{"id":"W2517734444","doi":"10.1118/1.4961779","title":"Poster - 05: Automated analysis of MR distortion using a novel anthropomorphic phantom and open source software","year":2016,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Cancer Agency","funders":"","keywords":"Imaging phantom; Distortion (music); Radiosurgery; Computer science; Computer vision; Software; Artificial intelligence; Image quality; Quality assurance; Medical imaging; Nuclear medicine; Medicine; Radiology; Image (mathematics)","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":[0.00112295,0.0008599877,0.0003670573,0.001156146,0.0003040374,0.001358935,0.001372476,0.000545978,0.007058951],"category_scores_gemma":[0.003168581,0.0003611809,0.0006967776,0.0004852014,0.0003939562,0.0008581905,0.001184252,0.0005247536,0.002301405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004358902,"about_ca_system_score_gemma":0.0007894209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009551257,"about_ca_topic_score_gemma":0.001290137,"domain_scores_codex":[0.9991027,0.0001291953,0.00006070089,0.000170856,0.0004898265,0.00004663687],"domain_scores_gemma":[0.9983712,0.000434474,0.0001980484,0.0003934308,0.0004940662,0.0001089059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001018752,0.000593665,0.00987203,0.0005815204,0.0002156281,0.001080493,0.00077973,0.05606326,0.3055822,0.005358814,0.01529439,0.6035596],"study_design_scores_gemma":[0.0001453877,0.0007779741,0.01672636,0.0001042597,0.0001327488,0.003518849,0.0001683038,0.474421,0.4480645,0.00349269,0.05222122,0.0002268262],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05894652,0.0001467744,0.9142444,0.0001153401,0.0001029927,0.0002697908,0.0005760095,0.02211892,0.003479244],"genre_scores_gemma":[0.2751758,0.0001811434,0.710485,0.00008573337,0.00003890289,0.0003482939,0.002659943,0.004952566,0.006072578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007058951,"threshold_uncertainty_score":0.02361453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333645771433836,"score_gpt":0.2859244126017325,"score_spread":0.2625879548873941,"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."}}