{"id":"W3015156083","doi":"10.1017/s0714980819000850","title":"Building Nutrition into a Falls Risk Screening Program for Older Adults in Family Health Teams in North Eastern Ontario","year":2020,"lang":"en","type":"article","venue":"Canadian Journal on Aging / La Revue canadienne du vieillissement","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Waterloo","funders":"Canadian Institutes of Health Research","keywords":"Work (physics); Medicine; Gerontology; Risk assessment; Population; Thematic analysis; Family medicine; Environmental health; Psychology; Qualitative research; Engineering; Sociology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001816135,0.0002243246,0.0002096679,0.0005651598,0.00770884,0.001264578,0.001214805,0.000537737,0.002217173],"category_scores_gemma":[0.003498031,0.0004763808,0.0003504222,0.0006715872,0.001388254,0.0007457156,0.002290347,0.0007693956,0.0002012128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02789002,"about_ca_system_score_gemma":0.07387873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8348619,"about_ca_topic_score_gemma":0.9616534,"domain_scores_codex":[0.9983897,0.0004183936,0.00009540118,0.0001321833,0.0003739209,0.000590343],"domain_scores_gemma":[0.9953393,0.0003062935,0.0004331744,0.00005729007,0.0008548273,0.003009133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004317424,0.003157108,0.5986173,0.001193573,0.00008328336,0.004806122,0.2088082,0.0005968062,0.004680675,0.0005642403,0.01310261,0.1639582],"study_design_scores_gemma":[0.0001658306,0.001937304,0.75115,0.0009597756,0.00008182944,0.0004013343,0.217219,0.0006255471,0.0005824868,0.0002878351,0.02652903,0.00005997719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912811,0.0003447207,0.0002933544,0.00243142,0.00003415815,0.0008836846,0.0001097764,0.00002203013,0.00459988],"genre_scores_gemma":[0.9884051,0.0009835132,0.004096301,0.001146025,0.00002312908,0.0005531876,0.0001598176,0.00001082246,0.004622071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1651381,"threshold_uncertainty_score":0.3322213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750941206470279,"score_gpt":0.289323665352275,"score_spread":0.2718142532875722,"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."}}