{"id":"W4323845238","doi":"10.18280/isi.280102","title":"MRI Brain Tumor Identification and Classification Using Deep Learning Techniques","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Artificial intelligence; Deep learning; Brain tumor; Computer science; Pattern recognition (psychology); 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":[0.000836984,0.0001684797,0.0001432094,0.0005958515,0.0007538113,0.0004787527,0.0001593039,0.00009874359,0.00002180219],"category_scores_gemma":[0.001762318,0.0001809986,0.00004540892,0.00127411,0.0002074634,0.00284344,0.00005751241,0.0002098762,0.0003174263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002388275,"about_ca_system_score_gemma":0.00003826568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000142657,"about_ca_topic_score_gemma":0.000003131606,"domain_scores_codex":[0.9982932,0.0002135616,0.000618555,0.0002729237,0.0003224467,0.0002793447],"domain_scores_gemma":[0.9988375,0.0001935286,0.000509005,0.0002370148,0.0001414291,0.00008147128],"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":[0.00002692703,0.00001369215,0.0006752103,0.0001725057,0.000004292415,0.00000191285,0.003187518,0.0002501124,0.813682,0.007963753,0.0002472104,0.1737748],"study_design_scores_gemma":[0.000369488,0.0000934093,0.05693023,0.0001214419,0.0000199085,0.0002186138,0.00428349,0.4927312,0.4197793,0.00529476,0.01964801,0.0005101622],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8718486,0.00002025695,0.1191118,0.0006797239,0.0003944304,0.0008048381,0.00001149213,0.002186934,0.004941886],"genre_scores_gemma":[0.998435,0.00006130741,0.0006362034,0.0003516414,0.00006104064,0.0001208162,0.00005833824,0.00002131214,0.0002543506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4924811,"threshold_uncertainty_score":0.7380909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729212538228021,"score_gpt":0.2787430641871003,"score_spread":0.24145093880482,"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."}}