{"id":"W2146451502","doi":"10.3386/w15642","title":"Virtual Borders: Online Nominal Rigidities and International Market Segmentation","year":2010,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Bank of Canada","funders":"Social Sciences and Humanities Research Council of Canada; HEC Montréal; National Science Foundation","keywords":"Market segmentation; Segmentation; Computer science; Business; Economics; Artificial intelligence; Econometrics; Monetary economics; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003692237,0.0002340596,0.0003444949,0.00153106,0.0001806534,0.0003826364,0.0004427548,0.0002985242,0.005397218],"category_scores_gemma":[0.0009015421,0.000251432,0.0001110323,0.0001481159,0.0002987261,0.0008510407,0.0004254617,0.0008468631,0.00006382138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747124,"about_ca_system_score_gemma":0.0009260954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004941264,"about_ca_topic_score_gemma":0.003617636,"domain_scores_codex":[0.9973542,0.00003485209,0.00062737,0.0004713929,0.00122679,0.0002853749],"domain_scores_gemma":[0.9970424,0.0005669968,0.0004416467,0.0001849623,0.001739635,0.00002437337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007585792,0.0005610304,0.08223925,0.001049913,0.0007262734,0.00001922454,0.0001293221,0.0000505119,0.001624953,0.07535949,0.6444629,0.1930185],"study_design_scores_gemma":[0.002170951,0.00006892127,0.08197129,0.0004257839,0.0001967959,0.00005791365,0.001262128,0.004889808,0.0000640706,0.08133813,0.8265143,0.001039885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09628967,0.000296753,0.000009451323,0.001693661,0.003021992,0.0005814919,0.0002822624,0.0000410777,0.8977836],"genre_scores_gemma":[0.953352,0.001134121,0.0003668134,0.000146169,0.008523221,0.0001035676,0.00442669,0.00009141,0.03185597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8659277,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2392993651600084,"score_gpt":0.4800985493008781,"score_spread":0.2407991841408698,"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."}}