{"id":"W3006261855","doi":"10.2196/16678","title":"Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Frailty in Older Adults","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Support vector machine; Decision tree; Artificial intelligence; Random forest; Logistic regression; Population; Computer science; Artificial neural network; Medicine; Gerontology; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002954545,0.0002104146,0.0004735615,0.0001192314,0.00009595716,0.00002634206,0.0001936028,0.0002912624,0.0002542853],"category_scores_gemma":[0.001657201,0.0001836537,0.0001168288,0.0003651343,0.00009313228,0.0002924215,0.00009307654,0.001047483,0.00004961583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007882242,"about_ca_system_score_gemma":0.000277815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000213989,"about_ca_topic_score_gemma":0.00004842096,"domain_scores_codex":[0.9978175,0.00003300968,0.0008420102,0.0001615854,0.0007512677,0.000394627],"domain_scores_gemma":[0.9987471,0.000254251,0.0001330335,0.0001748826,0.0001010901,0.0005896616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003163013,0.002742096,0.05969992,0.01800872,0.001188207,0.0001785625,0.5430017,0.125113,0.0001337487,0.005565405,0.04098544,0.2002203],"study_design_scores_gemma":[0.003728227,0.0008262483,0.000534958,0.000320869,0.00004658827,0.00003995231,0.006879482,0.9837494,0.000024018,0.0001491512,0.003528353,0.0001727572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6456835,0.0002237436,0.3140955,0.02674793,0.0002161111,0.003981697,0.0002277798,0.0006401315,0.008183675],"genre_scores_gemma":[0.9897536,0.00004378635,0.005995903,0.002710155,0.0002350131,0.0003900492,0.000736074,0.00003149838,0.0001039357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8586364,"threshold_uncertainty_score":0.748918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06628481390935935,"score_gpt":0.3156747560770438,"score_spread":0.2493899421676845,"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."}}