{"id":"W2113206757","doi":"10.1111/j.1467-9299.2007.00698.x","title":"POLICY DESIGN FOR LEGITIMACY: EXPERT KNOWLEDGE, CITIZENS, TIME AND INCLUSION IN THE UNITED KINGDOM’S BIOTECHNOLOGY SECTOR","year":2007,"lang":"en","type":"article","venue":"Public Administration","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Legitimacy; Inclusion (mineral); Narrative; Public administration; Political science; Public relations; Sociology; Law; Social science; Politics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002995573,0.00009439632,0.0001008976,0.0004514286,0.00126931,0.0001116638,0.0002659046,0.0001989103,0.00002965619],"category_scores_gemma":[0.000994499,0.00007982094,0.0000274316,0.00090003,0.0002322567,0.000185303,0.0001060568,0.0001501685,0.000004112168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001006,"about_ca_system_score_gemma":0.0005151424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001250285,"about_ca_topic_score_gemma":0.002795468,"domain_scores_codex":[0.9987571,0.0002894797,0.0001953481,0.0001801206,0.0001854719,0.0003924718],"domain_scores_gemma":[0.9990663,0.0006384098,0.00004381329,0.0001045133,0.00006552663,0.00008145074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001243033,0.0002030626,0.0001992267,0.0000135281,0.00001288583,0.000005798836,0.06856217,0.000002762839,0.005405636,0.8809588,0.00094617,0.04356567],"study_design_scores_gemma":[0.001996759,0.0007792455,0.003039115,0.00003864546,0.00001718141,0.00002601406,0.006468481,0.002787062,0.005693963,0.03827927,0.9403269,0.000547416],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5714031,0.0001589912,0.1456521,0.233055,0.0002077723,0.002332712,0.00001993213,0.0004477521,0.04672261],"genre_scores_gemma":[0.9978534,0.00002703743,0.0005478401,0.0009306933,0.000420689,0.00003970101,0.0000338311,0.000009692774,0.0001371069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9393807,"threshold_uncertainty_score":0.9762636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08998183470126617,"score_gpt":0.3905297206880784,"score_spread":0.3005478859868123,"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."}}