{"id":"W2006652402","doi":"10.1109/tciaig.2014.2309077","title":"An Enhanced Solver for the Game of Amazons","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Intelligence and AI in Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Solver; Chess endgame; Computer science; Combinatorial game theory; Game complexity; Game theory; Theoretical computer science; Problem solver; Computational complexity theory; Sequential game; Mathematical economics; Algorithm; Artificial intelligence; Mathematics; Programming language; Computational 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":[],"consensus_categories":[],"category_scores_codex":[0.0003808685,0.0001572485,0.0001888166,0.0001875242,0.0001452486,0.0001002164,0.0006101316,0.000066049,0.00001969732],"category_scores_gemma":[0.00002626899,0.0001254193,0.00009049514,0.0003474077,0.0002604215,0.0004291325,0.000004031972,0.0001841763,0.0000135047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002133698,"about_ca_system_score_gemma":0.00006003242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006546084,"about_ca_topic_score_gemma":0.00009959839,"domain_scores_codex":[0.9986525,0.00007561358,0.0004244766,0.0003750624,0.0002490593,0.0002232846],"domain_scores_gemma":[0.9974917,0.001813913,0.0000959336,0.0003277748,0.0002070463,0.00006366592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001956595,0.000121592,0.000009373563,0.00000867476,0.00001211216,1.828621e-7,0.001165698,0.6397819,0.0004599148,0.03015351,0.00001197108,0.3282555],"study_design_scores_gemma":[0.00005283561,0.0002779786,0.0002328884,0.00003528602,0.000007455733,0.000002695847,0.0002231292,0.8165371,0.09244273,0.08987927,0.0001779425,0.0001306851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01407479,0.0000488503,0.9838943,0.00118886,0.0003879714,0.0002902875,0.000007284084,0.00004999531,0.00005760618],"genre_scores_gemma":[0.9720806,0.00005493533,0.02696956,0.0007166347,0.00003832542,0.00008215394,0.000001097583,0.000009839349,0.00004681807],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9580058,"threshold_uncertainty_score":0.5114453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03134361171356633,"score_gpt":0.3152985357169212,"score_spread":0.2839549240033549,"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."}}