{"id":"W4392158123","doi":"10.1109/globecom54140.2023.10436915","title":"Mammogram Tumor Segmentation with Preserved Local Resolution: An Explainable AI System","year":2023,"lang":"en","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Lakehead University","funders":"","keywords":"Computer science; Artificial intelligence; Segmentation; Image segmentation; Computer vision; Resolution (logic)","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":[0.0002914617,0.0003805429,0.0003199104,0.0003148132,0.0002780416,0.0004946386,0.0008314597,0.0007265329,0.002136889],"category_scores_gemma":[0.0006917722,0.0001685629,0.0004590637,0.000252811,0.0003027089,0.0006240342,0.0005974176,0.0004917427,0.0004583441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000558382,"about_ca_system_score_gemma":0.0005236826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003470072,"about_ca_topic_score_gemma":0.003392486,"domain_scores_codex":[0.9999009,0.00001551547,0.000004605605,0.00003891292,0.00002330245,0.00001674692],"domain_scores_gemma":[0.9998558,0.00004367941,0.00002225951,0.00002411132,0.00003912739,0.00001501925],"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":[0.0005352937,0.0001897387,0.003362988,0.0002217118,0.0001469759,0.001128447,0.0003320334,0.2649192,0.1514138,0.01920128,0.007106688,0.5514419],"study_design_scores_gemma":[0.00001036014,0.00005787925,0.00084829,0.000006303615,0.00002990499,0.0002123748,0.00001529385,0.9815987,0.01124399,0.003423445,0.002541591,0.00001181698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07913717,0.0007709111,0.9076705,0.0009917408,0.0001003781,0.0001117819,0.0002639979,0.005183314,0.005770238],"genre_scores_gemma":[0.7595879,0.0004535544,0.2314354,0.0003602526,0.00009427976,0.0001109088,0.0003484502,0.0001779434,0.007431402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003470072,"threshold_uncertainty_score":0.007148623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01712347211055992,"score_gpt":0.251873401264616,"score_spread":0.2347499291540561,"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."}}