{"id":"W3141541960","doi":"10.1007/s12603-021-1626-2","title":"County-Level Characteristics Driving Malnutrition Death Rates among Older Adults in Texas","year":2021,"lang":"en","type":"article","venue":"The journal of nutrition health & aging","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada","funders":"","keywords":"Malnutrition; Poverty; Environmental health; Socioeconomic status; Medicine; Gerontology; Population; Geography; Demography; Mortality rate; Metropolitan area; Cause of death; Disease; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000379689,0.0001829488,0.0001988323,0.0007623051,0.000586948,0.0007439652,0.000365226,0.000328961,0.002808139],"category_scores_gemma":[0.001964652,0.0002551662,0.0004540516,0.001161704,0.0002369766,0.0004706714,0.0007318147,0.0005718517,0.0002720119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005920542,"about_ca_system_score_gemma":0.0008136088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06192869,"about_ca_topic_score_gemma":0.1293017,"domain_scores_codex":[0.9997457,0.00003753034,0.00003238958,0.00006720864,0.000023695,0.00009349087],"domain_scores_gemma":[0.9984899,0.0002173373,0.000642709,0.00008428727,0.0001868722,0.0003788186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002967059,0.0000189383,0.9991707,0.000003484638,0.00002141391,0.00001945678,0.00008300629,0.00003788151,0.00002859329,0.00001798014,0.0001849366,0.0003839998],"study_design_scores_gemma":[0.000001652157,0.00001687195,0.9989624,0.000005660024,0.00001514282,0.0000340669,0.0006340459,0.0001530447,0.00001271666,0.00002005419,0.0001423385,0.000002086076],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985625,0.00007276858,0.0000362494,0.00009588849,0.000006006047,0.00000366173,0.000862011,0.000003131829,0.0003578443],"genre_scores_gemma":[0.9989849,0.00005327816,0.00002887813,0.00002948344,0.000008646559,0.000004139858,0.0005403216,0.000001558562,0.000348715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06192869,"threshold_uncertainty_score":0.1231365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04542197342213483,"score_gpt":0.3499492804970528,"score_spread":0.3045273070749179,"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."}}