{"id":"W4231107670","doi":"10.32920/ryerson.14645787","title":"Social network analysis of climate change discussion on Twitter during COP21","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Skepticism; Climate change; Social media; Sample (material); Microblogging; Political science; Geography; Computer science; World Wide Web; Ecology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006416355,0.0001635658,0.0004780393,0.0002271235,0.0006688574,0.0001242368,0.0003737535,0.0003511694,0.005046586],"category_scores_gemma":[0.00002784723,0.0001262466,0.0004504731,0.0007971363,0.0001284626,0.00007239373,0.0007656055,0.0003364056,0.00002070476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001747727,"about_ca_system_score_gemma":0.00003481032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486348,"about_ca_topic_score_gemma":0.01731174,"domain_scores_codex":[0.9980407,0.0005543283,0.000342834,0.0003256511,0.0004209165,0.0003155163],"domain_scores_gemma":[0.9989476,0.00006403543,0.0003049057,0.0004792563,0.0001334089,0.00007077479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002252245,0.0007792645,0.1089228,0.0006636381,0.001712808,0.000008727926,0.8140237,0.00115479,0.0002694179,0.01077943,0.00263154,0.05882864],"study_design_scores_gemma":[0.0005017191,0.0000323618,0.883794,0.0008631197,0.001989541,1.476467e-7,0.09613051,0.001459333,0.00002875794,0.0006648183,0.01351578,0.001019974],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8821774,0.0001416228,0.0000366474,0.01693117,0.0006645081,0.0004995486,0.00005780321,0.0001439799,0.0993473],"genre_scores_gemma":[0.9816072,0.01533227,0.0001004035,0.0004296613,0.001000106,0.00007420656,0.0006847535,0.00001545762,0.0007559224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7748711,"threshold_uncertainty_score":0.995863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4516575332919505,"score_gpt":0.4743526640108456,"score_spread":0.02269513071889506,"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."}}