{"id":"W4220733064","doi":"10.18280/ria.360114","title":"Brain Tumor Classification Based on Enhanced CNN Model","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overfitting; Computer science; Artificial intelligence; Segmentation; Brain tumor; Pattern recognition (psychology); Context (archaeology); Benchmark (surveying); Convolutional neural network; Contextual image classification; Process (computing); Deep learning; Machine learning; Artificial neural network; Image (mathematics); Pathology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005332283,0.000190791,0.0001613457,0.0002357228,0.0008275504,0.00007201629,0.0005245531,0.00003813853,0.00174874],"category_scores_gemma":[0.0007119283,0.0002130173,0.0001052653,0.0009517528,0.0001177054,0.000119528,0.00007163859,0.0004368504,0.0008416341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002403098,"about_ca_system_score_gemma":0.0001019851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003598517,"about_ca_topic_score_gemma":0.00000177459,"domain_scores_codex":[0.9976219,0.0003045027,0.0004523065,0.0008007254,0.0004689986,0.0003515882],"domain_scores_gemma":[0.998382,0.0004724165,0.0002324144,0.0007543447,0.00004705556,0.0001118228],"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":[0.00006859488,0.0002193622,0.000003314838,0.000008522429,6.343213e-7,0.000003854139,0.0002277799,0.4061496,0.5706136,0.01429373,0.001026012,0.007385063],"study_design_scores_gemma":[0.00004363286,0.0001318449,0.00001331335,0.00000636022,0.000002232916,0.000007388196,0.0003468748,0.5705053,0.4226755,0.001057226,0.005071429,0.0001388961],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1623235,0.00001574429,0.752403,0.01482005,0.001146339,0.001178522,0.00006618728,0.0006758547,0.06737071],"genre_scores_gemma":[0.9853063,0.000003201865,0.0002363214,0.006409112,0.00005376216,0.0004031138,0.00001278371,0.00003570707,0.007539715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8229827,"threshold_uncertainty_score":0.9999363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08656262275295305,"score_gpt":0.2982000523940131,"score_spread":0.21163742964106,"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."}}