{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002153801,0.0001426499,0.0002274033,0.0002925679,0.00002562498,0.00003548036,0.0002666641,0.00004237156,0.00004021595],"category_scores_gemma":[0.0001706681,0.0001343598,0.00005360347,0.0004684603,0.0001514084,0.0001553984,0.0001752241,0.0002622306,0.00002133289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035063,"about_ca_system_score_gemma":0.00004022632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007450325,"about_ca_topic_score_gemma":6.568006e-7,"domain_scores_codex":[0.9983967,0.00003007649,0.0002009893,0.0005209463,0.0004359258,0.0004153938],"domain_scores_gemma":[0.9993418,0.00002190224,0.00005120561,0.0004623742,0.00001555393,0.000107178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006551218,0.00005411547,0.8650551,0.00005345158,0.000004949847,0.0004713011,0.0002446281,0.00003855483,0.03367687,0.000008129663,0.09865491,0.001672434],"study_design_scores_gemma":[0.001633823,0.0001751935,0.8182005,0.0001621993,0.00002449754,0.00003448533,0.0002085509,0.01110233,0.002877716,0.00001754854,0.1653285,0.0002345868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678956,0.00010419,0.008953196,0.002465047,0.002917811,0.0006074872,0.00001215665,0.00012866,0.0169159],"genre_scores_gemma":[0.9584301,0.00001604812,0.006010197,0.006880971,0.0000536548,0.00002536356,0.000003847289,0.00001971043,0.02856017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06667364,"threshold_uncertainty_score":0.5479034,"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."}}