{"id":"W3094196673","doi":"10.1609/aiide.v16i1.7444","title":"Trouncing in Dota 2: An Investigation of Blowout Matches","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Digital Games and Media","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Victory; HERO; Significant difference; Computer science; Boosting (machine learning); Artificial intelligence; Mean difference; Mathematics; Machine learning; Statistics; Political 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":[],"consensus_categories":[],"category_scores_codex":[0.0002067696,0.0001304055,0.0002126683,0.00006134188,0.00004100333,0.0002193473,0.0003318047,0.00004664447,0.00003487957],"category_scores_gemma":[0.0004619998,0.0001015841,0.00006630219,0.0002176337,0.0004169807,0.001102958,0.0001034743,0.0001443109,0.000007293132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006272207,"about_ca_system_score_gemma":0.00007252319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001107494,"about_ca_topic_score_gemma":0.0000713321,"domain_scores_codex":[0.9987663,0.00001530507,0.0004069717,0.0002554271,0.0003620405,0.0001939542],"domain_scores_gemma":[0.9992415,0.0000725954,0.0002601029,0.00005717192,0.0002304933,0.0001381368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007137009,0.0004244242,0.02450197,0.0001082054,0.00004647976,0.000001090306,0.2511471,0.00001961945,0.03716645,0.2883377,0.00004343928,0.3974898],"study_design_scores_gemma":[0.0002057366,0.002032953,0.004651275,0.001596079,0.00003485314,0.000001406138,0.3846999,0.004447615,0.5437317,0.0562104,0.001835251,0.0005528228],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609998,0.000007840474,0.00004176293,0.002957986,0.00008534259,0.0002912004,0.00001165203,0.0000126801,0.03559174],"genre_scores_gemma":[0.9993549,0.00003678564,0.00002809239,0.0002937868,0.000046653,0.00001158356,0.000001653902,0.000007188441,0.000219343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5065653,"threshold_uncertainty_score":0.4142478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08259144632977806,"score_gpt":0.3091175212294437,"score_spread":0.2265260748996657,"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."}}