.00475469,"domain_scores_codex":[0.9995114,0.0002257183,0.00003406758,0.00005902095,0.000117082,0.0000527036],"domain_scores_gemma":[0.9920871,0.0063593,0.0004601452,0.0002791141,0.0007166689,0.00009760653],"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":[0.0003145588,0.00008031342,0.006265418,0.00007813853,0.00003144593,0.0001103862,0.00004447077,0.9871582,0.002436158,0.0004146053,0.0001468306,0.002919349],"study_design_scores_gemma":[0.00004512159,0.0002188109,0.001994278,0.00001688634,0.00003225442,0.00008156195,0.00002464932,0.9935139,0.003633636,0.0002180027,0.000208097,0.00001273348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637189,0.0005519589,0.03152166,0.0001874317,0.00001779415,0.00008389974,0.0004435971,0.0001767139,0.003298056],"genre_scores_gemma":[0.9869822,0.000151619,0.01217642,0.00002623295,0.00000411188,0.00004901241,0.0002406997,0.00002927988,0.0003404751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009330407,"threshold_uncertainty_score":0.01855218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04308615340273367,"score_gpt":0.315801108696845,"score_spread":0.2727149552941113,"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."}}