{"id":"W4388441521","doi":"10.18280/isi.280518","title":"Automated Identification and Classification of Brain Tumors Using Hybrid Machine Learning Models and MRI Imaging","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Artificial intelligence; Computer science; Neuroimaging; Brain tumor; Machine learning; Pattern recognition (psychology); Neuroscience; Medicine; Psychology; Pathology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007129065,0.0001443442,0.0001610687,0.0005403837,0.0004285907,0.0002388991,0.00009869919,0.00004398058,0.000005261692],"category_scores_gemma":[0.0008109749,0.0001549244,0.00002955771,0.0007568662,0.0002331847,0.002865218,0.00005819719,0.0001352993,0.00002137799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001064125,"about_ca_system_score_gemma":0.00003757469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004190271,"about_ca_topic_score_gemma":0.000001978488,"domain_scores_codex":[0.9984936,0.0001706001,0.0006444727,0.0002267559,0.0002621105,0.0002025376],"domain_scores_gemma":[0.9988886,0.0001651446,0.0005810304,0.0001718022,0.0001278751,0.00006558939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004714878,0.00001849419,0.002480747,0.0004594762,0.000007948785,0.000002349705,0.005098925,0.007282798,0.9187018,0.007669417,0.0002308898,0.05800004],"study_design_scores_gemma":[0.0002500708,0.00001786797,0.02303901,0.00007140548,0.000008813398,0.0001036894,0.0008736574,0.9303525,0.04259024,0.002391058,0.000161934,0.0001397161],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9521472,0.00003617282,0.04545783,0.0002909901,0.0001238892,0.0003438553,0.00003705639,0.0009043941,0.0006586118],"genre_scores_gemma":[0.9994378,0.00006558584,0.0002038974,0.0000843286,0.00001366041,0.00002713133,0.00009549176,0.00001637275,0.00005572855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9230697,"threshold_uncertainty_score":0.6317636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145965148511233,"score_gpt":0.2711386075190708,"score_spread":0.2296789560339584,"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."}}