{"id":"W2957964466","doi":"","title":"Segmentation of Breast Cancer Ultrasound Images","year":2019,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University; Lawson Health Research Institute","keywords":"Breast cancer; Ultrasound; Segmentation; Computer vision; Artificial intelligence; Medicine; Computer science; Medical physics; Cancer; Radiology; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006220227,0.0002769048,0.0003081023,0.0002568542,0.00008677803,0.00007984941,0.0009021916,0.0002331147,0.01735162],"category_scores_gemma":[0.000003359369,0.0003230553,0.0001430503,0.0007431909,0.00003657277,0.0008474011,0.00009055842,0.0002447793,0.00006353523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000415957,"about_ca_system_score_gemma":0.000250582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006178136,"about_ca_topic_score_gemma":0.0004844186,"domain_scores_codex":[0.9985206,0.0000793389,0.0002178239,0.0005628557,0.000378081,0.000241344],"domain_scores_gemma":[0.9987395,0.00006366627,0.0004582517,0.0004378322,0.0002362544,0.00006444792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002570856,0.00008300647,0.003746063,0.0007180873,0.0002821348,0.00002236306,0.002079,0.0006222203,0.04141101,0.001190355,0.002141685,0.947447],"study_design_scores_gemma":[0.01016336,0.001110599,0.2129205,0.004008955,0.001664725,0.0001864162,0.02963738,0.003892834,0.5154256,0.001362436,0.2131116,0.006515614],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01950347,0.0006838634,0.08970894,0.0002322979,0.006682253,0.001300139,0.0004120285,0.0004456305,0.8810314],"genre_scores_gemma":[0.08002722,0.0004065861,0.003947561,0.00005704888,0.0001349419,0.000004642491,0.0001288834,0.00005402114,0.9152391],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9409314,"threshold_uncertainty_score":0.9999222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00794762795977336,"score_gpt":0.2185687768282424,"score_spread":0.210621148868469,"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."}}