{"id":"W7010222188","doi":"","title":"Growing Knowledge Translation and Transfer (KTT) in Ontario","year":2019,"lang":"en","type":"report","venue":"The Atrium (University of Guelph)","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Research Institute for Aging, University of Waterloo; Ontario Agri-Food Innovation Alliance; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Data collection; Knowledge transfer; Selection (genetic algorithm); Knowledge translation; Best practice; Technology transfer","routes":{"ca_aff":false,"ca_fund":true,"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":[0.1030708,0.0007512523,0.001251906,0.01033584,0.01584889,0.01279204,0.00350161,0.001677617,0.009122977],"category_scores_gemma":[0.1392605,0.001398675,0.001315837,0.02516668,0.007572799,0.008655835,0.01856945,0.002452573,0.001779998],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.173586,"about_ca_system_score_gemma":0.5113967,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9098576,"about_ca_topic_score_gemma":0.9352113,"domain_scores_codex":[0.9194261,0.02793412,0.01105773,0.004453049,0.02977017,0.007358824],"domain_scores_gemma":[0.8299012,0.06473939,0.01015996,0.01646097,0.06746496,0.01127362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001591587,0.0001724052,0.01957758,0.009033714,0.000111464,0.001247391,0.2385087,0.0004526415,0.001544036,0.0296921,0.08976781,0.6097331],"study_design_scores_gemma":[0.0001468226,0.0002186169,0.07538383,0.01385273,0.0001466903,0.0004103135,0.1288922,0.0006745975,0.001460628,0.009312482,0.7693691,0.0001319648],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1836945,0.07399312,0.03154898,0.1647351,0.002403258,0.01839848,0.01553746,0.001949733,0.5077393],"genre_scores_gemma":[0.7020906,0.06799553,0.1238594,0.01068665,0.0004497552,0.01646254,0.008359769,0.0009732945,0.06912246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.826414,"threshold_uncertainty_score":0.958523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4653965965289686,"score_gpt":0.4967807378045471,"score_spread":0.03138414127557848,"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."}}