{"id":"W3084964381","doi":"10.7202/1071451ar","title":"Adaptations of Empire: Kipling's Kim, Novel and Game","year":2020,"lang":"en","type":"article","venue":"Loading","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ideology; Colonialism; Narrative; Depiction; Rhetoric; Video game; Empire; Adaptation (eye); Big game; Sociology; History; Media studies; Aesthetics; Literature; Art; Computer science; Psychology; Political science; Multimedia; Law; Environmental ethics; Linguistics; Philosophy; Archaeology; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00006604978,0.00002944689,0.00006314315,0.00001210566,0.00003096779,0.00002948422,0.0000526057,0.00002142631,0.00002344846],"category_scores_gemma":[0.0002467024,0.00002960609,0.00001903402,0.0001215446,0.00007941799,0.0001095029,0.00001943729,0.00003144623,0.000006979408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006807165,"about_ca_system_score_gemma":0.0000380588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006596978,"about_ca_topic_score_gemma":0.00007279758,"domain_scores_codex":[0.9996529,0.000005367191,0.00007161329,0.00007478164,0.0001013926,0.00009396161],"domain_scores_gemma":[0.9997634,0.00005340307,0.00003040782,0.0000271817,0.00002079032,0.0001047647],"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":[0.00001778698,0.00008872515,0.01010809,0.00006008976,0.000040282,0.000005547247,0.2991715,0.00006845759,0.02740709,0.2677042,0.001232402,0.3940959],"study_design_scores_gemma":[0.0003234785,0.00006496235,0.006133487,0.00005241728,0.00001746932,4.461674e-7,0.01565752,0.00068782,0.0008689442,0.0006074891,0.9754475,0.000138507],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5831589,0.0003613205,0.001811911,0.00575709,0.0002020158,0.0001278427,0.00001187336,0.00006358407,0.4085054],"genre_scores_gemma":[0.9974564,0.00004896525,0.000638404,0.0002911144,0.0001100391,0.000001288238,8.36002e-7,0.000003387795,0.001449567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.974215,"threshold_uncertainty_score":0.1207301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06938949110622324,"score_gpt":0.3125653105184494,"score_spread":0.2431758194122262,"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."}}