{"id":"W2571537839","doi":"10.1016/j.healthpol.2016.12.009","title":"A Knowledge Translation framework on ageing and health","year":2017,"lang":"en","type":"article","venue":"Health Policy","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":96,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; University of Toronto","funders":"World Health Organization","keywords":"Knowledge translation; Context (archaeology); Population ageing; Process (computing); Healthy ageing; Public relations; Health policy; Political science; Population; Knowledge management; Economic growth; Health care; Medicine; Computer science; Ageing; Economics; Geography; Environmental health","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":[0.06120218,0.001455171,0.001978577,0.01132945,0.006156177,0.01864442,0.00439854,0.01395904,0.02455465],"category_scores_gemma":[0.07786629,0.0009949011,0.001851533,0.008008213,0.03915582,0.02849622,0.01160497,0.009517765,0.002684128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0133781,"about_ca_system_score_gemma":0.03354446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366726,"about_ca_topic_score_gemma":0.006300527,"domain_scores_codex":[0.9520698,0.03692531,0.00314484,0.00144825,0.004743841,0.001667924],"domain_scores_gemma":[0.8355116,0.146824,0.002397873,0.00568199,0.007370815,0.002213579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001127032,0.00004132958,0.00006669878,0.0002901892,0.00001102112,0.00008310571,0.004560373,0.0004533869,0.00001979476,0.9769003,0.004862311,0.0127002],"study_design_scores_gemma":[0.00002145241,0.00001240219,0.00008052051,0.0008776318,0.00001384644,0.0000412294,0.002502308,0.0006144301,0.0000800649,0.9691746,0.02657048,0.00001119137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.00586119,0.01037097,0.1856815,0.4314916,0.003962804,0.0006638495,0.0007461323,0.0003712463,0.3608508],"genre_scores_gemma":[0.6968468,0.0171997,0.1600774,0.06853163,0.005998816,0.003754255,0.001005028,0.0002566554,0.04632969],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06120218,"threshold_uncertainty_score":0.3236719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8594445254380473,"score_gpt":0.7727539316333789,"score_spread":0.08669059380466837,"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."}}