{"id":"W2536097953","doi":"","title":"Micronutrients in Long-Term Care (LTC): Issues and opportunities for improvement","year":2014,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Long-term care; Micronutrient; Term (time); Business; Gerontology; Medicine; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04746823,0.0009276669,0.003129089,0.00328783,0.003918302,0.009410012,0.003726859,0.005955282,0.009262158],"category_scores_gemma":[0.08448715,0.0005756672,0.003567277,0.00676256,0.002906927,0.01131015,0.006464561,0.006356212,0.001164257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009897311,"about_ca_system_score_gemma":0.06570903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03377502,"about_ca_topic_score_gemma":0.0682798,"domain_scores_codex":[0.9877703,0.006407775,0.00243509,0.0007206086,0.001463366,0.001202726],"domain_scores_gemma":[0.9149992,0.05066332,0.009075249,0.001982715,0.01667747,0.006602138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003896953,0.0004810715,0.01838664,0.1222836,0.0007949809,0.0004395748,0.005785463,0.0005236841,0.0004466108,0.01506862,0.1086839,0.7267162],"study_design_scores_gemma":[0.0007347194,0.001590974,0.0583872,0.39354,0.002920871,0.001016392,0.03724365,0.001279741,0.0005120993,0.03125768,0.4712984,0.0002183216],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004518006,0.6381766,0.001408222,0.3480966,0.002898578,0.0003140556,0.0003601623,0.00009970814,0.004128041],"genre_scores_gemma":[0.068978,0.8410782,0.02732775,0.05491609,0.003418493,0.001999159,0.0007687742,0.00003524365,0.001478365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04746823,"threshold_uncertainty_score":0.251039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02866019534648617,"score_gpt":0.2826432646020628,"score_spread":0.2539830692555766,"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."}}