{"id":"W4312319472","doi":"10.2139/ssrn.4298841","title":"Predictive Accuracy, Search Intensity, and Personalized Advertising","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Intensity (physics); Computer science; Business; Information retrieval","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":[0.008752993,0.0005285557,0.0009036754,0.00365549,0.0005101152,0.003700034,0.00076588,0.002477701,0.006720303],"category_scores_gemma":[0.08445492,0.0005182921,0.0009460972,0.002842118,0.001086681,0.003280802,0.0008288868,0.002382678,0.001053762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005948574,"about_ca_system_score_gemma":0.0004653949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003818461,"about_ca_topic_score_gemma":0.003078455,"domain_scores_codex":[0.9980629,0.0007531392,0.0001993682,0.0003289211,0.0004429838,0.0002126745],"domain_scores_gemma":[0.768113,0.2016907,0.01426593,0.01010399,0.002674456,0.003151986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001678827,0.000892506,0.9568475,0.00007473127,0.0005884594,0.0001548204,0.0002771736,0.01246623,0.0007968529,0.002531474,0.001156461,0.02253498],"study_design_scores_gemma":[0.0001025818,0.0004677196,0.8835405,0.00005954719,0.0007292079,0.0005531588,0.0002713896,0.09623969,0.0007400205,0.01655769,0.000664167,0.00007435395],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889303,0.00122497,0.001797583,0.0008486608,0.00004395999,0.00001891054,0.0003474177,0.00007760698,0.006710605],"genre_scores_gemma":[0.9983542,0.0002303486,0.0002421226,0.00009326303,0.0001227198,0.000004961461,0.0002518707,0.00001821793,0.000682296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008752993,"threshold_uncertainty_score":0.04629076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438190841520301,"score_gpt":0.2469854834777644,"score_spread":0.2326035750625614,"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."}}