{"id":"W2398808193","doi":"10.1093/gerona/glw089","title":"Heterogeneity of Human Aging and Its Assessment","year":2016,"lang":"en","type":"article","venue":"The Journals of Gerontology Series A","topic":"Frailty in Older Adults","field":"Medicine","cited_by":183,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research","keywords":"Biomarker; Receiver operating characteristic; Healthy aging; Predictive power; Gerontology; Medicine; Discriminative model; Proportional hazards model; Demography; Statistics; Internal medicine; Biology; Computer science; Mathematics; Artificial intelligence; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004649408,0.00009599603,0.0003820559,0.00005364584,0.00007074056,0.000003709237,0.000119868,0.0000606546,0.0001736933],"category_scores_gemma":[0.0001109446,0.00004873714,0.00006068497,0.00003809099,0.0002847578,0.0001258002,0.00007616697,0.0001119517,0.000001406726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002528682,"about_ca_system_score_gemma":0.00003879134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002674794,"about_ca_topic_score_gemma":0.0001880858,"domain_scores_codex":[0.9990771,0.0001119896,0.0003680683,0.0001029111,0.0001637267,0.0001761675],"domain_scores_gemma":[0.999102,0.0001279159,0.0002913702,0.0002455286,0.000167069,0.00006609633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002044113,0.0001055258,0.1273206,0.0001637071,0.0003758312,0.00002365276,0.0008958514,6.318604e-7,0.8599436,0.001575878,0.0006275869,0.008762652],"study_design_scores_gemma":[0.002091015,0.001271597,0.7435643,0.0006277407,0.0001762498,0.001422137,0.0004591091,0.000005812828,0.2483408,0.001311171,0.0006250998,0.0001050042],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759955,0.002549028,0.00009215029,0.0203658,0.00007832745,0.0001337396,0.000006514394,0.00001011279,0.0007688036],"genre_scores_gemma":[0.9981343,0.0007195417,0.0003382436,0.0001298163,0.00005490329,0.000003458542,3.730569e-7,0.000008976337,0.0006104127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6162437,"threshold_uncertainty_score":0.1987443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07944281671878828,"score_gpt":0.3898600066164384,"score_spread":0.3104171898976502,"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."}}