{"id":"W1857416707","doi":"10.1007/11866565_41","title":"Realistic Simulated MRI and SPECT Databases","year":2006,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Computer science; Ictal; Image registration; Ictal-Interictal SPECT Analysis by SPM; Artificial intelligence; Spect imaging; Neuroimaging; Pattern recognition (psychology); Nuclear medicine; Epilepsy; Medicine","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":[0.001562867,0.0006303546,0.000893601,0.001031393,0.0003046145,0.001212479,0.001987674,0.00130119,0.003301981],"category_scores_gemma":[0.006665839,0.0006017066,0.0008395987,0.001203447,0.0005699456,0.0006644774,0.0009462793,0.000634816,0.0006484431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007596311,"about_ca_system_score_gemma":0.0009441876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003553412,"about_ca_topic_score_gemma":0.002587596,"domain_scores_codex":[0.9989262,0.0004309826,0.00009768949,0.0001461418,0.0003310278,0.00006796276],"domain_scores_gemma":[0.9964063,0.002103105,0.0002366447,0.0005913546,0.0005396561,0.0001230322],"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":[0.0005144943,0.000173536,0.0031184,0.0001276527,0.0000712522,0.0003929117,0.0001009771,0.9764589,0.005009142,0.002907139,0.001252144,0.009873482],"study_design_scores_gemma":[0.0000976481,0.0001817411,0.001830796,0.0000185828,0.00003312192,0.0005620048,0.00006551596,0.9827049,0.007856864,0.003123287,0.003481098,0.00004446895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5391632,0.0004913115,0.4406756,0.0005845889,0.0001281859,0.0008833787,0.009306074,0.001661878,0.007105723],"genre_scores_gemma":[0.8752554,0.0003265399,0.1113179,0.0001698733,0.00003181528,0.0009603819,0.009823108,0.0002887649,0.001826273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003553412,"threshold_uncertainty_score":0.01104623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01869263148852085,"score_gpt":0.323540615611292,"score_spread":0.3048479841227711,"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."}}