{"id":"W4416799376","doi":"10.1109/icriset64803.2025.11253735","title":"Hybrid Ensemble DL Model for Breast Cancer Detection and Classification with Enhanced Breast Lesion Segmentation using U-Net Model","year":2025,"lang":"","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Segmentation; Pattern recognition (psychology); Breast cancer; Mammography; Deep learning; Image segmentation; Masking (illustration); Breast ultrasound; Medical imaging","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":[0.000464477,0.0007744971,0.0008171467,0.0007795551,0.0003020661,0.000799328,0.001551462,0.001020065,0.001665923],"category_scores_gemma":[0.0007122458,0.0003276087,0.000866193,0.0004650792,0.0002689235,0.0008299102,0.0005782818,0.0008121282,0.0005548006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202022,"about_ca_system_score_gemma":0.000913297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0193329,"about_ca_topic_score_gemma":0.01928583,"domain_scores_codex":[0.9998177,0.00002671238,0.000009384048,0.00006432163,0.00004658895,0.00003526505],"domain_scores_gemma":[0.9997732,0.00007086241,0.00002257496,0.00001788215,0.00009706299,0.00001850728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002424032,0.0001062223,0.002440823,0.00005196329,0.00008694865,0.0001092036,0.00005035379,0.8383762,0.005505597,0.002851987,0.002538159,0.1476402],"study_design_scores_gemma":[0.000001889131,0.00001088651,0.00008973754,0.000001658782,0.000006052453,0.00001081836,0.000001748054,0.9989271,0.0004631717,0.0003133101,0.0001714013,0.000002224714],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07418462,0.001235244,0.915546,0.0005763904,0.0001244991,0.00007335152,0.000351871,0.00251261,0.005395385],"genre_scores_gemma":[0.8574674,0.0007081485,0.1237575,0.0005569051,0.00007600861,0.0001996076,0.0008595947,0.000134468,0.01624042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0193329,"threshold_uncertainty_score":0.0384407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04168465454664711,"score_gpt":0.3018203444873563,"score_spread":0.2601356899407092,"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."}}