{"id":"W3035778436","doi":"10.1080/17457289.2020.1780432","title":"Raining on the parties’ parade: how media storms disrupt the electoral communicational environment","year":2020,"lang":"en","type":"article","venue":"Journal of Elections Public Opinion and Parties","topic":"Social Media and Politics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Parade; Storm; Advertising; Media studies; Political science; Business; Meteorology; Sociology; Geography; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006490846,0.0000809738,0.0001275767,0.00003854263,0.00138194,0.0002549149,0.0002797616,0.00005852552,0.0001335685],"category_scores_gemma":[0.00128138,0.00004643829,0.00008019583,0.0002178996,0.0005763666,0.0002183864,0.00002935071,0.0004264561,0.000006581048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006279464,"about_ca_system_score_gemma":0.0002489831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005183876,"about_ca_topic_score_gemma":0.00008239601,"domain_scores_codex":[0.9984939,0.0005537048,0.0002102463,0.0000663532,0.0004407839,0.0002350654],"domain_scores_gemma":[0.9982073,0.001201474,0.000218858,0.0001006156,0.00008000885,0.0001917086],"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":[0.00008436717,0.00018664,0.08112482,0.00001047999,0.0002480625,0.000001222294,0.2531835,0.00004636991,0.0001177329,0.5388887,0.1204903,0.005617871],"study_design_scores_gemma":[0.0001785688,0.0001678317,0.008319239,0.00001160229,0.00001610159,0.00000499705,0.05988489,0.00009716312,0.00007430438,0.001746814,0.929414,0.00008442991],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3030277,0.001459777,0.000117171,0.6930441,0.001076703,0.0001492842,0.000005714895,0.00002169675,0.00109784],"genre_scores_gemma":[0.9948295,0.001415431,0.00002346011,0.001910291,0.001697904,0.00001460419,0.000002527036,0.000005957902,0.0001002733],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8089238,"threshold_uncertainty_score":0.9999181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1702002027684782,"score_gpt":0.3370701867991854,"score_spread":0.1668699840307072,"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."}}