{"id":"W4402980415","doi":"10.1109/icme57554.2024.10687771","title":"Second-Order Self-Supervised Learning for Breast Cancer Classification","year":2024,"lang":"en","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Natural Science Foundation of China; Ministry of Education","keywords":"Computer science; Artificial intelligence; Machine learning; Breast cancer; Cancer; Supervised learning; Medicine; Artificial neural network; Internal medicine","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":[0.001485666,0.0009568917,0.001318983,0.001023412,0.0003938231,0.000910112,0.002480971,0.001012056,0.001358523],"category_scores_gemma":[0.003317124,0.0004183647,0.001075897,0.001044141,0.0006613192,0.001509565,0.001395853,0.001686887,0.0007731233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006783108,"about_ca_system_score_gemma":0.001033214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001848803,"about_ca_topic_score_gemma":0.002991263,"domain_scores_codex":[0.9989195,0.0002758368,0.0000561204,0.0003496387,0.0002762988,0.0001227036],"domain_scores_gemma":[0.9985977,0.0004606329,0.0001827414,0.0003572689,0.0003010779,0.0001005817],"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":[0.0004739696,0.0005940953,0.005925975,0.0002028435,0.0002284429,0.0001796218,0.0001685713,0.2528234,0.02017379,0.006400962,0.00930099,0.7035274],"study_design_scores_gemma":[0.000008033618,0.00003278517,0.0003206267,0.000002514329,0.000008865857,0.00002612108,0.000008701228,0.9943407,0.00272691,0.002141985,0.0003773509,0.000005444492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04588334,0.000423514,0.9486699,0.0002053998,0.00005056779,0.00008145445,0.0002126129,0.003471397,0.001001783],"genre_scores_gemma":[0.7287673,0.0002249029,0.2645694,0.0003707375,0.000151281,0.0002340013,0.001877602,0.0002665108,0.003538404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002480971,"threshold_uncertainty_score":0.007857025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192394045127387,"score_gpt":0.2800041904644108,"score_spread":0.2580802500131369,"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."}}