{"meta":{"query_hash":"2d4429f89592","filters":{"venue":"2020 IEEE Conference on Games (CoG)"},"cohort_total":4,"direct_labels_cover":0,"predictions_cover":4,"exported":4,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/2d4429f89592","api":"https://metacan.xera.ac/api/v1/cohort?venue=2020+IEEE+Conference+on+Games+%28CoG%29"},"results":[{"id":"W3093593979","doi":"10.1109/cog47356.2020.9231889","title":"Combining Influence Maps with Heuristic Search for Executing Sneak-Attacks in RTS Games","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Games (CoG)","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Adversary; Computer science; Surprise; Heuristic; Path (computing); Domain (mathematical analysis); Order (exchange); Artificial intelligence; Computer security; Programming language; Mathematics","score_opus":0.07439078111553457,"score_gpt":0.31316774152662985,"score_spread":0.23877696041109528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093593979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07209203,0.00036289875,0.91564804,0.00024325213,0.00007507044,0.00024145973,0.000051842562,0.0017515841,0.009533797],"genre_scores_gemma":[0.78446496,0.000210989,0.21255563,0.00012689758,0.000049540733,0.00026515548,0.00009555593,0.00018633765,0.0020449134],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906987,0.0003184316,0.000047481768,0.00012948184,0.0003073559,0.00012727894],"domain_scores_gemma":[0.99737906,0.0018299768,0.00016965986,0.00019241104,0.00026781068,0.00016109893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00126319,0.0015087452,0.0012238486,0.0016657781,0.0006550037,0.0012409898,0.0016017038,0.0013051194,0.001903464],"category_scores_gemma":[0.006969176,0.00072313857,0.000932843,0.0007803444,0.0014540206,0.0014812929,0.0016965437,0.00093235256,0.0003810686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011798779,0.000114255425,0.0011584902,0.0001027088,0.00008139523,0.00018502453,0.00017660856,0.9206145,0.0026633677,0.011456821,0.00063529477,0.06269365],"study_design_scores_gemma":[0.0000144581945,0.000033497614,0.0000698031,0.0000037594534,0.000013123458,0.00001463687,0.000013273988,0.9947797,0.00068585604,0.003986893,0.00037826932,0.0000066844923],"about_ca_topic_score_codex":0.0075989733,"about_ca_topic_score_gemma":0.008877063,"teacher_disagreement_score":0.0075989733,"about_ca_system_score_codex":0.0010506811,"about_ca_system_score_gemma":0.0011722456,"threshold_uncertainty_score":0.015109479},"labels":[],"label_agreement":null},{"id":"W3093947831","doi":"10.1109/cog47356.2020.9231637","title":"Evolving Initial Heuristic Functions for Agent-Centered Heuristic Search","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Games (CoG)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristics; Incremental heuristic search; Pathfinding; Computer science; Heuristic; Beam search; Artificial intelligence; Hyper-heuristic; Context (archaeology); Domain (mathematical analysis); Class (philosophy); Consistent heuristic; Mathematical optimization; Theoretical computer science; Machine learning; Graph; Search algorithm; Mathematics; Algorithm; Robot; Mobile robot","score_opus":0.13136062393839582,"score_gpt":0.32366120807018145,"score_spread":0.19230058413178563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093947831","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009415298,0.00020796887,0.9862619,0.00009989158,0.000028940733,0.00010807582,0.000051203682,0.00047496168,0.0033517936],"genre_scores_gemma":[0.24911338,0.00035406585,0.74763,0.00012275443,0.000024730063,0.0004919073,0.00024892847,0.00020129219,0.00181297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990748,0.0003484018,0.00006445966,0.00013652515,0.00028574807,0.00009008035],"domain_scores_gemma":[0.9968696,0.0019539592,0.00024157751,0.00030210326,0.00053703296,0.00009567418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021950502,0.0011211615,0.00094163715,0.0016724103,0.0006468558,0.0017235359,0.0016109301,0.0013824182,0.003981674],"category_scores_gemma":[0.012834347,0.000501911,0.00073405507,0.0012077925,0.0016744735,0.0020491555,0.0012478093,0.0017548099,0.0008686495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084926396,0.00010624541,0.0010357442,0.00018479217,0.00003932884,0.000089582856,0.000262955,0.7193109,0.0019967626,0.13049681,0.0023067552,0.14408511],"study_design_scores_gemma":[0.00002331092,0.000048389,0.00008536089,0.000042241754,0.000014832677,0.000029138208,0.0000402845,0.9548979,0.0011705472,0.040682565,0.0029518649,0.000013514222],"about_ca_topic_score_codex":0.0035587633,"about_ca_topic_score_gemma":0.0039843246,"teacher_disagreement_score":0.003981674,"about_ca_system_score_codex":0.0022499627,"about_ca_system_score_gemma":0.0020714102,"threshold_uncertainty_score":0.01632464},"labels":[],"label_agreement":null},{"id":"W3094342878","doi":"10.1109/cog47356.2020.9231887","title":"Can Deep Learning Predict Problematic Gaming?","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Games (CoG)","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Focus (optics); Deep learning; Artificial intelligence; Balance (ability); Machine learning; Class (philosophy); Data science; Psychology","score_opus":0.1098606878868081,"score_gpt":0.347349941712742,"score_spread":0.23748925382593394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094342878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61823195,0.021985024,0.266917,0.06416482,0.0015181128,0.0002149047,0.0045952164,0.0020494603,0.020323424],"genre_scores_gemma":[0.97010887,0.0025467074,0.021608349,0.0016787995,0.00024213972,0.00005609121,0.0014696304,0.000058373706,0.0022310712],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999564,0.00015751852,0.000017230697,0.00009523517,0.000067063396,0.00009888696],"domain_scores_gemma":[0.9986425,0.000633871,0.00016897061,0.00011267877,0.00022203078,0.00022002768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013808267,0.0012336376,0.0006759127,0.0011338195,0.00029594442,0.0019185151,0.0009570696,0.0015191914,0.002171278],"category_scores_gemma":[0.0070134224,0.00029493182,0.00039529544,0.0007347475,0.00056463975,0.0026315036,0.0008578271,0.0028822126,0.0010145429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005788518,0.0014578489,0.20362015,0.0004755077,0.0006173494,0.00021747792,0.00035613138,0.09034291,0.0028876269,0.015400105,0.047510523,0.6365355],"study_design_scores_gemma":[0.00004200134,0.00018269118,0.022203801,0.00032874956,0.00012113373,0.00012437633,0.00032698357,0.8675039,0.0011555774,0.10120207,0.006757276,0.00005147746],"about_ca_topic_score_codex":0.00569797,"about_ca_topic_score_gemma":0.007536537,"teacher_disagreement_score":0.00569797,"about_ca_system_score_codex":0.0006885949,"about_ca_system_score_gemma":0.00070134917,"threshold_uncertainty_score":0.011329591},"labels":[],"label_agreement":null},{"id":"W3094375143","doi":"10.1109/cog47356.2020.9231854","title":"Monte Carlo Tree Search Strategies in 2-Player Iterated Prisoner Dilemma Games","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Games (CoG)","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Monte Carlo tree search; Computer science; Iterated function; Prisoner's dilemma; Game tree; Tree (set theory); Dilemma; Game theory; Monte Carlo method; Fictitious play; Adversary; Variety (cybernetics); Mathematical optimization; Artificial intelligence; Mathematical economics; Sequential game; Mathematics; Computer security","score_opus":0.085846143607329,"score_gpt":0.3095868613929219,"score_spread":0.2237407177855929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094375143","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43113437,0.0013415013,0.55156904,0.00035173673,0.00007795568,0.00025708808,0.00008832407,0.00026158828,0.0149185],"genre_scores_gemma":[0.9424213,0.00026199146,0.0557393,0.000070764916,0.0000121200455,0.00016664645,0.000052095293,0.000027597715,0.0012481635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977914,0.0015830536,0.00006270752,0.00011809894,0.00030102453,0.00014366962],"domain_scores_gemma":[0.9930247,0.0059598605,0.00038017397,0.00014465407,0.00029313256,0.00019741006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002791074,0.00057792256,0.0008859328,0.0008245222,0.00053641264,0.001164098,0.0009770739,0.0013024309,0.0014384313],"category_scores_gemma":[0.01009263,0.00032997306,0.0005023171,0.00065116055,0.0009971458,0.0013888573,0.0007049278,0.0005925724,0.00018319795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014700243,0.00006620436,0.0012298524,0.000048641345,0.00004426299,0.00005616291,0.00008886182,0.962873,0.00037690156,0.02667251,0.0002142576,0.008182311],"study_design_scores_gemma":[0.000016423714,0.000066180495,0.00010917314,0.000006374189,0.000005663614,0.000017060198,0.0000122568445,0.9929254,0.00010706532,0.0065217777,0.00020683605,0.000005786958],"about_ca_topic_score_codex":0.004118555,"about_ca_topic_score_gemma":0.0032559312,"teacher_disagreement_score":0.004118555,"about_ca_system_score_codex":0.0009972488,"about_ca_system_score_gemma":0.0011258519,"threshold_uncertainty_score":0.014760792},"labels":[],"label_agreement":null}]}