{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001689137,0.0001356501,0.00009314904,0.0005523061,0.001560017,0.001733286,0.0003218702,0.00003175813,0.00005358491],"category_scores_gemma":[0.0004584901,0.0001202606,0.00005043799,0.001490437,0.0007618027,0.002247859,0.0001054341,0.0003484197,0.0000908868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002292924,"about_ca_system_score_gemma":0.0002411526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005250377,"about_ca_topic_score_gemma":0.000002380928,"domain_scores_codex":[0.997877,0.0001089549,0.0004618978,0.0005798471,0.0006535263,0.0003187935],"domain_scores_gemma":[0.9992169,0.0001609622,0.0001654072,0.0001700542,0.00008557221,0.0002010637],"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":[0.00001423798,0.00003026273,0.0001538911,0.00001032461,9.742915e-7,0.00003691388,0.001307879,0.0002374574,0.9524735,0.00480256,0.000009639942,0.04092238],"study_design_scores_gemma":[0.00004548736,0.00009564492,0.01774087,0.00006257045,0.000009426802,0.001643186,0.001474207,0.4265105,0.5339408,0.0182538,0.00003988137,0.0001836496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8977837,0.00005445594,0.09811135,0.00211682,0.001545754,0.000176656,0.00000390996,0.00009546708,0.0001118941],"genre_scores_gemma":[0.9975211,0.00001419791,0.002007795,0.00007478123,0.0002234601,0.000006633956,4.308557e-7,0.00001389162,0.0001377059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.426273,"threshold_uncertainty_score":0.9997398,"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."}}