{"id":"W4392033873","doi":"10.32920/25266718.v1","title":"Brain Tumor Classification Using Hyperspectral Image Analysis","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Hyperspectral imaging; Artificial intelligence; Pattern recognition (psychology); Computer science; Contextual image classification; Image (mathematics); Computer vision","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":[0.0003321664,0.0004335924,0.0002933231,0.001773526,0.000169314,0.0007057132,0.0002526941,0.00033194,0.001271386],"category_scores_gemma":[0.0005876584,0.0001075211,0.0004051624,0.0007739032,0.0001735971,0.000358004,0.0003174062,0.0002455553,0.0007136315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878637,"about_ca_system_score_gemma":0.0003007757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002719409,"about_ca_topic_score_gemma":0.002903519,"domain_scores_codex":[0.9997657,0.00003342892,0.00001134188,0.00005235447,0.0001047931,0.00003243584],"domain_scores_gemma":[0.9997843,0.00004836069,0.00003601279,0.00002746212,0.00008856464,0.00001540955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004880207,0.000243611,0.009222904,0.0001205146,0.000106535,0.0002634148,0.000100338,0.03616725,0.2816196,0.001527963,0.005171215,0.6649687],"study_design_scores_gemma":[0.00001310978,0.0001119207,0.0260983,0.00001507787,0.00004683863,0.0002860021,0.0001385395,0.8376386,0.1311644,0.001685811,0.002772272,0.00002902295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6771047,0.0008215362,0.3098225,0.0004022015,0.00009050978,0.0001726384,0.001450596,0.00253943,0.007596034],"genre_scores_gemma":[0.8800142,0.0004525164,0.1126796,0.00005006595,0.00004189523,0.00005923277,0.001919782,0.00007794366,0.004704796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002719409,"threshold_uncertainty_score":0.005407155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07971625213877605,"score_gpt":0.3316843715916016,"score_spread":0.2519681194528256,"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."}}