{"id":"W4413174753","doi":"10.18280/ts.420416","title":"Early Diagnosis of Mammogram Images Using Hybird Deep and Machine Learning Algorithm","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Algorithm; Deep learning; Pattern recognition (psychology)","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":[0.0003338445,0.0004513265,0.000365555,0.0009818209,0.0001772357,0.000424583,0.0007689635,0.0005587699,0.001321166],"category_scores_gemma":[0.000583981,0.0002274575,0.0003674816,0.0003750174,0.0001955928,0.0005311784,0.0004515839,0.0004900731,0.000570905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005133753,"about_ca_system_score_gemma":0.0006081768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007109851,"about_ca_topic_score_gemma":0.00866998,"domain_scores_codex":[0.9998407,0.00001941117,0.000007151097,0.00003961238,0.00006187741,0.0000311707],"domain_scores_gemma":[0.9998603,0.00002636654,0.00002029219,0.00001334985,0.00006657824,0.00001309856],"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":[0.0003330069,0.0003258854,0.006873828,0.000129692,0.0001183981,0.0002437761,0.00006757673,0.1579415,0.04546911,0.00344092,0.007554627,0.7775017],"study_design_scores_gemma":[0.000007653679,0.00004388582,0.00122537,0.000007706672,0.0000124499,0.0000637616,0.000008622465,0.988492,0.008301287,0.0007635352,0.00106653,0.000007212197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.139826,0.00136647,0.8485208,0.0005199662,0.0001644401,0.0001483219,0.0002813406,0.00435552,0.004817249],"genre_scores_gemma":[0.6754924,0.0006611008,0.3159899,0.0003485674,0.00008494448,0.00009725716,0.0006816546,0.00008194045,0.006562242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007109851,"threshold_uncertainty_score":0.01413691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01408350096558175,"score_gpt":0.244013649789575,"score_spread":0.2299301488239932,"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."}}