{"id":"W2741184253","doi":"10.1287/mnsc.1100.1287","title":"Search Engine Advertising: Channel Substitution When Pricing Ads to Context","year":2011,"lang":"en","type":"article","venue":"Management Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Online advertising; Search advertising; Business; Context (archaeology); Exploit; Channel (broadcasting); Substitution (logic); Native advertising; Advertising campaign; Contextual advertising; Display advertising; Informative advertising; Marketing channel; Marketing; The Internet; Computer science; World Wide Web; Telecommunications; Computer security","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":[0.001396029,0.0001868008,0.0001506938,0.0009487989,0.0005468538,0.0003677749,0.0007762896,0.0000257593,0.0004374529],"category_scores_gemma":[0.00005203986,0.0001808279,0.00004755982,0.001722568,0.0001731757,0.001731927,0.0008062631,0.0001071443,0.0006174219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006957899,"about_ca_system_score_gemma":0.00001698157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009526963,"about_ca_topic_score_gemma":0.00006707419,"domain_scores_codex":[0.9979352,0.000008098724,0.0002456496,0.0005629212,0.0006302771,0.000617861],"domain_scores_gemma":[0.9993057,0.00001247797,0.00006894659,0.0004179035,0.0001460085,0.0000490048],"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":[0.0001977343,0.0003735811,0.1516652,0.0005232089,0.00005075402,0.0001756973,0.003260222,0.0003330047,0.004301932,0.1144304,0.00275521,0.721933],"study_design_scores_gemma":[0.001287178,0.0000539696,0.888409,0.000449303,0.0002314855,0.000006458046,0.002602546,0.01461229,0.00417707,0.00204032,0.08479653,0.001333826],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7726799,0.00005756002,0.03102629,0.0004628469,0.001095012,0.0008825746,7.126569e-7,0.0003252794,0.1934698],"genre_scores_gemma":[0.9960803,0.000005160459,0.001167246,0.001397876,0.0001335137,0.00002993507,0.000002505402,0.00001590408,0.001167539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7367437,"threshold_uncertainty_score":0.7935916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04767229614317822,"score_gpt":0.2508611125833126,"score_spread":0.2031888164401343,"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."}}