{"id":"W1484734702","doi":"10.1609/aimag.v34i2.2474","title":"The Annual Computer Poker Competition","year":2013,"lang":"en","type":"article","venue":"AI Magazine","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Verafin (Canada); University of Alberta","funders":"","keywords":"Competition (biology); Competitor analysis; Benchmarking; Field (mathematics); Event (particle physics); Computer science; Operations research; Data science; Engineering; Marketing; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001734009,0.0001053897,0.00008738771,0.00003519044,0.0002140806,0.0004068129,0.000844305,0.00003747454,0.0001508509],"category_scores_gemma":[0.00002299089,0.00007087149,0.00004634587,0.0002054223,0.0001266115,0.0007971591,0.000291731,0.0001340979,0.0103763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002064438,"about_ca_system_score_gemma":0.00002174355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004585875,"about_ca_topic_score_gemma":0.00003004544,"domain_scores_codex":[0.9989953,0.00005747044,0.0002103474,0.0002327969,0.0002216378,0.0002824431],"domain_scores_gemma":[0.9989232,0.0001724778,0.00005308124,0.0005201625,0.0002619174,0.00006915654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002097969,0.00004711847,0.0004723211,0.000002816856,0.0000123994,0.000006802401,0.0005545895,0.0001786468,0.0004930744,0.4066168,0.2401071,0.3515062],"study_design_scores_gemma":[0.0001156775,0.0002105259,0.02930485,0.0000219404,0.000004552096,0.00003987644,0.00008654729,0.2672357,0.002148875,0.08738423,0.6130732,0.0003741089],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00776671,0.00009447344,0.947576,0.03424333,0.001212337,0.0002679714,0.000002055755,0.0002659866,0.008571091],"genre_scores_gemma":[0.9575696,0.00003062659,0.02926525,0.007740462,0.0005985431,0.00005224,0.000003957814,0.00001614474,0.004723144],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9498029,"threshold_uncertainty_score":0.9903942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127126165701008,"score_gpt":0.2502195679546236,"score_spread":0.2389483062976135,"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."}}