{"id":"W4353080404","doi":"10.54097/hset.v34i.5388","title":"Breast Cancer Prediction Based on the CNN Models","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"AI in cancer detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Breast cancer; Margin (machine learning); Medical diagnosis; Deep learning; Artificial intelligence; Computer science; Cancer; Residual neural network; Machine learning; Pattern recognition (psychology); Medicine; Internal medicine; Radiology","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":[0.0002410344,0.0008188827,0.000412024,0.0008319764,0.0001405564,0.0004298142,0.0006398579,0.0005356541,0.001692276],"category_scores_gemma":[0.0009891589,0.0002091244,0.0005175837,0.0004257445,0.0001240365,0.0004703117,0.0002616459,0.0004849891,0.0008900164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002357,"about_ca_system_score_gemma":0.000514656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02619902,"about_ca_topic_score_gemma":0.02610181,"domain_scores_codex":[0.9998783,0.00001413643,0.000005939681,0.00004303696,0.0000288856,0.00002972572],"domain_scores_gemma":[0.9998085,0.00004821901,0.00002119285,0.00001789722,0.00008992617,0.00001439303],"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":[0.0007392499,0.0003395148,0.05247149,0.0001910035,0.0002654384,0.0007285159,0.0000497617,0.4137248,0.01021045,0.00225022,0.03427667,0.4847528],"study_design_scores_gemma":[0.000005872187,0.00002349688,0.003438457,0.00001435747,0.00002799207,0.00008441008,0.000008734193,0.992961,0.001610105,0.0008358415,0.0009834472,0.000006203732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7213286,0.01267611,0.2242174,0.003476859,0.0008537927,0.0002236606,0.007933118,0.006105207,0.02318529],"genre_scores_gemma":[0.9681166,0.001361663,0.01873197,0.0004029474,0.0001187508,0.00005062025,0.003624732,0.00005691306,0.007535784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02619902,"threshold_uncertainty_score":0.05209303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039749525109442,"score_gpt":0.211775385055101,"score_spread":0.2013778898040066,"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."}}