{"id":"W4407286870","doi":"10.31893/multiscience.2025304","title":"Early brain tumor identification and segmentation using artificial intelligence","year":2024,"lang":"en","type":"article","venue":"Multidisciplinary Science Journal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Identification (biology); Artificial intelligence; Segmentation; Computer science; Psychology; Pattern recognition (psychology); Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009463577,0.001127703,0.0007129639,0.002724779,0.0004008774,0.00153842,0.001264376,0.001207096,0.001593373],"category_scores_gemma":[0.00256122,0.0004455526,0.0009707568,0.001522045,0.0005437365,0.001398623,0.0009551989,0.001001938,0.001243553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000940432,"about_ca_system_score_gemma":0.0009953765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695772,"about_ca_topic_score_gemma":0.006499711,"domain_scores_codex":[0.9993947,0.00009814767,0.00004435429,0.0001927497,0.0001972358,0.00007279943],"domain_scores_gemma":[0.9990627,0.0003545145,0.0001775967,0.000150505,0.0002152877,0.00003942687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002167489,0.0002386351,0.008522547,0.0003028736,0.0001380528,0.0003483098,0.0001642339,0.06457067,0.06452954,0.005878483,0.004956194,0.8501337],"study_design_scores_gemma":[0.00001202892,0.0001356731,0.0067015,0.00007465177,0.00007083502,0.0007852917,0.0000851406,0.8773476,0.09318166,0.01250677,0.009048345,0.00005039249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05092591,0.001489519,0.9383711,0.0005911685,0.00009252177,0.0001334479,0.0003572927,0.004020187,0.00401888],"genre_scores_gemma":[0.4351631,0.001500467,0.5563102,0.0005236425,0.0001130488,0.0001285855,0.001212454,0.0002574569,0.004791024],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003695772,"threshold_uncertainty_score":0.007348537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08417461017789891,"score_gpt":0.3613667835034692,"score_spread":0.2771921733255703,"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."}}