{"id":"W7117360372","doi":"10.71146/kjmr777","title":"A HYBRID DATASET-BASED ENSEMBLE STRATEGY FOR EFFICIENT BREAST CANCER DETECTION","year":2025,"lang":"","type":"article","venue":"Kashf Journal of Multidisciplinary Research","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Breast cancer; Support vector machine; Cancer; Mammography; Random forest; Feature (linguistics); Breast cancer awareness; Focus (optics)","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":[0.001702086,0.00119071,0.001878838,0.002684705,0.0008059603,0.001319168,0.001925503,0.001206776,0.001688111],"category_scores_gemma":[0.002584904,0.0003697355,0.001411512,0.002075256,0.0002066161,0.001601356,0.001686374,0.0009852232,0.001265524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006296505,"about_ca_system_score_gemma":0.001107014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01189328,"about_ca_topic_score_gemma":0.01842506,"domain_scores_codex":[0.998701,0.0001732906,0.00008220183,0.0004100687,0.0004133503,0.0002200932],"domain_scores_gemma":[0.9988149,0.0001827053,0.00006060342,0.0002101781,0.0006437406,0.00008788203],"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":[0.0004911702,0.0006419473,0.02495594,0.00009966858,0.0004846855,0.0002614109,0.0001253207,0.07066631,0.0224833,0.001401622,0.02514993,0.8532387],"study_design_scores_gemma":[0.0000167353,0.0001210259,0.004978441,0.00001251033,0.0001062549,0.0001732557,0.00006868033,0.9820758,0.005846052,0.001714149,0.004859893,0.00002722671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1480782,0.002784005,0.8286219,0.001175051,0.0006529161,0.0003859896,0.003886314,0.007601786,0.006813899],"genre_scores_gemma":[0.732156,0.0007658569,0.2453585,0.0008046378,0.000445215,0.0002867758,0.01203841,0.0002822991,0.007862302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01189328,"threshold_uncertainty_score":0.02364808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08854667192971007,"score_gpt":0.4251838935375887,"score_spread":0.3366372216078787,"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."}}