{"id":"W3199572846","doi":"10.1212/wnl.0000000000012698","title":"Multicenter Validation of a Deep Learning Detection Algorithm for Focal Cortical Dysplasia","year":2021,"lang":"en","type":"article","venue":"Neurology","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Cortical dysplasia; False positive paradox; Confidence interval; Medicine; Cohort; Magnetic resonance imaging; Epilepsy; Temporal lobe; Artificial intelligence; Nuclear medicine; Radiology; Pathology; Internal medicine; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007426948,0.00005384644,0.000143985,0.00003411477,0.00004050444,0.000003404183,0.00001633149,0.00007420671,0.00007952967],"category_scores_gemma":[0.0003210117,0.00004795507,0.00006147709,0.00006171054,0.00003928622,0.00001866381,0.0000183264,0.0001946478,0.00001394372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001226198,"about_ca_system_score_gemma":0.00002715965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007781656,"about_ca_topic_score_gemma":0.00002011138,"domain_scores_codex":[0.9993112,0.0001148922,0.000132861,0.000167644,0.0001026189,0.0001707984],"domain_scores_gemma":[0.9994482,0.0002243186,0.00003039599,0.00008720437,0.0001371697,0.00007267052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003754806,0.001075989,0.1447037,0.0001227615,0.0002522767,0.0006239879,0.0001696588,0.00006089377,0.1578237,0.00008341638,0.00002405578,0.6913048],"study_design_scores_gemma":[0.009599494,0.01542507,0.2524012,0.00001265235,0.0002656564,0.0006195119,0.00004024372,0.1901927,0.5279372,0.0001324663,0.003272208,0.0001015913],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9391167,0.00005686635,0.05968222,0.0006182733,0.0001176515,0.0002389504,0.000002239881,0.00002066939,0.0001464508],"genre_scores_gemma":[0.9970819,0.00002516274,0.002500923,0.0001680503,0.00007154388,0.00004411998,0.00003901559,0.00001005707,0.00005923293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6912032,"threshold_uncertainty_score":0.1955551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01724007166404138,"score_gpt":0.3052645768247327,"score_spread":0.2880245051606913,"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."}}