{"id":"W4312810017","doi":"10.1609/aiide.v9i1.12616","title":"Invited Talks","year":2013,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ubisoft (Canada)","funders":"","keywords":"Political science","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001607707,0.0003331932,0.0003074436,0.0001792024,0.0001698621,0.001219165,0.001555687,0.00008523431,0.0001159089],"category_scores_gemma":[0.0003758062,0.0002365312,0.0001624169,0.000400392,0.0004218046,0.002589802,0.0008197441,0.0003315673,0.0002448555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008920678,"about_ca_system_score_gemma":0.00002307982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007606088,"about_ca_topic_score_gemma":0.000003611903,"domain_scores_codex":[0.9977139,0.00001610465,0.0006978191,0.0006227336,0.0005177933,0.0004316593],"domain_scores_gemma":[0.9982694,0.0001634965,0.0004087231,0.0003263711,0.0006718404,0.0001601812],"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":[0.00008181746,0.0005778293,0.00128554,0.00003397121,0.00007990288,0.00000117284,0.004517255,0.00001991795,0.032094,0.4353711,0.001369887,0.5245676],"study_design_scores_gemma":[0.00003752747,0.0006821011,0.0006820413,0.0003917075,0.00001143793,0.00001503037,0.005559441,0.05277869,0.7067612,0.2317817,0.0008318991,0.0004672764],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906649,0.00003570614,0.03526548,0.02525396,0.0008334192,0.001507653,0.00001568433,0.0001747132,0.03026437],"genre_scores_gemma":[0.997611,0.00002881385,0.0004433255,0.001425777,0.00004448702,0.00009315291,0.000001056088,0.00001529117,0.0003371375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6746672,"threshold_uncertainty_score":0.9998177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04017724560051993,"score_gpt":0.2729088899018833,"score_spread":0.2327316443013634,"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."}}