{"id":"W4393102300","doi":"10.2196/52170","title":"Developing a Personalized Meal Recommendation System for Chinese Older Adults: Observational Cohort Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chinese Academy of Medical Sciences","keywords":"Observational study; Meal; Cohort; Medicine; Cohort study; Gerontology; Internal medicine","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":[0.001051451,0.0001444495,0.0001442756,0.000151102,0.0002922646,0.0001264811,0.0001578612,0.00008649017,0.00003716941],"category_scores_gemma":[0.0001136273,0.0001239113,0.00009789724,0.0002837015,0.0000694097,0.00002453427,0.00010324,0.0001222532,0.00002207659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580541,"about_ca_system_score_gemma":0.0003089661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001438892,"about_ca_topic_score_gemma":0.00001995689,"domain_scores_codex":[0.9984112,0.0002251735,0.0002860977,0.0003794002,0.0003837545,0.0003143862],"domain_scores_gemma":[0.9988851,0.00009115064,0.0000382718,0.0001713263,0.000713094,0.00010105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01284753,0.006481161,0.5725015,0.02310622,0.0038959,0.00005181897,0.0612878,0.00004044025,0.028326,0.0211049,0.2143473,0.05600933],"study_design_scores_gemma":[0.01248695,0.002956844,0.8490672,0.00127249,0.00008261872,0.00003859699,0.03962342,0.0105942,0.007633823,0.001454943,0.07356924,0.001219748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877331,0.0005449674,0.007897702,0.000505813,0.0002726224,0.002352254,0.0002427399,0.00004056864,0.0004102653],"genre_scores_gemma":[0.9944223,0.00006540617,0.0005054023,0.00004900863,0.0004158072,0.002279451,0.001952894,0.00002574913,0.0002840052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2765656,"threshold_uncertainty_score":0.5052955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05850357422769366,"score_gpt":0.4167254964412198,"score_spread":0.3582219222135261,"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."}}