{"id":"W4360989197","doi":"10.18280/ria.370118","title":"Human Brain Tumor Detection and Segmentation for MR Image","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Segmentation; Image segmentation; Image (mathematics); Human brain; Computer science; Pattern recognition (psychology); Psychology; Neuroscience","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":[0.000381174,0.0001126428,0.0001019273,0.0001730892,0.0004844881,0.0001092783,0.0001156239,0.00003989747,0.0000915867],"category_scores_gemma":[0.0005848181,0.0001210692,0.00005588509,0.0006139519,0.0001134836,0.0002046768,0.00003125108,0.00009815602,0.0004166093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004168245,"about_ca_system_score_gemma":0.0000096268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000760851,"about_ca_topic_score_gemma":0.00001507683,"domain_scores_codex":[0.9988427,0.00007297318,0.000281962,0.000447302,0.0001165421,0.000238585],"domain_scores_gemma":[0.9992731,0.0002901965,0.0001117811,0.0002119927,0.00004502535,0.00006790472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001176917,0.00002287202,0.000009386997,0.00003852821,0.000001093097,0.000002601292,0.0003618507,0.0002365756,0.9727602,0.002117701,0.0005066153,0.02393081],"study_design_scores_gemma":[0.00005901292,0.0001053735,0.0002372906,0.00001216412,0.000004331239,0.00002379873,0.0009131604,0.150938,0.841051,0.002752056,0.003783219,0.000120606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8524007,0.00001193434,0.141521,0.002556727,0.0005166865,0.0009395742,0.0000204798,0.0005492239,0.001483688],"genre_scores_gemma":[0.9950421,0.00001139454,0.0001878452,0.0004127125,0.00009121996,0.0001950093,0.000007066732,0.00002304322,0.004029586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1507014,"threshold_uncertainty_score":0.5354808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07334613727851877,"score_gpt":0.3254623130316898,"score_spread":0.252116175753171,"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."}}