{"id":"W2990569188","doi":"10.3389/fnagi.2019.00348","title":"Predicted Brain Age After Stroke","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Health and Medical Research Council; Australian Research Council; Medical Research Council; Universität Zürich","keywords":"Stroke (engine); Biomarker; Medicine; Brain aging; Aging brain; Brain damage; Internal medicine; Cardiology; Physical medicine and rehabilitation; Disease; Biology","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":[0.0006550355,0.0004428479,0.0003769991,0.0008671217,0.0001708581,0.0004639397,0.0002340227,0.0003753676,0.001930933],"category_scores_gemma":[0.003222895,0.00009902479,0.0004002864,0.0004377371,0.00008281434,0.0004210434,0.0003283535,0.0003632571,0.0005160893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018442,"about_ca_system_score_gemma":0.000194878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002833373,"about_ca_topic_score_gemma":0.003682679,"domain_scores_codex":[0.9997751,0.00006353368,0.00002289707,0.00007126559,0.00003683161,0.00003040685],"domain_scores_gemma":[0.9992434,0.0002087256,0.0002550441,0.00004635294,0.0001767614,0.00006970016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006542919,0.00008393551,0.965009,0.00008368636,0.0001856502,0.00009264216,0.0001658218,0.0009856239,0.0006022052,0.0002191162,0.001037761,0.0308803],"study_design_scores_gemma":[0.00001270897,0.0003697248,0.9929833,0.00003921772,0.0001326158,0.0003189669,0.00009765018,0.003339791,0.0006058487,0.0006393782,0.001446052,0.00001464794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891917,0.002148195,0.00285421,0.0001502663,0.00005875562,0.00005020461,0.002734969,0.00007180266,0.002739928],"genre_scores_gemma":[0.9956376,0.0005087079,0.001392297,0.00003097346,0.00003028968,0.00003249583,0.001551558,0.000005688049,0.0008104316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002833373,"threshold_uncertainty_score":0.006459594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008163781948036816,"score_gpt":0.2368373535109842,"score_spread":0.2286735715629474,"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."}}