{"id":"W4221101816","doi":"10.18280/ts.390123","title":"A Novel Ensemble Bagging Classification Method for Breast Cancer Classification Using Machine Learning Techniques","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"AI in cancer detection","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overfitting; Machine learning; Artificial intelligence; Ensemble learning; Computer science; Breast cancer; Contextual image classification; Statistical classification; Weighted voting; Pattern recognition (psychology); Cancer; Voting; Image (mathematics); Artificial neural network; Medicine","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":[0.001775033,0.001049443,0.001795797,0.002912185,0.0009070401,0.001194017,0.001666052,0.001049298,0.001383517],"category_scores_gemma":[0.002669576,0.0003606683,0.001460804,0.002666963,0.0002699116,0.001611544,0.0008291676,0.001156158,0.0009259211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005259662,"about_ca_system_score_gemma":0.001082451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007282487,"about_ca_topic_score_gemma":0.007851033,"domain_scores_codex":[0.9986771,0.0002400438,0.0001233464,0.0002667923,0.0005342301,0.0001584846],"domain_scores_gemma":[0.9986487,0.0003732317,0.00009762333,0.0001437923,0.0006771693,0.00005953111],"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":[0.0001695618,0.0001662624,0.004382575,0.00009178726,0.0001720007,0.00008511551,0.0001074811,0.04256416,0.008592752,0.001663021,0.005291446,0.9367139],"study_design_scores_gemma":[0.00001520114,0.0001363159,0.002592659,0.00002822485,0.000105704,0.0001950864,0.00005748334,0.9839106,0.006040017,0.002159209,0.004716835,0.00004269453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02852129,0.001945593,0.9655228,0.000227816,0.0003719285,0.0001113308,0.0002232831,0.001567925,0.001507996],"genre_scores_gemma":[0.4534122,0.001812431,0.5350667,0.000437974,0.0005026768,0.0003489621,0.001832114,0.0001769402,0.006410077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007282487,"threshold_uncertainty_score":0.01448023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06985194399396133,"score_gpt":0.3282756140508642,"score_spread":0.2584236700569029,"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."}}