{"id":"W4410564158","doi":"10.1177/14614448251336433","title":"Mutual influences between climate change communication and expressive participation on Weibo: A longitudinal network–behaviour co-evolution analysis","year":2025,"lang":"en","type":"article","venue":"New Media & Society","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Climate change; Social network analysis; Sociology; Psychology; Computer science; Social media; Ecology; World Wide Web; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002339337,0.0002477822,0.0002769785,0.001857208,0.0007938361,0.0008322063,0.0004101606,0.0003959123,0.003579493],"category_scores_gemma":[0.007862002,0.0001696948,0.0004987163,0.002279282,0.0004366841,0.001369855,0.001064848,0.00067723,0.0004983824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009442114,"about_ca_system_score_gemma":0.0007121117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01971251,"about_ca_topic_score_gemma":0.02456766,"domain_scores_codex":[0.9991769,0.0004238504,0.00003492986,0.000134285,0.00010187,0.0001281282],"domain_scores_gemma":[0.9939513,0.003359258,0.001096459,0.0004725328,0.0006253638,0.0004950968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007545901,0.0001070463,0.9827419,0.00003365053,0.00009319313,0.000169161,0.00245962,0.002943131,0.0002924321,0.001506024,0.0008550002,0.008723394],"study_design_scores_gemma":[0.000009561944,0.0001293068,0.9107143,0.00004740348,0.00008582122,0.0001395281,0.005395052,0.07719013,0.0003846193,0.002000527,0.003860097,0.00004381781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964536,0.00006377752,0.001537557,0.0001231498,0.000007532633,0.00002531498,0.0007794751,0.00001741201,0.0009921972],"genre_scores_gemma":[0.9978713,0.00003907704,0.0006097889,0.00001193778,0.000005896309,0.00006435352,0.0008208315,0.000005893571,0.0005708248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01971251,"threshold_uncertainty_score":0.03919554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09139326923876177,"score_gpt":0.4024409450863456,"score_spread":0.3110476758475839,"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."}}