{"id":"W3124648382","doi":"10.2139/ssrn.3675236","title":"Generalizable and Robust TV Advertising Effects","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Advertising; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005539862,0.0001518561,0.0001715009,0.00009594719,0.0003095906,0.0003135008,0.0001539316,0.0000444256,0.00007830477],"category_scores_gemma":[0.00008342337,0.000139695,0.00006480442,0.0002659962,0.00002247213,0.0007309495,0.0001033401,0.00078689,0.00004047474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007390583,"about_ca_system_score_gemma":0.0001438639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000207689,"about_ca_topic_score_gemma":0.0001825287,"domain_scores_codex":[0.9982386,0.00001784926,0.0001827388,0.0001954925,0.0001686878,0.001196666],"domain_scores_gemma":[0.9997037,0.00002768672,0.0001136453,0.00007391998,0.00005121261,0.0000298365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000374364,0.0001092195,0.3279442,0.0005396175,0.0003581545,0.0001355232,0.0003397057,0.001259002,0.009062656,0.1202198,0.004225323,0.5354325],"study_design_scores_gemma":[0.02478645,0.0009243962,0.1764041,0.001092353,0.004371628,0.002538715,0.007983098,0.1505097,0.0007746692,0.284999,0.3385342,0.007081648],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9475526,0.008365866,0.03300591,0.004208524,0.0004150829,0.0002247752,3.043913e-7,0.0001545244,0.006072473],"genre_scores_gemma":[0.9955862,0.0007363612,0.0002015231,0.002016,0.001179572,0.000002428104,0.000002473875,0.00003105286,0.0002444024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5283508,"threshold_uncertainty_score":0.5696595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205754683887352,"score_gpt":0.2075282126960017,"score_spread":0.1954706658571282,"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."}}