{"id":"W2008528373","doi":"10.1080/10584609.2012.721868","title":"Negative Advertising and Voter Choice: The Role of Ads in Candidate Selection","year":2012,"lang":"en","type":"article","venue":"Political Communication","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Negativity effect; Politics; Selection (genetic algorithm); Social psychology; Political communication; Tone (literature); Robustness (evolution); Advertising; Psychology; Economics; Sociology; Political science; Computer science; Law; Business","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":[],"consensus_categories":[],"category_scores_codex":[0.0003869459,0.00003208927,0.00005974339,0.00002421314,0.0001792845,0.00001045096,0.0001219379,0.00005473933,0.00002863045],"category_scores_gemma":[0.0003206905,0.00002549887,0.00001399891,0.0001203397,0.0003536753,0.0001591499,0.00003930558,0.00012242,0.000003643913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006893112,"about_ca_system_score_gemma":0.00001660605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02967399,"about_ca_topic_score_gemma":0.006713926,"domain_scores_codex":[0.9991094,0.0004616209,0.0001083631,0.00004281024,0.00007026701,0.0002075733],"domain_scores_gemma":[0.9993719,0.0004043087,0.00003429822,0.0001015091,0.00003726018,0.00005065122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000006354177,0.00003803334,0.2397442,0.000001179269,0.000003840057,4.344339e-9,0.01574294,5.624245e-8,0.0003378822,0.7391027,0.0000240257,0.004998764],"study_design_scores_gemma":[0.0001405936,0.00002008724,0.887792,0.00001672923,0.000008313637,4.944034e-7,0.01021398,0.00006647615,0.0007760739,0.08878349,0.01212539,0.00005638675],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8907498,0.0004217046,0.00001919534,0.005043419,0.00004635522,0.00009770425,0.000001029273,0.00001135376,0.1036095],"genre_scores_gemma":[0.9994569,0.00005036997,0.00007581659,0.0002717926,0.00007941972,0.000009626152,0.000001272392,0.000002559304,0.0000522214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6503192,"threshold_uncertainty_score":0.9767875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001651435856441,"score_gpt":0.3650813311088248,"score_spread":0.3450648167502604,"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."}}