{"id":"W4393100941","doi":"10.1007/978-3-031-54752-2","title":"AI-Generated Popular Culture","year":2024,"lang":"en","type":"book","venue":"","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Popular culture; Computer science; Sociology; Media studies","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004385765,0.000145707,0.0002276712,0.0001153771,0.0002313218,0.0001921966,0.0002026128,0.0003044145,0.003010273],"category_scores_gemma":[0.00004228041,0.0001120222,0.000246656,0.0002626196,0.00008419432,0.0000485322,0.00004592682,0.0003019114,0.001251968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164901,"about_ca_system_score_gemma":0.0007060075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000281279,"about_ca_topic_score_gemma":0.001859905,"domain_scores_codex":[0.9987682,0.0001407522,0.0001750146,0.0002837727,0.0004761505,0.0001560712],"domain_scores_gemma":[0.9995528,0.00003021234,0.00004506276,0.00009888869,0.0001799948,0.00009308453],"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":[4.458691e-7,0.000003612478,0.000001805295,0.000007949877,0.00007893519,0.00001092811,0.001223645,0.00001101613,0.000001452376,0.4566963,0.5365307,0.005433203],"study_design_scores_gemma":[0.00001453043,0.000004077593,9.33071e-7,0.00001956671,0.00009507131,2.948013e-7,0.00005952536,0.000113312,9.432882e-7,0.2262152,0.7733497,0.0001268898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000002211598,0.00241293,0.001249649,0.002816669,0.0006579655,0.00009008621,0.00001158437,0.0001947313,0.9925642],"genre_scores_gemma":[0.00004076306,0.0001613216,0.002472322,0.001066923,0.001735481,0.00000405191,0.0002274316,0.00001675074,0.994275],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2368189,"threshold_uncertainty_score":0.9995257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04177498592570473,"score_gpt":0.3866558812883201,"score_spread":0.3448808953626153,"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."}}