{"id":"W1824179100","doi":"10.24124/c677/20151196","title":"Going Negative: Campaigning in Canadian Provinces","year":2015,"lang":"en","type":"article","venue":"Canadian Political Science Review","topic":"Social Media and Politics","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Anticipation (artificial intelligence); Politics; Political communication; Advertising; Political science; Subject (documents); Business; Public relations; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.003280442,0.0003695826,0.0005989418,0.004956706,0.00530406,0.004302312,0.001208164,0.000687826,0.003511265],"category_scores_gemma":[0.008838829,0.00025228,0.000437367,0.01412174,0.002515942,0.0009144089,0.0009672011,0.00131797,0.0001584282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09964235,"about_ca_system_score_gemma":0.1899429,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970508,"about_ca_topic_score_gemma":0.9982666,"domain_scores_codex":[0.9964418,0.0005563984,0.0001368236,0.0002079478,0.001725878,0.0009312314],"domain_scores_gemma":[0.9927489,0.001155079,0.0007280036,0.0001240499,0.004391942,0.0008519784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005502967,0.0001519868,0.1091639,0.01049244,0.0006693567,0.0006311248,0.03528913,0.002165538,0.0008489505,0.124543,0.2016768,0.5138175],"study_design_scores_gemma":[0.00008618867,0.00006728782,0.4368915,0.004502635,0.0006604264,0.0002064753,0.02834729,0.0006274948,0.0004921762,0.003539542,0.5244346,0.0001442647],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1807438,0.5166981,0.0005034069,0.04639898,0.00124175,0.0001308678,0.004374871,0.00006086837,0.2498474],"genre_scores_gemma":[0.8270616,0.1591852,0.0003573094,0.003174979,0.00017678,0.00003517268,0.001027805,0.00002854595,0.0089526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09964235,"threshold_uncertainty_score":0.7229593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06359611304937147,"score_gpt":0.3873490222609774,"score_spread":0.323752909211606,"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."}}