{"id":"W2955602601","doi":"10.2139/ssrn.3363889","title":"Product Revenue and Price Setting: Evidence and Aggregate Implications","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Product (mathematics); Aggregate (composite); Revenue; Economics; Finance","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":[0.002676934,0.0004315285,0.0007868074,0.001560433,0.0003699235,0.002982239,0.0008016117,0.0008408853,0.01206191],"category_scores_gemma":[0.02127939,0.0003869519,0.0007961728,0.003101905,0.001353462,0.001886957,0.001225336,0.00152801,0.002052459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005969606,"about_ca_system_score_gemma":0.0003977684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003866429,"about_ca_topic_score_gemma":0.001964637,"domain_scores_codex":[0.9979934,0.0009546773,0.0001559489,0.0003849142,0.0003486107,0.0001625399],"domain_scores_gemma":[0.9550762,0.02920262,0.01012473,0.002371534,0.002231485,0.0009934531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00671987,0.002345529,0.8393589,0.0008232421,0.001650254,0.001079814,0.0004953596,0.003992225,0.001085584,0.02302647,0.00576731,0.1136554],"study_design_scores_gemma":[0.0004415924,0.001010265,0.9632834,0.0001963382,0.001388111,0.001208383,0.0009643669,0.002877946,0.001826099,0.0188567,0.007890407,0.00005641117],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9537658,0.01385805,0.001443424,0.00200377,0.00009925428,0.00003167269,0.00180914,0.00003845125,0.0269505],"genre_scores_gemma":[0.9945964,0.003141155,0.0002751558,0.0001232669,0.0001703178,0.000006324761,0.0007123385,0.00001318638,0.0009619179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01206191,"threshold_uncertainty_score":0.04035115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03500272683311052,"score_gpt":0.2336883010670281,"score_spread":0.1986855742339176,"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."}}