{"id":"W4295007472","doi":"10.1177/00222429221127927","title":"Does Topic Consistency Matter? A Study of Critic and User Reviews in the Movie Industry","year":2022,"lang":"en","type":"article","venue":"Journal of Marketing","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Nanyang Technological University","keywords":"Consistency (knowledge bases); Recall; Revenue; Advertising; Computer science; Presentation (obstetrics); Theme (computing); Psychology; Marketing; World Wide Web; Business; Cognitive psychology; Artificial intelligence; Accounting","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":[0.01924335,0.00005838544,0.0002470519,0.0000750262,0.00031007,0.00005932922,0.0002582216,0.00003723715,0.000175114],"category_scores_gemma":[0.006351825,0.00003419209,0.00005641212,0.0002447367,0.00009510626,0.0001176517,0.00007318336,0.0005197769,3.380325e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004597305,"about_ca_system_score_gemma":0.00008819461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001680659,"about_ca_topic_score_gemma":0.0002169173,"domain_scores_codex":[0.9950799,0.00369026,0.0005284857,0.0000782844,0.0004710623,0.0001519548],"domain_scores_gemma":[0.9973294,0.002108837,0.0003790803,0.00007655315,0.00006267581,0.0000434267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001233021,0.0003449211,0.9227795,0.00008190643,0.00001786052,0.00005926771,0.05495061,0.000001263617,0.0000112228,0.000104523,0.002739035,0.01878661],"study_design_scores_gemma":[0.0004504783,0.0001521749,0.5130998,0.0002599881,0.00003672435,0.00001246214,0.4483252,9.296767e-7,4.562026e-7,0.0003912665,0.03718498,0.00008562153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794571,0.0007086145,1.510342e-7,0.002469222,0.0003590741,0.0002032881,9.257362e-7,0.000002031963,0.01679958],"genre_scores_gemma":[0.9988779,0.0001541529,0.00002896163,0.0003186889,0.0001637635,0.00000898643,5.358182e-8,0.000003867684,0.0004435557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4096797,"threshold_uncertainty_score":0.7604187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02775773583281558,"score_gpt":0.318679824896433,"score_spread":0.2909220890636174,"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."}}