{"id":"W2296329795","doi":"10.15273/pnsis.v47i1.3382","title":"THE USE AND INFLUENCE OF SCIENTIFIC INFORMATION IN ENVIRONMENTAL POLICY MAKING: LESSONS LEARNED FROM NOVA SCOTIA","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Nova Scotian Institute of Science","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Nova scotia; Context (archaeology); Public policy; Science policy; Political science; Information needs; Process (computing); Policy analysis; Policy making; Environmental planning; Business; Public administration; Geography; Library science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.006746258,0.0002878354,0.0004317265,0.001305307,0.004058204,0.006045287,0.0009911796,0.000800201,0.002035842],"category_scores_gemma":[0.01930229,0.0002570819,0.0003391396,0.002501646,0.003715616,0.001682282,0.003706328,0.002235022,0.0002427757],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05010144,"about_ca_system_score_gemma":0.09180456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9662361,"about_ca_topic_score_gemma":0.9790742,"domain_scores_codex":[0.9958931,0.001355595,0.0002604992,0.0003023524,0.0009474996,0.001240966],"domain_scores_gemma":[0.9721256,0.01630823,0.001469312,0.001029049,0.006627366,0.002440426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001207302,0.0005909135,0.2879122,0.004158895,0.0003195766,0.02017869,0.2005123,0.006917639,0.004033759,0.07415813,0.04071147,0.3592992],"study_design_scores_gemma":[0.000121803,0.0002456353,0.5757489,0.00880293,0.0002519299,0.0008595202,0.1787467,0.003132663,0.002186405,0.009103242,0.2205946,0.0002056895],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7267842,0.02400154,0.001111967,0.07503462,0.0004325626,0.0002450225,0.000795527,0.0000416545,0.171553],"genre_scores_gemma":[0.9758463,0.01103726,0.0009039335,0.003046732,0.0000389029,0.00003976723,0.0002335031,0.00001796314,0.008835656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9498985,"threshold_uncertainty_score":0.3635131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03927688293312559,"score_gpt":0.2607410151374448,"score_spread":0.2214641322043192,"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."}}