{"id":"W3033603373","doi":"","title":"Engaging the public in climate research through multi-media science communication: An example from the Canadian Arctic","year":2018,"lang":"en","type":"article","venue":"AGUFM","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Arctic; Science communication; The arctic; Media studies; Geography; Political science; Sociology; Oceanography; Science education; Geology","routes":{"ca_aff":false,"ca_fund":false,"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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01545193,0.0006059227,0.000564872,0.002723567,0.06227198,0.01335651,0.002221788,0.005451105,0.004065459],"category_scores_gemma":[0.0159629,0.0003791723,0.0005452652,0.005115799,0.01476268,0.003216055,0.009466266,0.005648723,0.0004275391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05414793,"about_ca_system_score_gemma":0.1117887,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9632866,"about_ca_topic_score_gemma":0.9808159,"domain_scores_codex":[0.9874923,0.006239694,0.0002163395,0.0006174234,0.002737291,0.0026969],"domain_scores_gemma":[0.9751946,0.01339504,0.0008765411,0.000887338,0.005749665,0.003896805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000174315,0.0001256955,0.01593357,0.0002046111,0.00005555504,0.003712343,0.8849195,0.0004930344,0.001871906,0.03148982,0.02937669,0.03164292],"study_design_scores_gemma":[0.00002101039,0.00003432465,0.01008133,0.0002363079,0.000033369,0.0002511313,0.7483022,0.0003131263,0.0004518144,0.003782117,0.2364214,0.00007185323],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5966144,0.003517827,0.004198398,0.1306106,0.00158328,0.0002101718,0.00050786,0.0001394534,0.262618],"genre_scores_gemma":[0.9643673,0.001970156,0.002122132,0.007231737,0.0001888168,0.00005864134,0.000117289,0.00008926052,0.02385466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9866435,"threshold_uncertainty_score":0.3928726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8651855237437075,"score_gpt":0.5550161823686852,"score_spread":0.3101693413750223,"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."}}