{"id":"W4288766512","doi":"10.2196/38464","title":"Evolving Hybrid Partial Genetic Algorithm Classification Model for Cost-effective Frailty Screening: Investigative Study","year":2022,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Frailty in Older Adults","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetic algorithm; Computer science; Logistic regression; Set (abstract data type); Data mining; Support vector machine; Random forest; Decision tree; Feature (linguistics); Index (typography); Artificial intelligence; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004222047,0.0002496887,0.0003522848,0.0001866402,0.0005387543,0.00004678897,0.0001915271,0.00003482102,0.00006871588],"category_scores_gemma":[0.0002335576,0.0002704324,0.0001232131,0.0002892712,0.000105708,0.0001614519,0.0002011164,0.0004855111,0.000006879472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004249811,"about_ca_system_score_gemma":0.0001533156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005138207,"about_ca_topic_score_gemma":0.0000052171,"domain_scores_codex":[0.9977794,0.0001934307,0.0003784352,0.0006454121,0.0005671608,0.0004361957],"domain_scores_gemma":[0.9987402,0.0002361513,0.0001912707,0.0004481233,0.0001832959,0.0002009608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004342076,0.002098957,0.05484364,0.0002202556,0.0006303495,0.0001600763,0.03370373,0.04512597,0.01188065,0.00006903123,0.01662713,0.834206],"study_design_scores_gemma":[0.003327572,0.0006738587,0.1018649,0.00005685237,0.0001442001,0.00003569944,0.003114101,0.8884141,0.0008812959,0.0002874098,0.0009512731,0.0002487167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4453354,0.0001333569,0.5362336,0.001505385,0.0002596871,0.01586097,0.00014451,0.0002943236,0.0002328212],"genre_scores_gemma":[0.9506956,9.802015e-7,0.03232427,0.0004848502,0.0002577191,0.01534879,0.0001321316,0.00006990158,0.000685743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8432882,"threshold_uncertainty_score":0.9999748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0860540941344495,"score_gpt":0.3516168879369881,"score_spread":0.2655627938025386,"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."}}