{"id":"W4312371681","doi":"10.1609/aiide.v10i2.12738","title":"Preface","year":2014,"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":"University of Alberta","funders":"","keywords":"Presentation (obstetrics); Pleasure; Computer science; Adversarial system; Representation (politics); Term (time); Artificial intelligence; Psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001724745,0.001034671,0.0008578786,0.002634424,0.002223662,0.004564733,0.001454985,0.001438721,0.4283285],"category_scores_gemma":[0.01551051,0.000359252,0.0005958865,0.001992464,0.0006639134,0.003399131,0.002242534,0.003700988,0.3117974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970892,"about_ca_system_score_gemma":0.001614875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002157512,"about_ca_topic_score_gemma":0.002333398,"domain_scores_codex":[0.9988845,0.0001582975,0.00009799332,0.0002117829,0.0005541089,0.00009330732],"domain_scores_gemma":[0.9922385,0.001186516,0.0003062728,0.0006120075,0.004445392,0.001211465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002800034,0.00001712384,0.00008733103,0.00008754283,0.000002035503,0.0000361272,0.00006685119,0.00007773095,0.0001358002,0.003906934,0.963122,0.03243253],"study_design_scores_gemma":[0.000004750139,0.00001761219,0.0002400527,0.0001248273,0.000001636118,0.00005749651,0.00006144989,0.00004139451,0.00007717936,0.003201108,0.996167,0.000005532099],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002018287,0.0180739,0.01525313,0.06390382,0.3337781,0.0006749154,0.01636107,0.002930375,0.5470064],"genre_scores_gemma":[0.01123534,0.009937522,0.005312135,0.01204823,0.06536433,0.0004766874,0.01480592,0.001775821,0.879044],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5716715,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03891820528764053,"score_gpt":0.2792691293390521,"score_spread":0.2403509240514116,"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."}}