{"id":"W3129240920","doi":"10.1002/mp.14791","title":"A quantitative assessment of dual energy computed tomography‐based material decomposition for imaging bone marrow edema associated with acute knee injury","year":2021,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute; University of Calgary","funders":"","keywords":"Medicine; Digital Enhanced Cordless Telecommunications; Voxel; Nuclear medicine; Radiology; Bone marrow; Gold standard (test); Biomedical engineering; Pathology; Computer science","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":[0.0001152602,0.0001773011,0.0003380416,0.00004676355,0.00006689987,0.00002442262,0.0000660564,0.0000558363,0.00002676474],"category_scores_gemma":[0.00002443838,0.0001733316,0.00009620762,0.000315753,0.00009174499,0.0001458159,0.00002865302,0.0001353555,2.94865e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006082077,"about_ca_system_score_gemma":0.0001170075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004491445,"about_ca_topic_score_gemma":0.000005918986,"domain_scores_codex":[0.9988421,0.00004857857,0.0002697114,0.000189717,0.0003860676,0.000263783],"domain_scores_gemma":[0.999328,0.0001891133,0.00008830386,0.0001265313,0.0001668513,0.0001011544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001464678,0.003477287,0.004583045,0.001322435,0.004691285,0.001276985,0.0007908404,0.0781216,0.7494381,0.02836582,0.004386841,0.122081],"study_design_scores_gemma":[0.002700215,0.0003455084,0.001531898,0.0006313552,0.0002356347,0.00001311118,0.00007526549,0.7069147,0.2833293,0.003603207,0.0001514764,0.0004684185],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1466341,0.00005549931,0.8523203,0.0001276375,0.0003111785,0.0000954236,0.0001672927,0.0001512577,0.0001373269],"genre_scores_gemma":[0.9807926,0.000004928257,0.01810304,0.0001857869,0.0001279971,0.00004431378,0.0006970275,0.00004014368,0.000004109884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8342172,"threshold_uncertainty_score":0.7068257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00685240968258744,"score_gpt":0.277449801727837,"score_spread":0.2705973920452495,"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."}}