{"id":"W2166636660","doi":"10.1109/icpr.2006.318","title":"Bayesian MS Lesion Classification Modeling Regional and Local Spatial Information","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Posterior probability; Voxel; Bayesian probability; Entropy (arrow of time); Principle of maximum entropy; Multivariate statistics; Spatial analysis; Probabilistic logic; Mathematics; Machine learning; Statistics","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":[0.002162155,0.0006329996,0.000837307,0.001306189,0.0004732429,0.001154055,0.001216996,0.001114024,0.001378808],"category_scores_gemma":[0.005508208,0.000581964,0.0008906166,0.0005556266,0.0006672655,0.001094347,0.000774644,0.0009106116,0.0005765148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070389,"about_ca_system_score_gemma":0.001136185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009356261,"about_ca_topic_score_gemma":0.0114982,"domain_scores_codex":[0.9990307,0.0003263198,0.00005362051,0.0001930812,0.0003045739,0.00009179578],"domain_scores_gemma":[0.9982439,0.001003936,0.000220257,0.000147827,0.0003252401,0.00005880355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003257753,0.0001127094,0.00386706,0.0001097744,0.0001290913,0.0001048584,0.0001463861,0.6851382,0.01380439,0.01678257,0.002488533,0.2769906],"study_design_scores_gemma":[0.00001130288,0.00002260406,0.001164041,0.00001010128,0.00001546173,0.00006220171,0.000008539186,0.9871103,0.001100156,0.009998446,0.0004758197,0.00002107041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02151641,0.0001913406,0.9769285,0.0001283798,0.00001039863,0.00003420509,0.0001165521,0.000413778,0.000660393],"genre_scores_gemma":[0.5496826,0.0003238554,0.4457541,0.0001143458,0.00008419984,0.0002072204,0.0005430705,0.0001684589,0.00312215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009356261,"threshold_uncertainty_score":0.01860362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841240055342877,"score_gpt":0.2455650570422901,"score_spread":0.2271526564888613,"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."}}