{"id":"W4281672560","doi":"10.1287/mnsc.2022.4439","title":"Negative Advertising and Competitive Positioning","year":2022,"lang":"en","type":"article","venue":"Management Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Product proliferation; Advertising; Competition (biology); Product differentiation; Product (mathematics); Profit (economics); Consumer welfare; Economics; Politics; Marketing; Digital advertising; Economic surplus; Commission; Business; Welfare; Microeconomics; New product development; Product management; Political science; Digital marketing; Market economy","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":[0.0008433697,0.0002507745,0.0002609513,0.0006741474,0.0008180583,0.00246407,0.0002314142,0.001104975,0.009823249],"category_scores_gemma":[0.004559395,0.0001339633,0.0002469782,0.0007789618,0.001787577,0.001034522,0.0008680344,0.0007870567,0.0006506537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009576141,"about_ca_system_score_gemma":0.0003790313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002157994,"about_ca_topic_score_gemma":0.001976582,"domain_scores_codex":[0.9992823,0.0002912224,0.00002330825,0.0001167076,0.0001578908,0.0001285681],"domain_scores_gemma":[0.995398,0.002486962,0.001336271,0.0001748641,0.0002703386,0.0003336536],"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":[0.0005470318,0.0009216827,0.1659468,0.0003735231,0.0001404018,0.0009768733,0.003578933,0.009775924,0.007746509,0.6565318,0.006464974,0.1469956],"study_design_scores_gemma":[0.0001375132,0.00081681,0.3216623,0.0002206158,0.0002377272,0.001591009,0.004650008,0.02719515,0.004243384,0.5860826,0.05301903,0.000143826],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7822533,0.00337421,0.006889148,0.003704719,0.00007775406,0.00003202712,0.0001109276,0.00002161905,0.2035362],"genre_scores_gemma":[0.9963477,0.0004071956,0.0003747297,0.0001475451,0.00003703061,0.000004772649,0.00001746953,0.000003154844,0.002660454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009823249,"threshold_uncertainty_score":0.03286207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01073097127307117,"score_gpt":0.2289631099908124,"score_spread":0.2182321387177412,"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."}}