{"id":"W4401366390","doi":"10.2139/ssrn.4915952","title":"Estimating the Value of Offsite Tracking Data to Advertisers: Evidence from Meta","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Value (mathematics); Tracking (education); Computer science; Advertising; Statistics; Econometrics; Business; Mathematics; Psychology","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":[0.1178062,0.002913237,0.005706113,0.009470381,0.0009929773,0.006576101,0.006150074,0.005785965,0.00487277],"category_scores_gemma":[0.4548256,0.002272184,0.01377861,0.01104441,0.002732989,0.006080697,0.002990512,0.004673671,0.0007809976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444881,"about_ca_system_score_gemma":0.001550851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01094655,"about_ca_topic_score_gemma":0.007038323,"domain_scores_codex":[0.8629035,0.1128687,0.007864835,0.009136677,0.006249614,0.0009767198],"domain_scores_gemma":[0.1516544,0.7972643,0.02391881,0.0220097,0.00413558,0.001017243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"observational","study_design_scores_codex":[0.0146053,0.0007041952,0.3018586,0.0187763,0.57234,0.0004448101,0.0010701,0.008882759,0.0003279991,0.002415946,0.003066286,0.07550774],"study_design_scores_gemma":[0.004408991,0.003241607,0.1171101,0.009802347,0.8207276,0.0005642276,0.0009965408,0.01568051,0.002047923,0.01723581,0.007844555,0.0003397596],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6307679,0.3070679,0.02772133,0.005527118,0.001644041,0.0007053184,0.01463247,0.0005645486,0.01136929],"genre_scores_gemma":[0.9647744,0.02252866,0.006324372,0.00120978,0.0005522165,0.0002192969,0.003432468,0.0001562263,0.0008026509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1178062,"threshold_uncertainty_score":0.6230264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07225569788643144,"score_gpt":0.3095151399105188,"score_spread":0.2372594420240874,"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."}}