{"id":"W1160321526","doi":"10.1007/978-3-319-16976-7_60","title":"Corrective Advertising: The Canadian Situation","year":2015,"lang":"en","type":"book-chapter","venue":"Developments in marketing science: proceedings of the Academy of Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Advertising; Psychology; Business; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007417309,0.0009013432,0.0009657278,0.006587088,0.02295918,0.01324734,0.003654981,0.007015737,0.03914981],"category_scores_gemma":[0.02221688,0.0008410392,0.0009398512,0.01393018,0.009751651,0.004312644,0.003097193,0.008738124,0.002048105],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1620195,"about_ca_system_score_gemma":0.3200878,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944841,"about_ca_topic_score_gemma":0.9972415,"domain_scores_codex":[0.9870357,0.0008546517,0.0003432234,0.001222234,0.007926536,0.002617681],"domain_scores_gemma":[0.9686601,0.003086807,0.0009296869,0.0008531165,0.02111154,0.005358782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001332082,0.0001123923,0.006531118,0.0004829268,0.00003310199,0.0006960127,0.00550263,0.0002225912,0.0004823271,0.2279598,0.541759,0.2160849],"study_design_scores_gemma":[0.00002899485,0.00001876388,0.01461979,0.0004721891,0.00003680937,0.0004023946,0.004581363,0.0002363398,0.0002119553,0.006321829,0.9729717,0.00009783701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02913731,0.06038677,0.001057248,0.5153508,0.003958701,0.00009532833,0.00182854,0.0002929126,0.3878924],"genre_scores_gemma":[0.4483886,0.09543193,0.003907029,0.1353823,0.002501508,0.0001034335,0.001371699,0.0006132812,0.3123001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1620195,"threshold_uncertainty_score":0.9719386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03107215856369044,"score_gpt":0.2651832517304527,"score_spread":0.2341110931667622,"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."}}