{"id":"W4415104312","doi":"10.30683/1929-2279.2025.14.20","title":"A Sisters Similarity Neural Network SSNN Model for Generalization and Detection of Mammographic Breast Cancer Lesion Abnormalities","year":2025,"lang":"en","type":"article","venue":"Journal of cancer research updates","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pattern recognition (psychology); Preprocessor; Generalization; Artificial neural network; Similarity (geometry); Segmentation; Discriminative model; Deep learning; Mammography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004361086,0.0004667742,0.0004538296,0.0003501072,0.0002218693,0.0004263251,0.001106437,0.0007634083,0.001834445],"category_scores_gemma":[0.0008417732,0.0002303529,0.0006325645,0.0003499291,0.0003120602,0.0005821954,0.0005489303,0.0007176966,0.0004408443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006282767,"about_ca_system_score_gemma":0.0005875993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008886592,"about_ca_topic_score_gemma":0.007631546,"domain_scores_codex":[0.9998318,0.00002418653,0.00001182118,0.00006547457,0.00004187337,0.00002487949],"domain_scores_gemma":[0.9998057,0.00004348567,0.00002206266,0.00002483842,0.0000922204,0.00001168105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002139598,0.0001542027,0.00360155,0.00007567091,0.0001093897,0.0001298272,0.00006236428,0.7815493,0.0103514,0.005823427,0.003646032,0.194283],"study_design_scores_gemma":[0.000002082369,0.00002469015,0.0002400152,0.000003026788,0.000005973149,0.00001336688,0.000002571613,0.9981003,0.0006351406,0.0007973151,0.0001729325,0.000002523509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2196823,0.001239647,0.7659574,0.000858353,0.0002365929,0.00009498289,0.00051419,0.001490552,0.009925991],"genre_scores_gemma":[0.9573436,0.000249221,0.032456,0.0001650649,0.00004930454,0.00007987431,0.0005415152,0.00003389799,0.009081523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008886592,"threshold_uncertainty_score":0.01766974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05699549791103678,"score_gpt":0.3811213001421099,"score_spread":0.3241258022310731,"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."}}