{"id":"W2205498337","doi":"10.1016/j.plrev.2012.05.006","title":"Advancing our understanding of aging using mathematical modeling of longitudinal data","year":2012,"lang":"en","type":"review","venue":"Physics of Life Reviews","topic":"Frailty in Older Adults","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Longitudinal data; Computer science; Data science; Management science; Cognitive science; Psychology; Data mining; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00194542,0.0005424192,0.006470331,0.0001715019,0.00003678851,0.000007793236,0.000653229,0.0001659656,0.00002424305],"category_scores_gemma":[0.0007702369,0.0004276509,0.0008669808,0.0005211455,0.00007573141,0.0003542073,0.0005653221,0.0004903564,0.00002144647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002297644,"about_ca_system_score_gemma":0.0004816643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001962644,"about_ca_topic_score_gemma":0.00000112127,"domain_scores_codex":[0.9953179,0.0002245395,0.002918095,0.0004861828,0.0006208246,0.0004324924],"domain_scores_gemma":[0.9946967,0.0002816116,0.002611386,0.002039404,0.0001553697,0.0002155509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000006202929,0.0002876344,0.00003802653,0.6092018,0.0005373287,0.000001831992,0.0001254626,0.00009279168,0.000009513147,0.001043677,0.00008168539,0.3885741],"study_design_scores_gemma":[0.0006978805,0.000113289,2.563317e-7,0.8400935,0.01982649,0.00009986506,0.0002737512,0.03625206,0.00001217888,0.001420798,0.1003504,0.0008595388],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003772236,0.8676792,0.130637,0.00001681071,0.0001068041,0.001170938,0.00008363478,0.00001304112,0.0002888437],"genre_scores_gemma":[0.0008434934,0.963736,0.03452257,0.000007124698,0.0005817654,0.00001007909,0.000178947,0.0001052058,0.00001479964],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3877145,"threshold_uncertainty_score":0.9998176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5847105098362467,"score_gpt":0.4751334535385271,"score_spread":0.1095770562977196,"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."}}