{"id":"W2030448323","doi":"10.1118/1.3250860","title":"Identification of breast calcification using magnetic resonance imaging","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mammography; Magnetic resonance imaging; Digital mammography; Breast cancer; Microcalcification; Nuclear magnetic resonance; Contrast (vision); Paramagnetism; Susceptibility weighted imaging; Diamagnetism; Radiology; Materials science; Medicine; Cancer; Magnetic field; Physics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007622794,0.0003636386,0.0003586287,0.002857721,0.0001631978,0.0004449284,0.0002321824,0.0006790383,0.0009001421],"category_scores_gemma":[0.001770987,0.000322633,0.0002704717,0.0009904522,0.0002557329,0.0003409409,0.000252092,0.0002937204,0.0003440003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000137427,"about_ca_system_score_gemma":0.0001929067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005961768,"about_ca_topic_score_gemma":0.001082914,"domain_scores_codex":[0.9997131,0.00007709169,0.00002185906,0.00004701934,0.0001129086,0.00002804038],"domain_scores_gemma":[0.9996157,0.0001274066,0.00007226582,0.00004249042,0.0001138506,0.00002840599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008236693,0.0001246269,0.06024225,0.0006624623,0.0001119232,0.003971646,0.0002597521,0.0005173557,0.7615877,0.0003416483,0.0006293784,0.1707276],"study_design_scores_gemma":[0.00008567856,0.001209475,0.5182109,0.0002131105,0.000291255,0.05783592,0.000471886,0.01563869,0.3921831,0.0008617216,0.01286504,0.0001332405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337524,0.01035121,0.04701064,0.0004570148,0.0001153214,0.0002634295,0.000253511,0.0007470776,0.007049384],"genre_scores_gemma":[0.8998559,0.004528001,0.09316611,0.0002075805,0.00006795525,0.00005844672,0.0002101722,0.00003399927,0.001871856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002857721,"threshold_uncertainty_score":0.00403142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708021983409125,"score_gpt":0.3346599816156356,"score_spread":0.3175797617815443,"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."}}