{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":6,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":6,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"1b1b5196a5ce","filters":{"venue":"Advances in Computer Games"}},"results":[{"id":"W1580378151","doi":"10.1007/978-0-387-35706-5_13","title":"Building the Checkers 10-Piece Endgame Databases","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Chess endgame; Database; nobody; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.03809776430838342,"gpt":0.3123459949166396,"spread":0.2742482306082561,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044801,0.0007180729,0.0006632467,0.0003413014,0.0001862571,0.0003152641,0.003821774,0.0001985371,0.0002315709],"category_scores_gemma":[0.00006748939,0.0005743271,0.0002563552,0.0002214818,0.0005992772,0.001652979,0.001679051,0.0008381105,0.0004060199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002873586,"about_ca_system_score_gemma":0.0002269076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005262207,"about_ca_topic_score_gemma":0.0001276766,"domain_scores_codex":[0.9962708,0.00006136748,0.0008787487,0.001355918,0.0007354417,0.0006977005],"domain_scores_gemma":[0.9963699,0.0008640655,0.0005001952,0.002000255,0.000141431,0.0001241509],"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":[0.000005255088,0.00001845143,0.00001389057,0.00003105453,0.00002276461,0.00008631498,0.0002550808,0.01028251,0.000003550549,0.5921483,0.0005674366,0.3965654],"study_design_scores_gemma":[0.0001009126,0.00008413093,0.00001141556,0.0007786677,0.00001436521,0.00004121103,0.00000853771,0.01641533,0.0005621084,0.3471006,0.6341997,0.0006830663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002130852,0.01296716,0.9286578,0.0008657259,0.002537072,0.0004771503,0.00002058324,0.0003543517,0.0540989],"genre_scores_gemma":[0.01168402,0.01132647,0.9211099,0.003397299,0.003046981,0.0001194665,0.00004194554,0.0002446196,0.04902932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6336323,"threshold_uncertainty_score":0.9996708,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1516840567","doi":"10.1007/978-0-387-35706-5_23","title":"Solving the Oshi-Zumo Game","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Nash equilibrium; Mathematical economics; Computer science; Game theory; Strategy; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05315334453245216,"gpt":0.3524715400949214,"spread":0.2993181955624692,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001294142,0.0003901839,0.0005562491,0.0002663222,0.000158647,0.0002899627,0.002257575,0.0001871418,0.0009235838],"category_scores_gemma":[0.0001380607,0.000249311,0.0002522523,0.0001975281,0.0005379209,0.00045764,0.0005018655,0.0006386686,0.001390904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008390851,"about_ca_system_score_gemma":0.0001006273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003646855,"about_ca_topic_score_gemma":0.00006292402,"domain_scores_codex":[0.9968436,0.00008359829,0.0008961364,0.0008808976,0.000948081,0.0003477061],"domain_scores_gemma":[0.9951223,0.002648033,0.0005125339,0.001477007,0.0001575359,0.00008257879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000678208,0.00001331504,0.00002666936,0.000005652061,0.000008746911,0.00001254448,0.0003540339,0.005841901,0.000001223473,0.6231413,0.000714614,0.3698731],"study_design_scores_gemma":[0.000103019,0.00002234892,0.00007679014,0.0001162634,0.000006351583,0.00001090029,0.00001755507,0.0003668694,0.000008036827,0.5516402,0.4474536,0.000178075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003333527,0.01523467,0.1821067,0.002900404,0.002187179,0.0008781467,0.0000510651,0.0001914152,0.7961171],"genre_scores_gemma":[0.3941571,0.006465461,0.02722236,0.005408886,0.003929906,0.0001855083,0.0000384039,0.0002171234,0.5623752],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.446739,"threshold_uncertainty_score":0.9999959,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1579046794","doi":"10.1007/978-0-387-35706-5_9","title":"DF-PN in Go: An Application to the One-Eye Problem","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Problem solver; Solver; Order (exchange); Computer science; Mathematics; Theoretical computer science; Algorithm; Mathematical optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.02263971972645847,"gpt":0.299328276221947,"spread":0.2766885564954885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004539659,0.0004673574,0.00049775,0.0003911593,0.00008410402,0.0002384302,0.003126162,0.0002326503,0.0000199927],"category_scores_gemma":[0.0000125181,0.0004063045,0.00009981962,0.0003071364,0.000162179,0.001132776,0.0007838706,0.0006205893,0.0004538604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003347166,"about_ca_system_score_gemma":0.0001398411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001007107,"about_ca_topic_score_gemma":0.002406451,"domain_scores_codex":[0.9968553,0.00006156397,0.000804549,0.001243071,0.0005310909,0.0005044505],"domain_scores_gemma":[0.9976628,0.0001970148,0.0002965421,0.001600824,0.0001213776,0.0001214789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005783839,0.00005039545,0.00008563569,0.0000240009,0.000005502286,0.00001250114,0.001466457,0.06320558,0.000003680785,0.3249925,0.00005969993,0.6100883],"study_design_scores_gemma":[0.000108282,0.0002496829,0.0002178414,0.000617345,0.000005683864,0.000006672941,0.00001377597,0.04241214,0.0002024469,0.6500478,0.3054238,0.0006944833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008938667,0.002027629,0.962756,0.002056206,0.0007585153,0.001343424,0.000005843775,0.0002139123,0.03074908],"genre_scores_gemma":[0.07346686,0.002912106,0.8931605,0.005844764,0.002421796,0.0008690314,0.00004681212,0.0002214338,0.02105669],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6093938,"threshold_uncertainty_score":0.9998389,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1489504788","doi":"10.1007/978-0-387-35706-5_17","title":"Solving 7×7 Hex: Virtual Connections and Game-State Reduction","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Outcome (game theory); Reduction (mathematics); Sequential game; Game tree; Computer science; State (computer science); Connection (principal bundle); Tree (set theory); Combinatorial game theory; Extensive-form game; Monte Carlo tree search; Game theory; Theoretical computer science; Mathematical optimization; Mathematical economics; Algorithm; Mathematics; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.01846941880043569,"gpt":0.2704984088857533,"spread":0.2520289900853177,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002269204,0.00050163,0.0005534693,0.0004890559,0.0001419517,0.0002915103,0.0007446098,0.0002222648,0.0000385949],"category_scores_gemma":[0.00002791286,0.0005368029,0.0001295591,0.0001443887,0.0004246535,0.001600622,0.0006000599,0.0006320919,0.00009126544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002367606,"about_ca_system_score_gemma":0.0001360437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004142169,"about_ca_topic_score_gemma":0.0001268261,"domain_scores_codex":[0.9972997,0.00003916611,0.0007237803,0.001118961,0.0003686405,0.0004497123],"domain_scores_gemma":[0.9983832,0.0002708787,0.0003594064,0.0007209873,0.0001384348,0.0001270706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000696902,0.00002193248,0.00001550335,0.00002966027,0.00002113657,0.00005099736,0.001270606,0.02042449,0.00001342838,0.3458147,0.00008364109,0.6322469],"study_design_scores_gemma":[0.0002385075,0.0004326204,0.00004754498,0.001101138,0.00001759209,0.0002391633,0.00004546185,0.04404821,0.000870587,0.8424483,0.1094015,0.001109336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003375994,0.006834134,0.9675534,0.0004726184,0.003966149,0.0003880768,0.000007996202,0.0003814687,0.02005851],"genre_scores_gemma":[0.4065874,0.05214388,0.4235261,0.001565354,0.004568689,0.0001734925,0.00004653917,0.0004221712,0.1109664],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6311375,"threshold_uncertainty_score":0.9997084,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1526187220","doi":"10.1007/978-0-387-35706-5_15","title":"Search and Knowledge in Lines of Action","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Olympiad; Action (physics); Domain (mathematical analysis); Gold medal; Computer science; Class (philosophy); Position (finance); Artificial intelligence; Mathematics education; Psychology; Mathematics; Art; Business; Art history","retraction":null,"screen_n_in":null,"score":{"opus":0.0518174757458234,"gpt":0.3466774546907443,"spread":0.2948599789449209,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002585309,0.0002838334,0.0004771934,0.0005649052,0.0000246523,0.00005202738,0.0007406425,0.0002022096,0.00001412499],"category_scores_gemma":[0.00001191039,0.0002857842,0.00006732657,0.0001561108,0.0002660868,0.0009197442,0.0005575852,0.0004164624,0.00002497014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001218532,"about_ca_system_score_gemma":0.0001486408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005561282,"about_ca_topic_score_gemma":0.0005963398,"domain_scores_codex":[0.9982565,0.00003836134,0.000583299,0.0006214488,0.000237544,0.0002628616],"domain_scores_gemma":[0.9989094,0.000305724,0.00014711,0.0004702909,0.0001152985,0.00005225048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007403138,0.0000380673,0.0003262789,0.0001450149,0.000006355796,0.00002343787,0.0009274767,0.007920894,0.00001141529,0.2287074,0.00001101583,0.7618752],"study_design_scores_gemma":[0.0005790233,0.0006359345,0.001185549,0.004760351,0.00001291567,0.00005212123,0.00007940302,0.1743308,0.007691861,0.7305566,0.07872524,0.001390215],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006421624,0.04786011,0.8851394,0.0004957733,0.003279351,0.0008574941,0.000009237953,0.0002128545,0.05572414],"genre_scores_gemma":[0.5803531,0.05313458,0.3398674,0.000373143,0.001681999,0.00005525557,0.00001535619,0.0001665588,0.02435267],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.760485,"threshold_uncertainty_score":0.9999594,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1548895693","doi":"10.1007/978-0-387-35706-5_1","title":"Evaluation Function Tuning via Ordinal Correlation","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristic; Metric (unit); Correlation; Computer science; Function (biology); Feature (linguistics); Quality (philosophy); Evaluation function; Space (punctuation); Artificial intelligence; Ordinal optimization; Mathematics; Data mining; Machine learning; Ordinal data; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03255499166891886,"gpt":0.2965026661006124,"spread":0.2639476744316935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008735927,0.0004420711,0.0004128705,0.0004779389,0.0001196279,0.0001736402,0.0008395324,0.0003047749,0.0001817141],"category_scores_gemma":[0.00003551813,0.0004739328,0.0001418733,0.0001452826,0.0001346674,0.001913821,0.0003223785,0.0005681234,0.0003350195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006533225,"about_ca_system_score_gemma":0.0002438622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001966938,"about_ca_topic_score_gemma":0.0001015515,"domain_scores_codex":[0.9967765,0.0000891816,0.0007258445,0.0009474411,0.001109283,0.0003517698],"domain_scores_gemma":[0.9980603,0.0002441299,0.0004952745,0.0007373139,0.0003868407,0.00007607588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000786303,0.00001550316,0.00003623757,0.00001533738,0.00001658114,0.0000117791,0.0001992348,0.1249355,0.000003107771,0.12338,0.00005880475,0.7513199],"study_design_scores_gemma":[0.0001251312,0.000167497,0.00007476049,0.0003794128,0.00003162818,0.00001474416,0.000003241104,0.4780514,0.00004276869,0.4947024,0.02603973,0.0003673001],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002378574,0.004444508,0.9334579,0.0001228044,0.005667622,0.000479534,0.000001462334,0.0002292054,0.05557321],"genre_scores_gemma":[0.4339418,0.004430498,0.5097229,0.00184584,0.006033081,0.0002934863,0.000242095,0.0003604845,0.04312985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7509527,"threshold_uncertainty_score":0.9997712,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}