{"id":"W2290133885","doi":"10.7939/r3bb8f","title":"Fuegito: an Educational Software Package for Game Tree Search","year":2013,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Monte Carlo tree search; Tree (set theory); Game programming; Software; Simple (philosophy); Game tree; Theoretical computer science; Software engineering; Artificial intelligence; Machine learning; Sequential game; Programming language; Game design; Game theory; Game Developer; Monte Carlo method; Game design document; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0008591106,0.001702011,0.0009560351,0.001593131,0.0005482344,0.001729284,0.003182473,0.001201244,0.1110172],"category_scores_gemma":[0.006505345,0.001313581,0.001620278,0.001136639,0.0004447788,0.002895368,0.002174767,0.002452882,0.04154586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008246291,"about_ca_system_score_gemma":0.001853108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005128488,"about_ca_topic_score_gemma":0.00735404,"domain_scores_codex":[0.9995863,0.00006695899,0.00005013481,0.00006457372,0.0001480802,0.00008384998],"domain_scores_gemma":[0.9983032,0.001062934,0.00006439385,0.0001631116,0.0003165495,0.00008980602],"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":[0.0005463853,0.0004042606,0.001890318,0.001948062,0.0001392761,0.0004350858,0.0006794203,0.01773692,0.007788504,0.07513537,0.489705,0.4035913],"study_design_scores_gemma":[0.0006161555,0.0001671667,0.002102822,0.0005750871,0.0001402661,0.000818604,0.0001231866,0.1348068,0.01817665,0.0993652,0.742906,0.0002021952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002699602,0.0003801071,0.7044296,0.0003156077,0.0001691422,0.0005924307,0.01082682,0.2322688,0.04831784],"genre_scores_gemma":[0.04155289,0.0009865735,0.7933616,0.0006299695,0.00008473574,0.003678684,0.03012984,0.0707543,0.05882136],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1110172,"threshold_uncertainty_score":0.3713896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182795457964371,"score_gpt":0.2330946786967994,"score_spread":0.2112667241171557,"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."}}