{"id":"W2724925318","doi":"10.1093/geroni/igx004.926","title":"MAKING THE MOST OF MEALTIMES: WHO IS PRESCRIBED MODIFIED TEXTURE FOODS IN CANADIAN LONG-TERM CARE","year":2017,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Dysphagia Assessment and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Toronto; University Health Network; Research Institute for Aging; Toronto Rehabilitation Institute; University of Waterloo","funders":"","keywords":"Medicine; Medical prescription; Malnutrition; Cross-sectional study; Dysphagia; Terminology; Dementia; Gerontology; Family medicine; Environmental health; Nursing; Surgery; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0008932779,0.0002964443,0.0005019306,0.001236146,0.003780382,0.001460458,0.001739219,0.0006739265,0.00147341],"category_scores_gemma":[0.003700171,0.0003826905,0.000772606,0.004579069,0.0008089557,0.0006992306,0.001242993,0.0009952926,0.0001678324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02595823,"about_ca_system_score_gemma":0.02735038,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9931398,"about_ca_topic_score_gemma":0.9963433,"domain_scores_codex":[0.9985234,0.00008266514,0.0001025405,0.0001716531,0.0005988563,0.000520901],"domain_scores_gemma":[0.9977598,0.0001284599,0.0006598287,0.00006586649,0.0007894238,0.0005966706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007841891,0.00004957156,0.9873558,0.00006761957,0.00003974524,0.0001094965,0.002871846,0.00005355963,0.0001311777,0.00006236945,0.001210803,0.00796973],"study_design_scores_gemma":[0.000003726336,0.00002796552,0.994335,0.00007297145,0.0000212495,0.0000805392,0.004648918,0.0001491343,0.00003280676,0.00002076402,0.0005912698,0.0000156875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949501,0.000922457,0.00006255716,0.0005110833,0.00001340978,0.00003541877,0.001726051,0.000006901323,0.001772136],"genre_scores_gemma":[0.9977741,0.0007372846,0.000155773,0.0001862012,0.000004435639,0.00001431582,0.0008002698,0.000003427665,0.0003241908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02595823,"threshold_uncertainty_score":0.188341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09754246241603898,"score_gpt":0.448903372757771,"score_spread":0.351360910341732,"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."}}