{"id":"W3159520786","doi":"10.17645/pag.v9i2.3754","title":"Public Engagement in Climate Communication on China’s Weibo: Network Structure and Information Flows","year":2021,"lang":"en","type":"article","venue":"Politics and Governance","topic":"Social Media and Politics","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Social Sciences and Humanities Research Council of Canada; Memorial University of Newfoundland","keywords":"Microblogging; Homophily; Deliberation; China; Social network analysis; Public engagement; Climate change; Social media; Political science; Politics; Public relations; Sociology; Social science; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002063343,0.00006259336,0.00009160505,0.00001280792,0.0003815216,0.0001324124,0.00007315358,0.00006957067,0.00002619681],"category_scores_gemma":[0.0003780591,0.00006585677,0.00001216841,0.0001196217,0.00009016789,0.0003185041,0.00006191977,0.0001608288,0.000002454879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000846925,"about_ca_system_score_gemma":0.0001114492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002009843,"about_ca_topic_score_gemma":0.00413635,"domain_scores_codex":[0.9991443,0.0001593865,0.0001391655,0.00007385105,0.0001773185,0.0003060474],"domain_scores_gemma":[0.9995368,0.0001323465,0.00007416376,0.0001171152,0.0000473391,0.00009222324],"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":[0.0000012104,0.000008308684,0.02355472,0.00001503171,0.000003017039,7.504129e-7,0.008922518,0.000007475565,0.000001367207,0.9629756,0.0003079954,0.004202055],"study_design_scores_gemma":[0.0003532018,0.00002165791,0.4177253,0.0000728231,0.000007785446,9.586877e-7,0.002944342,0.0002520112,0.00002608264,0.05794591,0.5205007,0.0001492655],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9682207,0.0007514146,0.000004692442,0.01110852,0.0002899386,0.0001066099,0.00008396701,0.00001449184,0.01941967],"genre_scores_gemma":[0.9925084,0.005437477,0.0002636562,0.001519203,0.0001804723,0.000004935252,0.0000228633,0.000003446887,0.00005959077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9050297,"threshold_uncertainty_score":0.3038295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02307867675956918,"score_gpt":0.2817371282575241,"score_spread":0.2586584514979549,"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."}}