{"id":"W2780757550","doi":"10.1139/facets-2017-0087","title":"Keeping science’s seat at the decision-making table: Mechanisms to motivate policy-makers to keep using scientific information in the age of disinformation","year":2017,"lang":"en","type":"article","venue":"FACETS","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mitacs","funders":"Natural Resources Canada; National Research Council Canada; Agriculture and Agri-Food Canada; Canadian Space Agency; Health Canada; Environment and Climate Change Canada; Fisheries and Oceans Canada; Canadian Food Inspection Agency; Mitacs; Public Health Agency; Canadian Nuclear Safety Commission; Public Health Agency of Canada","keywords":"Disinformation; Public relations; Scientific evidence; Government (linguistics); Outreach; Work (physics); Political science; Position (finance); Process (computing); Public policy; Public administration; Business; Computer science; Engineering; Law; Social media","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1734649,0.0009843826,0.001127904,0.006040321,0.02036426,0.03139359,0.00494504,0.02232525,0.01168764],"category_scores_gemma":[0.2660555,0.001493967,0.001367621,0.004093003,0.04383494,0.01813843,0.02105387,0.01799201,0.001873676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02607607,"about_ca_system_score_gemma":0.1101329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03071255,"about_ca_topic_score_gemma":0.04417467,"domain_scores_codex":[0.8768579,0.08990829,0.004425666,0.005621625,0.01334576,0.009840742],"domain_scores_gemma":[0.6117079,0.2810363,0.03208178,0.01845986,0.025734,0.03098019],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003227257,0.0007807717,0.02271515,0.001247464,0.0003971555,0.001667698,0.05525008,0.003901305,0.002245075,0.6633332,0.08531736,0.162822],"study_design_scores_gemma":[0.0004811408,0.0002982574,0.007093715,0.001987559,0.0001896955,0.0003691412,0.02122786,0.003663208,0.002087824,0.6211765,0.3410874,0.0003376206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03089314,0.002869268,0.04474329,0.8208814,0.001731563,0.001039114,0.0001026284,0.0003774108,0.09736221],"genre_scores_gemma":[0.791866,0.002440323,0.07725491,0.1127303,0.001326052,0.001134817,0.00007200813,0.0001465,0.01302917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8265351,"threshold_uncertainty_score":0.9173812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05026186289946618,"score_gpt":0.3797295475353752,"score_spread":0.329467684635909,"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."}}