{"id":"W1579490063","doi":"10.3386/w19176","title":"Multichannel Spillovers from a Factory Store","year":2013,"lang":"en","type":"article","venue":"National Bureau of Economic Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Factory (object-oriented programming); Business; Quality (philosophy); Advertising; Marketing; Commerce; Computer science","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":[0.001975316,0.0003697739,0.000895576,0.0005782603,0.0006830296,0.001412242,0.0005918756,0.001080783,0.01683236],"category_scores_gemma":[0.005322192,0.0004611269,0.001142398,0.0006493144,0.0009747489,0.001263178,0.00181131,0.001194356,0.0006156086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001313626,"about_ca_system_score_gemma":0.0007902281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01143707,"about_ca_topic_score_gemma":0.01691871,"domain_scores_codex":[0.9987865,0.0003565581,0.00005365742,0.000338653,0.0001692572,0.000295267],"domain_scores_gemma":[0.9873644,0.007566432,0.00292932,0.001132334,0.0004433359,0.0005641985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004230309,0.01059167,0.7756363,0.001236209,0.001819532,0.003060343,0.003098467,0.05094482,0.02913331,0.02302868,0.004960773,0.09225969],"study_design_scores_gemma":[0.0005233965,0.003330201,0.9369895,0.0001398138,0.001157286,0.0005523642,0.003746176,0.02364466,0.009804003,0.01171288,0.008144992,0.0002547744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915001,0.0001693606,0.002477441,0.0001963951,0.00001970745,0.00007549929,0.0006057921,0.00003133389,0.004924456],"genre_scores_gemma":[0.9959002,0.000156871,0.0009093857,0.0001767924,0.00002651195,0.00006712537,0.0002521256,0.000005553391,0.00250535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01683236,"threshold_uncertainty_score":0.05630982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2484518186953801,"score_gpt":0.4242272725401491,"score_spread":0.175775453844769,"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."}}