{"id":"W3122446134","doi":"10.1257/mac.20180461","title":"Advertising, Innovation, and Economic Growth","year":2021,"lang":"en","type":"article","venue":"American Economic Journal Macroeconomics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microfoundations; Economics; Growth model; Channel (broadcasting); Econometrics; Empirical evidence; Advertising; Microeconomics; Business; Telecommunications; Computer science; Macroeconomics","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":[0.0006994341,0.0002274355,0.0002401927,0.000921791,0.0002542611,0.001601699,0.0001767276,0.000781213,0.00324795],"category_scores_gemma":[0.006047614,0.00009690948,0.0002334332,0.001213946,0.0007621319,0.001046765,0.0004975174,0.0006651797,0.0003596509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391381,"about_ca_system_score_gemma":0.0004592194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004301438,"about_ca_topic_score_gemma":0.002812119,"domain_scores_codex":[0.9997435,0.0001123633,0.0000112827,0.00003719128,0.00004710475,0.00004851707],"domain_scores_gemma":[0.9932914,0.00477593,0.00132902,0.0001326355,0.0002341966,0.0002367693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003895061,0.0004763402,0.4090978,0.0003577906,0.0002107089,0.000994983,0.001077849,0.1316776,0.002854188,0.2635579,0.0090874,0.1802179],"study_design_scores_gemma":[0.0001109997,0.0003185911,0.4449382,0.0002778056,0.0002411148,0.0009406956,0.001457285,0.206135,0.001985295,0.3094223,0.03407381,0.00009900534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254081,0.00967434,0.006461769,0.007482599,0.00007339838,0.00001700853,0.000339323,0.0001064782,0.0504371],"genre_scores_gemma":[0.9950046,0.002078995,0.0002916192,0.00009507872,0.00006571436,0.000003620565,0.00005280771,0.000004765047,0.002402776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004301438,"threshold_uncertainty_score":0.01086545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0120281364135401,"score_gpt":0.2262665414716945,"score_spread":0.2142384050581544,"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."}}