{"id":"W4391973206","doi":"10.1016/j.compbiomed.2024.108196","title":"Brain tumor detection based on a novel and high-quality prediction of the tumor pixel distributions","year":2024,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Pixel; Computer science; Histogram; Minimum bounding box; Artificial intelligence; Pattern recognition (psychology); Computation; Computer vision; Brain tumor; Image (mathematics); Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008471737,0.0008717149,0.001071302,0.001664482,0.000374501,0.001431275,0.001087257,0.001297587,0.001419786],"category_scores_gemma":[0.00231235,0.0003689125,0.000711373,0.001081272,0.0004472751,0.001126078,0.001084442,0.0009799373,0.00111852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003850554,"about_ca_system_score_gemma":0.000985943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003301848,"about_ca_topic_score_gemma":0.006237235,"domain_scores_codex":[0.9992969,0.00007123014,0.000034561,0.0002052584,0.0003209953,0.00007094804],"domain_scores_gemma":[0.9988193,0.0003254906,0.0001256787,0.0001523777,0.0004992314,0.00007780325],"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":[0.0008888593,0.0003486283,0.02029227,0.0002585198,0.0002128252,0.000475278,0.000118589,0.07173477,0.1615766,0.002789409,0.008224801,0.7330794],"study_design_scores_gemma":[0.00001781433,0.000056046,0.005697599,0.00001095098,0.0000506458,0.0004455196,0.00001643427,0.9694342,0.02164487,0.001518598,0.001085406,0.00002184313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04434917,0.000569822,0.951574,0.0002621483,0.00006338969,0.00005648533,0.00042938,0.001896898,0.0007988002],"genre_scores_gemma":[0.5357858,0.0008873262,0.4574159,0.0002729237,0.0002082936,0.00009872536,0.001545031,0.0002945262,0.003491512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003301848,"threshold_uncertainty_score":0.006565273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03838205991429625,"score_gpt":0.3136471672711917,"score_spread":0.2752651073568955,"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."}}