{"id":"W2996627376","doi":"10.6000/1929-7092.2019.08.81","title":"The Impact of Technological and Marketing Innovations on Retailing Industry: Evidence of India","year":2019,"lang":"en","type":"article","venue":"Journal of Reviews on Global Economics","topic":"Indian Economic and Social Development","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Business; Marketing; Industrial organization","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007546929,0.0002592218,0.0003087222,0.00296565,0.0003813817,0.002285186,0.0005334599,0.0005522238,0.004441412],"category_scores_gemma":[0.003090823,0.000166496,0.0008041323,0.005789994,0.001344025,0.0008818898,0.0009296502,0.0007057646,0.0004057375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009203632,"about_ca_system_score_gemma":0.001363304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0253265,"about_ca_topic_score_gemma":0.03412974,"domain_scores_codex":[0.9992435,0.0001458826,0.00006757686,0.0001090797,0.0002306563,0.0002033559],"domain_scores_gemma":[0.9905961,0.005382406,0.002241858,0.0003485847,0.001002184,0.000428789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007997607,0.0006396536,0.8710752,0.003107652,0.001286987,0.002186914,0.003023919,0.001755569,0.00324159,0.006314387,0.003334025,0.1032344],"study_design_scores_gemma":[0.000008606031,0.0001139033,0.9912595,0.0001748805,0.0004595722,0.0002400039,0.001550948,0.0001427921,0.0004729676,0.0003149023,0.00524481,0.00001694062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466989,0.03291272,0.0001276951,0.001584585,0.00005350618,0.00001343801,0.0007141265,0.0000172619,0.01787785],"genre_scores_gemma":[0.9806605,0.01756307,0.00008708533,0.0001726618,0.00006531553,0.000002733203,0.0002958972,0.000004051692,0.001148743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0253265,"threshold_uncertainty_score":0.05035818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05155300943617146,"score_gpt":0.2929279761055951,"score_spread":0.2413749666694236,"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."}}