{"id":"W2944799710","doi":"10.3148/cjdpr-2019-013","title":"Provincial Differences in Long-Term Care Menu Variety and Food Intake for Residents who Consume a Regular Texture","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Dietetic Practice and Research","topic":"Nutrition, Health and Food Behavior","field":"Nursing","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Waterloo; University of Alberta; University of Manitoba; Université de Moncton","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Variety (cybernetics); Food intake; Environmental health; Food group; Healthy food; Gerontology; Demography; Food science; Mathematics; Biology; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0004374637,0.0001299639,0.0002230094,0.0005371044,0.001047794,0.0006502297,0.0004164076,0.0002128133,0.002206286],"category_scores_gemma":[0.002800555,0.000169466,0.0004893134,0.001255609,0.0002884862,0.0002151264,0.0004456891,0.0004228762,0.0001709585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005005891,"about_ca_system_score_gemma":0.004716487,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9206678,"about_ca_topic_score_gemma":0.9658017,"domain_scores_codex":[0.9995838,0.00005032462,0.00002955933,0.00006907208,0.0001049364,0.0001622611],"domain_scores_gemma":[0.9984223,0.0001785712,0.0004797504,0.00009722625,0.0005455129,0.0002767239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001901602,0.00003938594,0.9951952,0.00001319528,0.00004822142,0.00003160267,0.0006649871,0.00007718,0.0001923113,0.00005198736,0.0003728609,0.003122934],"study_design_scores_gemma":[0.000002629368,0.00002290517,0.9991385,0.000006697851,0.00001146606,0.000020662,0.0004953207,0.000102801,0.00002944001,0.00001263978,0.000153625,0.000003235908],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979813,0.0001055154,0.00007816862,0.00005961389,0.000003496986,0.000006704317,0.0007111116,0.000005542597,0.001048712],"genre_scores_gemma":[0.9990265,0.00003799554,0.000112629,0.00002041177,9.835725e-7,0.000002868668,0.0003602542,0.000003737561,0.000434541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07933217,"threshold_uncertainty_score":0.1595987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210353819699694,"score_gpt":0.3740929845476389,"score_spread":0.321989446350642,"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."}}