{"id":"W4295233197","doi":"10.1002/nav.22079","title":"Traffic channeling under uncertain conversion rates on e‐commerce platforms","year":2022,"lang":"en","type":"article","venue":"Naval Research Logistics (NRL)","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Spillover effect; Business; Product (mathematics); Channel (broadcasting); Competition (biology); Industrial organization; Microeconomics; Computer science; Commerce; Economics; Telecommunications","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":[0.001968782,0.0008529425,0.0008803629,0.001128794,0.001225843,0.002587806,0.001312758,0.001459622,0.006001837],"category_scores_gemma":[0.01056908,0.0004807079,0.0007414508,0.0006508721,0.00182876,0.003160491,0.001985796,0.00197295,0.0003806788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003187858,"about_ca_system_score_gemma":0.00102109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009299863,"about_ca_topic_score_gemma":0.004613271,"domain_scores_codex":[0.9987667,0.0003711052,0.00002815587,0.0001708353,0.0001443261,0.0005190783],"domain_scores_gemma":[0.9882599,0.00744576,0.001519236,0.0004847926,0.001218198,0.001072152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000535902,0.00020493,0.006439234,0.00007104021,0.00004640391,0.0007195987,0.0001870836,0.90873,0.004871592,0.06694128,0.001723827,0.009529104],"study_design_scores_gemma":[0.00001622746,0.0001035445,0.001755072,0.0000138945,0.00002356391,0.00007369908,0.0002948065,0.9746603,0.0005991216,0.02207726,0.0003526435,0.00002983357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9293803,0.0002013877,0.05675217,0.0008003094,0.00006573169,0.00007193826,0.0002035951,0.0001236658,0.01240097],"genre_scores_gemma":[0.9977058,0.00007522061,0.001077173,0.00002492663,0.00001323662,0.00001374963,0.00002946707,0.00001229093,0.001048203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009299863,"threshold_uncertainty_score":0.0231297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2239226144608143,"score_gpt":0.3693479171244493,"score_spread":0.145425302663635,"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."}}