{"id":"W2191222448","doi":"10.1016/j.cmpb.2015.09.019","title":"An automated confirmatory system for analysis of mammograms","year":2015,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Computer science; Mammography; Segmentation; Pattern recognition (psychology); Feature (linguistics); Computer vision; Image processing; Image segmentation; Feature selection; Image (mathematics); Medicine","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":[0.001683876,0.001059504,0.0009438422,0.004035796,0.00106444,0.001211579,0.001239268,0.001417061,0.01283182],"category_scores_gemma":[0.004163724,0.0005774736,0.0005190003,0.00146486,0.0002644869,0.000914378,0.001136292,0.0005978335,0.006689907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004430915,"about_ca_system_score_gemma":0.001924856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001940199,"about_ca_topic_score_gemma":0.003316101,"domain_scores_codex":[0.9990201,0.0001842139,0.0001293837,0.0001888526,0.000415458,0.00006198903],"domain_scores_gemma":[0.9955112,0.001497346,0.0002560352,0.0004488611,0.002073597,0.0002130404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002836531,0.0002645389,0.01309853,0.0007597243,0.0001400697,0.001075059,0.0001922802,0.0008555616,0.2943863,0.001808347,0.03728165,0.6473013],"study_design_scores_gemma":[0.001377857,0.002377964,0.07422645,0.0005274123,0.00122226,0.01777886,0.0003454318,0.231084,0.5335237,0.003530431,0.1335397,0.0004658394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1176101,0.00327594,0.7466915,0.000941897,0.0005335576,0.001673153,0.00591019,0.1167817,0.006581982],"genre_scores_gemma":[0.2164121,0.0007811586,0.7652169,0.0006683072,0.0003319835,0.0007810788,0.005141288,0.001400056,0.009267136],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01283182,"threshold_uncertainty_score":0.04292679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153654836854507,"score_gpt":0.4306598360999119,"score_spread":0.3152943524144612,"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."}}