{"id":"W2334963234","doi":"10.5594/j18417","title":"Themed Entertainment: From Analog to Digital","year":2014,"lang":"en","type":"article","venue":"SMPTE Motion Imaging Journal","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Entertainment; Computer graphics (images); Digital media; Computer science; Attraction; Advertising; Visual arts; Art; Business; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000266872,0.0001009116,0.0002032759,0.0001848291,0.0001432209,0.000227441,0.0001242161,0.00001600853,0.0003566167],"category_scores_gemma":[0.0002331027,0.0001013368,0.00009448694,0.00008787227,0.00002276506,0.0002603166,0.00004819788,0.0001335392,0.0006868802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007192495,"about_ca_system_score_gemma":0.000004062042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002710938,"about_ca_topic_score_gemma":0.000003996148,"domain_scores_codex":[0.9991784,0.000008767139,0.0003551257,0.0001904574,0.00004699926,0.0002202702],"domain_scores_gemma":[0.9994862,0.00003560218,0.0001700932,0.0001350721,0.00003111609,0.0001419116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002409601,0.0001195503,0.8449532,0.000007565809,0.0001265117,0.00001334399,0.002781547,0.0001081409,0.0001584571,0.008276137,0.02416299,0.1192684],"study_design_scores_gemma":[0.002027373,0.00008503537,0.3438682,0.00008394677,0.00001866398,0.00005734298,0.0006006764,0.003863066,0.0001608162,0.08843604,0.560309,0.0004897946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4984066,0.001663813,0.4077249,0.01930187,0.003669589,0.0001705659,0.0001358002,0.00007366916,0.06885315],"genre_scores_gemma":[0.9972863,0.00006074522,0.0004193816,0.0008632974,0.0006404846,0.00000344386,0.00001009815,0.00001311024,0.0007031626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.536146,"threshold_uncertainty_score":0.8828684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332766410598997,"score_gpt":0.2021067886542608,"score_spread":0.1887791245482708,"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."}}