{"id":"W2180823206","doi":"10.1177/2158244015604193","title":"The Mobilization of Scientific Evidence by Public Policy Analysts","year":2015,"lang":"en","type":"article","venue":"SAGE Open","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Mobilization; Mediation; Public policy; Field (mathematics); Path analysis (statistics); Government (linguistics); Policy analysis; Political science; Public economics; Test (biology); Positive economics; Psychology; Econometrics; Economics; Public administration; Computer science","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.274198,0.0006966455,0.001567116,0.01456878,0.006798176,0.02892391,0.002784272,0.005624406,0.008305745],"category_scores_gemma":[0.5680684,0.001390451,0.001161829,0.01184926,0.01881625,0.01365231,0.0168084,0.007494759,0.001108796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01290256,"about_ca_system_score_gemma":0.04632067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007972872,"about_ca_topic_score_gemma":0.008693052,"domain_scores_codex":[0.5976369,0.3343979,0.009393171,0.008729685,0.04143274,0.008409772],"domain_scores_gemma":[0.1581007,0.7517034,0.03563195,0.03005325,0.02008102,0.004429696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007577147,0.000568431,0.1326423,0.002582412,0.001157417,0.000894706,0.07357515,0.003683052,0.002528621,0.3972278,0.01799281,0.3663897],"study_design_scores_gemma":[0.0005718562,0.0005050894,0.08539321,0.008480428,0.0009698345,0.0006203514,0.05573308,0.01014689,0.00767041,0.6201404,0.2094477,0.0003207548],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4080552,0.01392702,0.05273207,0.2180645,0.0008077871,0.001606691,0.0008005165,0.0004241037,0.3035821],"genre_scores_gemma":[0.9720874,0.002974977,0.0148766,0.005914505,0.0002784138,0.000726451,0.0001408351,0.00006598632,0.002934729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9932019,"threshold_uncertainty_score":0.8950431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5517309626375979,"score_gpt":0.584428211461108,"score_spread":0.03269724882351011,"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."}}