{"id":"W4300217162","doi":"10.1007/978-3-031-01654-7_2","title":"Detection and Analysis of Breast Masses","year":2012,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on biomedical engineering","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Breast cancer; Sign (mathematics); Abnormality; Medicine; Mammography; Radiology; Cancer; Internal medicine; 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":[0.0003904045,0.0008187969,0.0007359901,0.001274538,0.0001673212,0.001159199,0.0008327243,0.0008056628,0.0112376],"category_scores_gemma":[0.00098787,0.0004867105,0.0005603135,0.000795526,0.000428521,0.0007577697,0.0006418481,0.0008347975,0.007853745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003044098,"about_ca_system_score_gemma":0.0002887518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00058517,"about_ca_topic_score_gemma":0.001249014,"domain_scores_codex":[0.9997724,0.00001837498,0.000006977601,0.00006531621,0.0001159829,0.00002097952],"domain_scores_gemma":[0.9996977,0.0001647496,0.00001583824,0.00002925556,0.00007342177,0.00001902873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007274013,0.00003663325,0.0004682527,0.00042062,0.00004158357,0.0001042894,0.00008308554,0.005424972,0.05285314,0.01034462,0.03500678,0.8951432],"study_design_scores_gemma":[0.00003323591,0.0002424336,0.0132363,0.000404486,0.0001589578,0.003491318,0.00019398,0.2095571,0.1888909,0.09128863,0.4923652,0.0001375164],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008881113,0.03754878,0.9111892,0.001352744,0.001078276,0.00008264496,0.0007993028,0.002689681,0.03637819],"genre_scores_gemma":[0.1059948,0.03861453,0.5697928,0.0008973211,0.001597999,0.0001220992,0.002429815,0.0009395749,0.2796111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0112376,"threshold_uncertainty_score":0.03759348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007176013851671199,"score_gpt":0.1968454778935385,"score_spread":0.1896694640418673,"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."}}