{"id":"W2500714020","doi":"10.1186/s12961-016-0130-3","title":"Development of training for medicines-oriented policymakers to apply evidence","year":2016,"lang":"en","type":"article","venue":"Health Research Policy and Systems","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Bruyère; Canadian Agency for Drugs and Technologies in Health; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Knowledge translation; Scope (computer science); Medical education; Context (archaeology); Medicine; Health services research; Best practice; Health administration; Knowledge management; Public health; Nursing; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03778685,0.0001678743,0.0005785583,0.001167272,0.001933772,0.00001380337,0.0003320565,0.0001215765,0.00002764872],"category_scores_gemma":[0.03489022,0.0001114467,0.00003003808,0.001513272,0.0002541609,0.0001938384,0.0001824445,0.0002990939,0.00008997356],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001362335,"about_ca_system_score_gemma":0.01764618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004883069,"about_ca_topic_score_gemma":0.001165554,"domain_scores_codex":[0.9905549,0.00292146,0.00206921,0.00051326,0.001447575,0.002493652],"domain_scores_gemma":[0.9789334,0.01698193,0.0004898446,0.0004413767,0.001296054,0.001857426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005298933,0.0000422749,0.006399026,0.01323185,0.00004002636,0.000001392236,0.520178,0.000002106301,0.009573045,0.1281727,0.1406341,0.1811956],"study_design_scores_gemma":[0.001565325,0.0005399947,0.009029464,0.005470093,0.000001439263,0.000003838496,0.03650875,0.00006168949,0.00007526291,0.0001917747,0.946399,0.000153377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3874776,0.0005014664,0.04732511,0.5404271,0.001093576,0.02006153,0.0004560995,0.0001635197,0.002493907],"genre_scores_gemma":[0.9615826,0.000245116,0.006377121,0.02185034,0.001682496,0.00499654,0.000003831065,0.00004586391,0.003216075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8057649,"threshold_uncertainty_score":0.9993656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9566925383569985,"score_gpt":0.7882827987465426,"score_spread":0.1684097396104559,"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."}}