{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"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","author_layer_release":"2026-06-26"},"query_hash":"63b634f1c600","filters":{"venue":"Huadong Li-Gong Daxue xuebao"}},"results":[{"id":"W2366166569","doi":"","title":"Projective Genetic Algorithm","year":2000,"lang":"en","type":"article","venue":"Huadong Li-Gong Daxue xuebao","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"CAE (Canada)","funders":"","keywords":"Projective test; Genetic algorithm; Computer science; Genetic representation; Meta-optimization; Algorithm; Mathematical optimization; Mathematics; Pure mathematics","authors":[{"name":"Le Hui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01239832406851907,"gpt":0.2545149076565105,"spread":0.2421165835879915,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006818677,0.0007535642,0.0008403935,0.000859409,0.0007044765,0.00120352,0.001303984,0.001022611,0.00575747],"category_scores_gemma":[0.002076762,0.0003256341,0.0008089018,0.001284563,0.0006901997,0.001063977,0.001115207,0.0009373231,0.001517416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006631271,"about_ca_system_score_gemma":0.001113477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917722,"about_ca_topic_score_gemma":0.001706406,"domain_scores_codex":[0.9994357,0.0001748329,0.00002359139,0.0001136176,0.0001933497,0.00005889617],"domain_scores_gemma":[0.9996499,0.0001203089,0.00003875233,0.00005701767,0.000115106,0.00001894748],"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":[0.00008899624,0.00007120405,0.001394033,0.0002532891,0.0001767158,0.0002124204,0.0001611995,0.4470632,0.007638381,0.1833676,0.01031952,0.3492535],"study_design_scores_gemma":[0.0000491729,0.0001309793,0.0004866124,0.00003323412,0.00007174841,0.0002838776,0.00003011406,0.9346556,0.003207891,0.03330476,0.02771396,0.00003209506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006218445,0.0006154813,0.9769763,0.0001963731,0.0001097677,0.00008069725,0.00008027792,0.0008893234,0.01483336],"genre_scores_gemma":[0.3539503,0.001860863,0.6227201,0.0004844754,0.000152341,0.0005287136,0.0005144437,0.0002850744,0.0195037],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00575747,"threshold_uncertainty_score":0.0192607,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2354988967","doi":"","title":"An Analysis of the Intermediate Target Choice of China's Monetary Policy","year":2007,"lang":"en","type":"article","venue":"Huadong Li-Gong Daxue xuebao","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Monetary policy; Money supply; Inflation (cosmology); Variance decomposition of forecast errors; Monetary economics; Exchange rate; Variance (accounting); Interest rate; Quarter (Canadian coin); Granger causality; Causality (physics); Inflation targeting; Econometrics; Macroeconomics","authors":[{"name":"Jianguo Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01910849243750047,"gpt":0.3408196971467733,"spread":0.3217112047092728,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003131363,0.0001942005,0.0003754135,0.00129862,0.0004855671,0.001440287,0.0003540701,0.0003707915,0.001902609],"category_scores_gemma":[0.006495453,0.0001056129,0.0003037844,0.001073525,0.0004488775,0.0008078092,0.0004468175,0.0005276388,0.00008081853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002548657,"about_ca_system_score_gemma":0.001397474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01442786,"about_ca_topic_score_gemma":0.007400264,"domain_scores_codex":[0.9991026,0.0003935734,0.00004479616,0.0000835805,0.0002037222,0.000171889],"domain_scores_gemma":[0.9976212,0.001238445,0.0004405931,0.00007199615,0.000497514,0.0001302612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001657114,0.0004256724,0.5020673,0.000409553,0.0002947867,0.002140244,0.003472321,0.09341662,0.007379459,0.2479708,0.007542969,0.1332232],"study_design_scores_gemma":[0.0001105562,0.0004179103,0.5028568,0.0000978999,0.0001956309,0.0001437256,0.003430429,0.4575292,0.003451199,0.02652238,0.005169749,0.00007449295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889777,0.0002170192,0.002158358,0.0003395924,0.000009128905,0.00002836477,0.0000696114,0.00001183066,0.008188429],"genre_scores_gemma":[0.998703,0.00008653593,0.0004100422,0.00001365791,0.000005319965,0.000009737567,0.00004148485,0.000002182984,0.0007278454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01442786,"threshold_uncertainty_score":0.02868778,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}