{"id":"W2759876715","doi":"10.18146/2213-0969.2017.jethc125","title":"Russia’s STS Television Network","year":2017,"lang":"en","type":"article","venue":"VIEW Journal of European Television History and Culture","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Hybridity; Entertainment; State (computer science); Entertainment industry; Media studies; Advertising; Political science; Telecommunications; Business; Sociology; Engineering; Computer science; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002119395,0.0001090641,0.0002391788,0.00002699928,0.001889681,0.000103559,0.0007053271,0.00005076149,0.0001891447],"category_scores_gemma":[0.0004901189,0.00007552658,0.0001104332,0.00003815593,0.0003125086,0.0003711788,0.0001565633,0.0003223571,0.00002891765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009874775,"about_ca_system_score_gemma":0.00006227098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001585733,"about_ca_topic_score_gemma":0.0000472399,"domain_scores_codex":[0.9983847,0.0006382006,0.0003447512,0.0001177975,0.0003391302,0.0001754047],"domain_scores_gemma":[0.9983843,0.00004613948,0.0008150848,0.000365629,0.0002084139,0.0001804531],"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":[0.0000418233,0.00005658917,0.001198577,0.00003142518,0.00003592576,0.00006917304,0.01572153,0.000002763655,0.000109783,0.006875315,0.3566928,0.6191643],"study_design_scores_gemma":[0.0002206762,0.0000999184,0.01525584,0.0003364861,0.00003039507,0.00001227118,0.0006099672,0.000001352839,0.000001202595,0.0002140094,0.9831224,0.00009545749],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02637951,0.3116523,0.0002471734,0.008844579,0.003735025,0.0002909941,0.000002062078,0.00004435471,0.648804],"genre_scores_gemma":[0.8054565,0.1786536,0.0009772175,0.0007142134,0.002884875,7.957343e-7,0.000001506771,0.0000209584,0.01129036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.779077,"threshold_uncertainty_score":0.9994097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04303154566692719,"score_gpt":0.3004898927056974,"score_spread":0.2574583470387702,"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."}}