{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000573828,0.0008815344,0.00057925,0.002611132,0.0004641805,0.0007934176,0.0008603618,0.00116527,0.003474309],"category_scores_gemma":[0.001307117,0.000449324,0.0008309092,0.001248709,0.0004313946,0.0005549293,0.0006968633,0.0005032502,0.002471222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006680905,"about_ca_system_score_gemma":0.001008236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007541318,"about_ca_topic_score_gemma":0.009931077,"domain_scores_codex":[0.9995552,0.00005751523,0.00003168411,0.0001504612,0.0001377273,0.00006743927],"domain_scores_gemma":[0.9996644,0.00007096188,0.00006243586,0.00005911297,0.000119472,0.00002349148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003448201,0.0001359319,0.002311021,0.0003485153,0.00009624316,0.0003661517,0.0001513046,0.03811776,0.1455714,0.002759296,0.01280801,0.7969896],"study_design_scores_gemma":[0.00002142781,0.0001410409,0.00954971,0.00006335864,0.0000652211,0.001202147,0.0001099913,0.8631342,0.1026669,0.004996161,0.01800418,0.00004574088],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05417462,0.001673145,0.9296535,0.0003735402,0.00008951948,0.0003874862,0.001135306,0.008985932,0.00352703],"genre_scores_gemma":[0.3093868,0.001655441,0.6759648,0.0002706343,0.00008103828,0.0003846849,0.003923905,0.0006992345,0.007633453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007541318,"threshold_uncertainty_score":0.01499486,"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."}}