{"meta":{"query_hash":"cc976d28704e","filters":{"venue":"IEEE/CAA Journal of Automatica Sinica"},"cohort_total":25,"direct_labels_cover":0,"predictions_cover":25,"exported":25,"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/cc976d28704e","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE%2FCAA+Journal+of+Automatica+Sinica"},"results":[{"id":"W2735375376","doi":"10.1109/jas.2017.7510550","title":"Design of second order sliding mode and sliding mode algorithms: a practical insight to DC-DC buck converter","year":2017,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Buck converter; Sliding mode control; Robustness (evolution); Settling time; Parametric statistics; Voltage; Transient response; Converters; Computer science; Algorithm; Engineering; Step response; Mathematics; Control engineering; Physics; Nonlinear system; Control (management)","score_opus":0.03760449388677179,"score_gpt":0.3187479894362668,"score_spread":0.281143495549495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735375376","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08723994,0.00017927954,0.9099985,0.00080061593,0.0009142281,0.0003335661,0.000012143778,0.00009633004,0.00042542373],"genre_scores_gemma":[0.81289935,0.000102754755,0.18653552,0.00015760059,0.00015590734,0.000007839099,4.73873e-7,0.000081716455,0.00005885613],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971864,0.000129274,0.0013071294,0.0002983022,0.0005457069,0.00053314597],"domain_scores_gemma":[0.9968383,0.00093580235,0.00072143547,0.0006989247,0.00035166566,0.00045388474],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00065237307,0.00040079904,0.000975646,0.00031478913,0.00021135705,0.00021929998,0.0005589979,0.000215202,0.00012516993],"category_scores_gemma":[0.0009596037,0.00037028728,0.00014963608,0.00015299616,0.00011975552,0.0014418691,0.00012146896,0.0006348581,0.000028777158],"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":[0.000919464,0.0007310921,0.00056428555,0.001792293,0.0033633607,0.0014062746,0.021654766,0.050791327,0.7188449,0.001504785,0.012949459,0.185478],"study_design_scores_gemma":[0.0016354219,0.0003224605,0.00038763558,0.0006042239,0.00017649237,0.0005488807,0.00020258492,0.976374,0.017659042,0.0007303486,0.0008909667,0.00046800022],"about_ca_topic_score_codex":0.0000059781137,"about_ca_topic_score_gemma":0.0000055318446,"teacher_disagreement_score":0.9255826,"about_ca_system_score_codex":0.00016088363,"about_ca_system_score_gemma":0.00020456803,"threshold_uncertainty_score":0.9998749},"labels":[],"label_agreement":null},{"id":"W2773137334","doi":"10.1109/jas.2017.7510691","title":"Economical optimization of grid power factor using predictive data","year":2017,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Dalhousie University; U.S. Department of Energy","keywords":"Factor (programming language); Computer science; Power grid; Predictive power; Grid; Power (physics); Mathematics; Physics","score_opus":0.05302742896056461,"score_gpt":0.28955430898672974,"score_spread":0.23652688002616512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2773137334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7744176,0.00016059712,0.21413334,0.00027893245,0.006316258,0.00021563571,0.00015733587,0.00012232138,0.0041979793],"genre_scores_gemma":[0.9617015,0.00007411001,0.03773776,0.0000152387565,0.00041512158,7.1369743e-7,0.000004779105,0.000040610084,0.000010150603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984566,0.00004033858,0.00088265614,0.00014995104,0.00026409104,0.00020638933],"domain_scores_gemma":[0.99787116,0.00012987222,0.0006786956,0.0010882278,0.000110058536,0.000121963996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003875849,0.0001700325,0.00044089084,0.00014729996,0.00008999043,0.00010979821,0.0011364521,0.000091543196,0.00018953886],"category_scores_gemma":[0.00028317582,0.0001581943,0.00010448173,0.000044808567,0.00011286682,0.000967185,0.00018867549,0.00020040703,0.000007679742],"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":[0.000023287825,0.000057524085,0.00043896807,0.000045733257,0.00037830375,0.000013301835,0.00010542891,0.9941245,0.0008244358,0.000031819174,0.0036381017,0.0003186231],"study_design_scores_gemma":[0.00060391414,0.000105932886,0.009457106,0.0001831337,0.00012397941,0.00003114782,0.000029767576,0.98653466,0.0016764693,0.000035141948,0.0010624473,0.00015632092],"about_ca_topic_score_codex":0.0000042326096,"about_ca_topic_score_gemma":0.0000013099219,"teacher_disagreement_score":0.1872839,"about_ca_system_score_codex":0.00012020583,"about_ca_system_score_gemma":0.00007490275,"threshold_uncertainty_score":0.6450977},"labels":[],"label_agreement":null},{"id":"W2779598397","doi":"10.1109/jas.2017.7510730","title":"SVM-DT-based adaptive and collaborative intrusion detection","year":2017,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":129,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Intrusion detection system; Support vector machine; Computer science; Data mining; Network security; Set (abstract data type); Artificial intelligence; Machine learning; Computer security","score_opus":0.01622038227106846,"score_gpt":0.2659510673315655,"score_spread":0.24973068506049703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779598397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53940725,0.00040618153,0.44978347,0.0044443132,0.003564017,0.00035063003,0.0000041874214,0.00013823815,0.0019017135],"genre_scores_gemma":[0.96791214,0.000100778605,0.03144815,0.00021393276,0.00028810004,0.0000033339368,1.09943116e-7,0.00001030384,0.000023153078],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981653,0.00024226692,0.00064101914,0.00024643462,0.00047554815,0.00022942343],"domain_scores_gemma":[0.9969879,0.0003522736,0.0013458483,0.0005842343,0.00053510384,0.00019468748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009837102,0.00018195096,0.0003728413,0.00020613322,0.0008203443,0.00057779497,0.00080186775,0.00014674939,0.00002228685],"category_scores_gemma":[0.00046300123,0.00015136228,0.00011264671,0.000236508,0.0002252946,0.0014337882,0.00014500809,0.0004086642,0.000017455613],"study_design_candidate":"design_other","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":[0.00089784886,0.00063154526,0.00022095894,0.00009820844,0.00030392184,0.00026500475,0.003487142,0.0010604919,0.040883604,0.0077152727,0.00456371,0.93987226],"study_design_scores_gemma":[0.003521602,0.0047004847,0.014673749,0.00077894423,0.00011104495,0.00046063313,0.00016380053,0.83742046,0.11198125,0.01475878,0.010802931,0.0006263139],"about_ca_topic_score_codex":0.000010235258,"about_ca_topic_score_gemma":0.000028199885,"teacher_disagreement_score":0.939246,"about_ca_system_score_codex":0.00008068115,"about_ca_system_score_gemma":0.00023136256,"threshold_uncertainty_score":0.6309508},"labels":[],"label_agreement":null},{"id":"W2785634791","doi":"10.1109/jas.2017.7510811","title":"Vehicle dynamic state estimation: state of the art schemes and perspectives","year":2018,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":179,"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 Waterloo","funders":"","keywords":"Estimation; State (computer science); Yaw; Vehicle dynamics; Computer science; Control theory (sociology); Control engineering; Engineering; Control (management); Automotive engineering; Artificial intelligence; Algorithm","score_opus":0.005502748775215664,"score_gpt":0.21933693514562574,"score_spread":0.21383418637041007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785634791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864828,0.0006387395,0.011111425,0.0005590593,0.00038902438,0.00012755468,0.000012719367,0.000044013745,0.0006346565],"genre_scores_gemma":[0.9979159,0.00009017026,0.0017686185,0.000018039971,0.000042536594,0.0000017744916,1.7258162e-7,0.000023783656,0.00013896196],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872327,0.00006162856,0.0006545082,0.00009103828,0.00028790935,0.0001816701],"domain_scores_gemma":[0.9990018,0.0001276245,0.00032033073,0.00023337035,0.00023560016,0.000081297076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040940486,0.00013575176,0.0003346098,0.0000797004,0.00007148256,0.00005868937,0.00023256213,0.000037910195,0.000019322864],"category_scores_gemma":[0.00007330593,0.000096242984,0.000109496046,0.0001608342,0.00021236564,0.00019357317,0.000025486295,0.0001897286,0.0000118501375],"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":[0.0005312451,0.0009645113,0.0052179038,0.0019589511,0.005050885,0.000108565924,0.04505695,0.21831273,0.38234386,0.0027353428,0.008298065,0.32942098],"study_design_scores_gemma":[0.0006456368,0.00018589008,0.015094218,0.00024883647,0.00004666514,0.0000790447,0.00017373117,0.9804289,0.0013094862,0.0012775128,0.00038825453,0.00012185239],"about_ca_topic_score_codex":0.0000019509812,"about_ca_topic_score_gemma":0.000010551651,"teacher_disagreement_score":0.76211613,"about_ca_system_score_codex":0.000060489587,"about_ca_system_score_gemma":0.00006335273,"threshold_uncertainty_score":0.3924675},"labels":[],"label_agreement":null},{"id":"W2795756056","doi":"10.1109/jas.2018.7511069","title":"A Mode-Switching Motion Control System for Reactive Interaction and Surface Following Using Industrial Robots","year":2018,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":21,"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 Ottawa","funders":"","keywords":"Computer science; Motion planning; RGB color model; Trajectory; Computer vision; Occupancy grid mapping; Robot; Artificial intelligence; Controller (irrigation); Fuzzy logic; PID controller; Real-time computing; Engineering; Control engineering; Mobile robot","score_opus":0.05085270997990477,"score_gpt":0.3078463335679382,"score_spread":0.25699362358803346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795756056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5682551,0.00002929014,0.42978925,0.000043851145,0.0015276736,0.00016132755,5.479413e-7,0.0000785661,0.0001143894],"genre_scores_gemma":[0.98847055,0.0000017672116,0.010733576,0.000014201907,0.00073234946,0.0000015579474,6.875267e-7,0.000040073865,0.000005223773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985768,0.000119936776,0.00074270624,0.00012404425,0.00022489687,0.00021161442],"domain_scores_gemma":[0.99877286,0.00041574214,0.00043378715,0.00011031083,0.00015919062,0.00010813691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007407634,0.00016632884,0.00041799742,0.00015737106,0.00016898698,0.00013173772,0.00009155954,0.00014488354,0.000005667934],"category_scores_gemma":[0.00023411284,0.0001573826,0.00015817379,0.00012580893,0.000019318953,0.0006779397,0.000008833083,0.00035713956,0.0000036534282],"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":[0.00013529729,0.000022310744,0.0003409564,0.0000824731,0.00030986662,0.000008487669,0.0011145094,0.9018068,0.0920787,0.00004715402,0.000094827556,0.0039586257],"study_design_scores_gemma":[0.0019631723,0.000154942,0.00028868258,0.0007065327,0.00018794657,0.0001408374,0.00052469317,0.99284047,0.0029483452,0.000034337863,0.000059258375,0.00015077759],"about_ca_topic_score_codex":0.000009375467,"about_ca_topic_score_gemma":0.0000019371894,"teacher_disagreement_score":0.42021546,"about_ca_system_score_codex":0.00024405285,"about_ca_system_score_gemma":0.000044974786,"threshold_uncertainty_score":0.6417876},"labels":[],"label_agreement":null},{"id":"W2806832624","doi":"10.1109/jas.2018.7511144","title":"Parallel reinforcement learning: a framework and case study","year":2018,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":73,"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 Waterloo","funders":"","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Machine learning; Markov chain; Action learning; Action (physics); Markov decision process; Markov process; Cooperative learning; Mathematics","score_opus":0.014603650579195477,"score_gpt":0.27574930087607585,"score_spread":0.26114565029688036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806832624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97604746,0.00022654312,0.020761615,0.00010305479,0.001099721,0.00024170257,2.741672e-7,0.00016094753,0.0013586675],"genre_scores_gemma":[0.9978276,0.000024202533,0.0014836708,0.000048436763,0.00045337155,0.000006777056,4.9496787e-8,0.000025749516,0.00013012993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984959,0.000107099964,0.00079335284,0.00010158611,0.0002903336,0.00021175621],"domain_scores_gemma":[0.9990665,0.00021709364,0.00022173749,0.00019353426,0.0001191488,0.00018201247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059761375,0.00016087161,0.00037745756,0.00013410066,0.00012766015,0.00009936839,0.00012326357,0.00009489168,0.00009586495],"category_scores_gemma":[0.0001785545,0.00013266514,0.000089191984,0.00015044237,0.00006238859,0.00014136595,0.000016325295,0.00042480943,0.000047362006],"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":[0.0017264464,0.0029872674,0.013327468,0.0016714155,0.012569052,0.035714183,0.1715203,0.5018925,0.017162617,0.0014266232,0.04284885,0.19715329],"study_design_scores_gemma":[0.0048925164,0.0063927285,0.0015049062,0.00052913994,0.00033535418,0.021165002,0.012405692,0.9325366,0.00037258118,0.00032515603,0.018905101,0.00063523883],"about_ca_topic_score_codex":0.0000123607915,"about_ca_topic_score_gemma":0.000009608929,"teacher_disagreement_score":0.43064407,"about_ca_system_score_codex":0.00004795929,"about_ca_system_score_gemma":0.000028891722,"threshold_uncertainty_score":0.54099274},"labels":[],"label_agreement":null},{"id":"W2911098646","doi":"10.1109/jas.2019.1911330","title":"Adaptive fuzzy dynamic surface control of flexible-joint robot systems with input saturation","year":2019,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":156,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Control theory (sociology); Bounded function; Fuzzy logic; Tracking error; Computer science; Uniform boundedness; Adaptive control; Filter (signal processing); Mathematics; Mathematical optimization; Algorithm; Control (management); Artificial intelligence","score_opus":0.010971944062123222,"score_gpt":0.21784538148184665,"score_spread":0.20687343741972342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911098646","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69114166,0.0038073915,0.2968882,0.00023055269,0.003230181,0.0014045392,0.000057244317,0.00024788472,0.0029923536],"genre_scores_gemma":[0.99233264,0.000026577038,0.0070651406,0.000019570178,0.00019033825,0.0000053756175,0.000001967011,0.00008371513,0.00027465602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99671817,0.00023064636,0.001699092,0.00020475683,0.00076582236,0.00038150288],"domain_scores_gemma":[0.99691236,0.00054157875,0.0011938395,0.00046400004,0.0006970127,0.00019123097],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008705688,0.00036691007,0.0013181958,0.00023143314,0.000036634858,0.000068719535,0.00035114918,0.00019092284,0.000032498672],"category_scores_gemma":[0.00007374382,0.00028247884,0.0002467357,0.0002867051,0.00009419892,0.0004784413,0.000016336964,0.0005021595,0.000101389305],"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":[0.00043134062,0.00011858428,0.0002904039,0.00037108135,0.0013133192,0.000055244913,0.0005899923,0.93775725,0.057737768,0.00036853665,0.00039013434,0.00057636393],"study_design_scores_gemma":[0.004447342,0.0017472515,0.005361093,0.001814349,0.00028818604,0.00044111058,0.000753821,0.9832054,0.0012454478,0.000036670426,0.00022069068,0.00043863792],"about_ca_topic_score_codex":0.000012103793,"about_ca_topic_score_gemma":0.000005380406,"teacher_disagreement_score":0.301191,"about_ca_system_score_codex":0.00028168783,"about_ca_system_score_gemma":0.00022023029,"threshold_uncertainty_score":0.99996275},"labels":[],"label_agreement":null},{"id":"W2987167661","doi":"10.1109/jas.2019.1911765","title":"Finite-time adaptive fault-tolerant control for nonlinear systems with multiple faults","year":2019,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Backstepping; Control theory (sociology); Nonlinear system; Fault tolerance; Actuator; Controller (irrigation); Tracking error; Fault (geology); Computer science; Adaptive control; Artificial neural network; Scheme (mathematics); Control (management); Control engineering; Engineering; Mathematics; Distributed computing; Artificial intelligence","score_opus":0.010135731805380856,"score_gpt":0.21866630639872153,"score_spread":0.20853057459334068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2987167661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45898777,0.0024068768,0.5251591,0.0004151082,0.0047639804,0.004942828,0.0008840833,0.00065635965,0.0017838833],"genre_scores_gemma":[0.97992826,0.000012430025,0.018449806,0.00006933081,0.0009153004,0.000041514813,0.0000076127726,0.00015644633,0.00041930322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99647325,0.00017055645,0.0017031191,0.000295242,0.0007314503,0.00062635285],"domain_scores_gemma":[0.9943385,0.0030794833,0.00086960127,0.0005110178,0.00087923487,0.00032217108],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009319326,0.00051017065,0.001601531,0.00026996544,0.00007903061,0.000098921046,0.00056410034,0.00024678366,0.000046728717],"category_scores_gemma":[0.00034685608,0.0003846475,0.00041041148,0.00022115334,0.00009046675,0.00045712772,0.000017308697,0.00050928554,0.00037447686],"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":[0.0019933134,0.0003186794,0.00054859725,0.00058190554,0.0024207793,0.00014554815,0.0006153879,0.97638416,0.012357459,0.0000665137,0.0035578439,0.0010098228],"study_design_scores_gemma":[0.009641176,0.0017833029,0.0003652383,0.0010471944,0.00024565627,0.0002309972,0.00023085932,0.9771494,0.00035334477,0.000009950082,0.008467682,0.00047516596],"about_ca_topic_score_codex":0.0000062003005,"about_ca_topic_score_gemma":0.000004291809,"teacher_disagreement_score":0.5209405,"about_ca_system_score_codex":0.00020001164,"about_ca_system_score_gemma":0.00021883826,"threshold_uncertainty_score":0.9998605},"labels":[],"label_agreement":null},{"id":"W3045264779","doi":"10.1109/jas.2020.1003288","title":"Formation-containment control using dynamic event-triggering mechanism for multi-agent systems","year":2020,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Containment (computer programming); Event (particle physics); Set (abstract data type); Convergence (economics); Distributed computing; Mechanism (biology); Control (management); Holonomic; Multi-agent system; Mobile robot; Robot; Control theory (sociology); Artificial intelligence","score_opus":0.05207191200711912,"score_gpt":0.3045710648764912,"score_spread":0.2524991528693721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045264779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020503955,0.00035118943,0.9729563,0.002228127,0.0022815957,0.0014423485,0.000057983194,0.00016495776,0.000013516696],"genre_scores_gemma":[0.94441307,0.000014932421,0.05472715,0.00050728285,0.00023487877,0.00004896745,0.0000027489732,0.000037848815,0.000013146207],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99518424,0.0003551249,0.0024923123,0.00039024794,0.0009409648,0.00063708954],"domain_scores_gemma":[0.9955699,0.00043283013,0.002255682,0.00052906014,0.0007207026,0.00049184164],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001437076,0.00039358632,0.0010652845,0.00020813441,0.00024201839,0.0005514862,0.0015230351,0.00015540085,0.000004827065],"category_scores_gemma":[0.0004942002,0.00034708428,0.00055104244,0.00033095197,0.000035968696,0.0013110483,0.00009468133,0.00029906517,0.00003564358],"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":[0.00082518137,0.0024389548,0.00013122559,0.004061551,0.0052393884,0.00095509045,0.011467248,0.2516069,0.6387643,0.06552052,0.0051702727,0.013819338],"study_design_scores_gemma":[0.0059505403,0.0004698667,0.000049368802,0.00043058067,0.00017879426,0.00027162384,0.00024849517,0.98897994,0.0023703,0.00016923354,0.0005398551,0.00034138685],"about_ca_topic_score_codex":0.000008759276,"about_ca_topic_score_gemma":0.0000016233521,"teacher_disagreement_score":0.92390907,"about_ca_system_score_codex":0.00058079226,"about_ca_system_score_gemma":0.0003444534,"threshold_uncertainty_score":0.99989814},"labels":[],"label_agreement":null},{"id":"W3085946920","doi":"10.1109/jas.2020.1003474","title":"A sensorless state estimation for a safety-oriented cyber-physical system in urban driving: Deep learning approach","year":2021,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":51,"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 Waterloo","funders":"","keywords":"Brake; Dropout (neural networks); Chassis; Artificial neural network; Automotive engineering; Computer science; Deep learning; Engineering; Control engineering; Artificial intelligence; Simulation; Machine learning","score_opus":0.0052173091745352715,"score_gpt":0.21788296055767092,"score_spread":0.21266565138313565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3085946920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6455423,0.00016879237,0.3527776,0.000051665473,0.000411772,0.00025863736,0.000006907448,0.00013012215,0.0006521686],"genre_scores_gemma":[0.9895118,0.000012433891,0.010140406,0.0000068941463,0.00017414746,0.00002231121,0.0000082517245,0.000061288476,0.00006245252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99766326,0.00020140805,0.0011767187,0.00019151729,0.00038536283,0.00038171717],"domain_scores_gemma":[0.99850994,0.0004551139,0.0003848521,0.00022178612,0.00026891983,0.00015936849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007483785,0.00023085158,0.0007744891,0.00017982062,0.000074109055,0.000110418565,0.00018029421,0.00010075947,0.000002173283],"category_scores_gemma":[0.00019468204,0.00022072477,0.00026236885,0.0003537259,0.000027543349,0.00021033351,0.00001984814,0.00045710182,0.000005767299],"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":[0.0000748894,0.00019657554,0.00035501973,0.00074040395,0.0002846305,0.000115646384,0.0031324024,0.9778213,0.0060287155,0.0012363542,0.000056852226,0.009957249],"study_design_scores_gemma":[0.0017036654,0.00010623492,0.0015374275,0.00059253495,0.00007712396,0.00026739878,0.00066613394,0.99412286,0.00022289879,0.00006548703,0.0004217777,0.00021643614],"about_ca_topic_score_codex":0.0000029307676,"about_ca_topic_score_gemma":0.0000073552455,"teacher_disagreement_score":0.34396946,"about_ca_system_score_codex":0.0003164276,"about_ca_system_score_gemma":0.0000969431,"threshold_uncertainty_score":0.9000895},"labels":[],"label_agreement":null},{"id":"W3123895068","doi":"10.1109/jas.2020.1003435","title":"Adaptive Pseudo Inverse Control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems","year":2021,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Fundamental Research Funds for the Central Universities; Japan Society for the Promotion of Science; National Natural Science Foundation of China","keywords":"Nonlinear system; Inverse; Control theory (sociology); Class (philosophy); Control (management); Hysteresis; Mathematics; Computer science; Physics; Artificial intelligence; Geometry; Condensed matter physics","score_opus":0.009888876821310375,"score_gpt":0.22124166733977116,"score_spread":0.2113527905184608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123895068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81472915,0.008248808,0.17198606,0.00047990345,0.0021446766,0.0011208407,0.00028315352,0.0001768686,0.0008305605],"genre_scores_gemma":[0.9883477,0.00020025113,0.01096865,0.00008352128,0.00030252247,0.000010240099,0.0000028064742,0.000048025602,0.00003630203],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977427,0.00012664753,0.0012484768,0.00016890779,0.00036525395,0.00034799107],"domain_scores_gemma":[0.99717623,0.0011316334,0.00054042204,0.0002441725,0.0006845386,0.00022300429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005224268,0.00025897849,0.0010172124,0.00029528243,0.000049930466,0.000070730064,0.00021055162,0.00019282223,0.000009244085],"category_scores_gemma":[0.00056284864,0.0002196745,0.0002608254,0.0005746527,0.00007217223,0.00019002674,0.000014373795,0.0003597601,0.0000046707873],"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":[0.0053755166,0.0042097378,0.0018370426,0.0105937645,0.026804328,0.0024126293,0.005078723,0.10981953,0.29600394,0.0042980383,0.047411866,0.48615488],"study_design_scores_gemma":[0.004076895,0.0006474121,0.00013213872,0.0003744107,0.000423985,0.00034887585,0.0001900405,0.9906544,0.0019282245,0.0000767955,0.0009242531,0.00022254839],"about_ca_topic_score_codex":0.000003401989,"about_ca_topic_score_gemma":0.0000023392586,"teacher_disagreement_score":0.8808349,"about_ca_system_score_codex":0.000096317315,"about_ca_system_score_gemma":0.00029238957,"threshold_uncertainty_score":0.8958066},"labels":[],"label_agreement":null},{"id":"W3176538911","doi":"10.1109/jas.2021.1004054","title":"Development of Granular Fuzzy Relation Equations Based on a Subset of Data","year":2021,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":7,"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":"National Natural Science Foundation of China","keywords":"Mathematics; Fuzzy logic; Particle swarm optimization; Granularity; Relation (database); Fuzzy number; Mathematical optimization; Defuzzification; Fuzzy set; Interval (graph theory); Fuzzy set operations; Data mining; Algorithm; Computer science; Artificial intelligence","score_opus":0.0692812921829738,"score_gpt":0.297573387494635,"score_spread":0.22829209531166123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176538911","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059310053,0.0004194455,0.93071425,0.0028184599,0.00083391514,0.00023669415,0.000027015867,0.00004720805,0.0055929446],"genre_scores_gemma":[0.79307824,0.0000050975354,0.2067424,0.00010274379,0.0000392336,0.0000016449325,0.000007497764,0.0000058849964,0.000017234906],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969601,0.00028171053,0.0015184358,0.00021976595,0.00085181056,0.00016819335],"domain_scores_gemma":[0.9963311,0.00085787574,0.0012051414,0.0010111913,0.0004923619,0.000102307844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001745112,0.00012763712,0.00048660664,0.00017450615,0.00007637737,0.000047398957,0.001191384,0.00008169321,0.000013293814],"category_scores_gemma":[0.0006077889,0.00010464067,0.00013081166,0.00047696428,0.000050987743,0.0004640764,0.00010680174,0.00017204488,0.000012230286],"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":[0.00072118617,0.011259489,0.004448724,0.0022792232,0.0024862734,0.0010194894,0.018815646,0.045634285,0.24927448,0.30841476,0.020475548,0.3351709],"study_design_scores_gemma":[0.0055676727,0.0009224431,0.0247609,0.0021854595,0.00025142686,0.00016004212,0.00029977498,0.9259218,0.019197823,0.016371945,0.0037520702,0.00060865027],"about_ca_topic_score_codex":0.0000021006117,"about_ca_topic_score_gemma":0.0000045671964,"teacher_disagreement_score":0.8802875,"about_ca_system_score_codex":0.000050294155,"about_ca_system_score_gemma":0.0012309286,"threshold_uncertainty_score":0.42671227},"labels":[],"label_agreement":null},{"id":"W4224983028","doi":"10.1109/jas.2022.105506","title":"Cooperative and Competitive Multi-Agent Systems: From Optimization to Games","year":2022,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":199,"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 Windsor","funders":"Program of Shanghai Academic Research Leader; Project 211; Chinesisch-Deutsche Zentrum für Wissenschaftsförderung; National Natural Science Foundation of China","keywords":"Computer science; Optimization problem; Multi-agent system; Autonomy; Perspective (graphical); Mathematical optimization; Artificial intelligence","score_opus":0.021633974522397972,"score_gpt":0.26784127805189367,"score_spread":0.2462073035294957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224983028","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005660691,0.00028008717,0.9911825,0.0012303329,0.0009130093,0.0004194117,0.000031695537,0.00013651588,0.00014572417],"genre_scores_gemma":[0.41817304,0.000026961123,0.58122975,0.0004156548,0.00005145457,0.000036094058,0.0000027145911,0.000015738715,0.000048589463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977003,0.00039014601,0.000820336,0.00028809474,0.0005955977,0.0002055221],"domain_scores_gemma":[0.997853,0.0005463886,0.00060734234,0.0003313924,0.00044527935,0.00021660213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062260486,0.00018161396,0.0004261436,0.00031574705,0.0002492744,0.0002483193,0.0007549684,0.000041163537,0.00007190077],"category_scores_gemma":[0.00031926317,0.00016717715,0.00007229201,0.0004920549,0.000068341615,0.00040759178,0.00030414553,0.00024925222,0.0000062182175],"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":[0.000035555702,0.0003576992,0.00008331512,0.00001677588,0.00015985411,0.00006808934,0.006177426,0.9695191,0.00049003813,0.018676225,0.0034127235,0.0010032452],"study_design_scores_gemma":[0.00082455325,0.000867769,0.00035697306,0.00015675266,0.00003872688,0.00017995598,0.0008065845,0.9949243,0.0005372123,0.00023628629,0.00083714764,0.0002337105],"about_ca_topic_score_codex":0.000011888119,"about_ca_topic_score_gemma":6.600275e-7,"teacher_disagreement_score":0.41251236,"about_ca_system_score_codex":0.00018552317,"about_ca_system_score_gemma":0.00018233286,"threshold_uncertainty_score":0.6817286},"labels":[],"label_agreement":null},{"id":"W4295832134","doi":"10.1109/jas.2022.105866","title":"Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic","year":2022,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":42,"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 Waterloo","funders":"Special Project for Research and Development in Key areas of Guangdong Province","keywords":"Trajectory; Computer science; Softmax function; Support vector machine; Sigmoid function; Collision; Gaussian; Function (biology); Inference; Dimension (graph theory); Machine learning; Artificial intelligence; Simulation; Mathematics; Artificial neural network","score_opus":0.007908278095326788,"score_gpt":0.24065500440223014,"score_spread":0.23274672630690335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295832134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997431,0.00021995747,0.0007558766,0.00024024176,0.000832895,0.00012800888,0.000017707638,0.00015632872,0.00021797688],"genre_scores_gemma":[0.9987491,0.00030454152,0.0008417666,0.0000151293,0.000040537456,0.000016935935,0.0000017448046,0.000021970882,0.000008311787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842316,0.00019867865,0.0008398721,0.00012620685,0.00020696399,0.00020510262],"domain_scores_gemma":[0.9992657,0.00027350156,0.00022998052,0.00014857129,0.000023775068,0.000058513797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000893679,0.00013827934,0.00034318372,0.00043193303,0.00009303114,0.00001685258,0.00017974837,0.00010592033,0.000112951704],"category_scores_gemma":[0.000039282128,0.00014316874,0.00007845333,0.00026533863,0.000051556584,0.00023211037,0.000028962077,0.001438398,0.000002451855],"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":[0.000103507424,0.0006195343,0.042188518,0.000117464144,0.00029757756,0.00028354957,0.0024183057,0.8849593,0.0016560629,0.00007488718,0.0017373189,0.06554398],"study_design_scores_gemma":[0.0015215325,0.0003725703,0.33400014,0.0001042121,0.00005772034,0.00037844558,0.0014733553,0.66046786,0.00024832436,0.00022691055,0.0009711716,0.00017777734],"about_ca_topic_score_codex":0.0000051287425,"about_ca_topic_score_gemma":0.00005290281,"teacher_disagreement_score":0.29181162,"about_ca_system_score_codex":0.00041574647,"about_ca_system_score_gemma":0.00010533824,"threshold_uncertainty_score":0.62492037},"labels":[],"label_agreement":null},{"id":"W4312969010","doi":"10.1109/jas.2022.106016","title":"Mpc-based motion planning and control enables smarter and safer autonomous marine vehicles: perspectives and a tutorial survey","year":2022,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":138,"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 Victoria","funders":"","keywords":"SAFER; Context (archaeology); Model predictive control; Resource (disambiguation); Control (management); Computer science; Field (mathematics); Systems engineering; Engineering; Artificial intelligence; Computer security; Computer network","score_opus":0.01022368527740029,"score_gpt":0.22660944616238135,"score_spread":0.21638576088498107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312969010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99311966,0.00095696136,0.0040957867,0.00052868965,0.0005274228,0.00018938485,0.000048504917,0.00009241284,0.00044119856],"genre_scores_gemma":[0.9985711,0.000036517067,0.0010782562,0.000085423424,0.00016354873,0.000005885657,0.0000051570723,0.000024033472,0.000030055751],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985993,0.0002722244,0.0005348332,0.00014733005,0.0002599321,0.00018636104],"domain_scores_gemma":[0.99881196,0.0006752811,0.00016476666,0.000106104504,0.000095391784,0.0001465085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011685612,0.00016365071,0.0003826502,0.00015684255,0.00018387091,0.00010376854,0.00008581275,0.000064357155,0.00018019175],"category_scores_gemma":[0.00015670383,0.0001565363,0.00005226081,0.00010768616,0.000093708695,0.00017791831,0.000036289257,0.00037698136,8.6309655e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007655877,0.0024709385,0.4715308,0.0028729856,0.0048544817,0.0013503314,0.053014588,0.1820719,0.05813295,0.002532591,0.022736654,0.1907759],"study_design_scores_gemma":[0.0076334,0.0006851632,0.58252954,0.00012176268,0.00016344029,0.00038689395,0.0009745731,0.40380213,0.0003205821,0.00049145415,0.0024448275,0.00044620922],"about_ca_topic_score_codex":0.000018146357,"about_ca_topic_score_gemma":0.00000388645,"teacher_disagreement_score":0.22173025,"about_ca_system_score_codex":0.00009282343,"about_ca_system_score_gemma":0.00006758577,"threshold_uncertainty_score":0.63833654},"labels":[],"label_agreement":null},{"id":"W4380765912","doi":"10.1109/jas.2023.123282","title":"Fundamental Limits of Doppler Shift-Based, ToA-Based, and TDoA-Based Underwater Localization","year":2023,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Hong Kong University of Science and Technology; Government of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Multilateration; Doppler effect; Focus (optics); Computer science; FDOA; Underwater; Time of arrival; Acoustics; Angle of arrival; SIGNAL (programming language); Real-time computing; Telecommunications; Wireless; Physics; Geology; Optics; Antenna (radio)","score_opus":0.030975188583073573,"score_gpt":0.2620891405558723,"score_spread":0.23111395197279871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380765912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7965919,0.00043901068,0.1992218,0.0022275213,0.00039968733,0.000342398,0.000036047437,0.00038222273,0.0003594356],"genre_scores_gemma":[0.99516743,0.000037659207,0.0043750727,0.0002468585,0.000070227645,0.000008839847,0.00001484556,0.000057677407,0.000021399703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977544,0.00016132947,0.0011540209,0.00014273231,0.000496898,0.00029064948],"domain_scores_gemma":[0.9985023,0.0004152206,0.00035997244,0.00039966794,0.0001475963,0.00017523275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066172786,0.00023119386,0.00048111295,0.0003771836,0.00009202228,0.00010168335,0.0003601832,0.00014023924,0.00008064773],"category_scores_gemma":[0.000014609604,0.00019865438,0.0001771832,0.00043888806,0.00013101305,0.00019076526,0.000024844796,0.00022907113,0.000042948293],"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":[0.0003350985,0.0008261005,0.0145277465,0.0028008341,0.0007161897,0.00009932402,0.0022948536,0.8809694,0.07516966,0.00021084643,0.01047803,0.011571888],"study_design_scores_gemma":[0.0030667318,0.00050108746,0.005335226,0.0009994298,0.00013371749,0.000042142554,0.00028346624,0.87930286,0.10199987,0.000372197,0.007540236,0.0004230386],"about_ca_topic_score_codex":0.000009251745,"about_ca_topic_score_gemma":0.000012124283,"teacher_disagreement_score":0.19857554,"about_ca_system_score_codex":0.00009395643,"about_ca_system_score_gemma":0.00013365048,"threshold_uncertainty_score":0.81008905},"labels":[],"label_agreement":null},{"id":"W4388579628","doi":"10.1109/jas.2023.123975","title":"Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios","year":2023,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"National Natural Science Foundation of China","keywords":"Ideal (ethics); Motion planning; Control (management); Path (computing); Tracking (education); Computer science; Control theory (sociology); Artificial intelligence; Psychology; Robot; Epistemology; Philosophy","score_opus":0.03489914072935201,"score_gpt":0.3095191981650242,"score_spread":0.2746200574356722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388579628","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04948537,0.00026639077,0.9461762,0.0020292813,0.0014635563,0.0002957672,0.0000062385366,0.00023526303,0.00004198769],"genre_scores_gemma":[0.8581199,0.000009164523,0.14098436,0.00044962924,0.0003676984,0.000009629208,0.0000011354767,0.0000359004,0.000022606853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968538,0.00016745183,0.0011711158,0.00038653042,0.00068278087,0.0007383067],"domain_scores_gemma":[0.9949198,0.0033081844,0.0007492124,0.0004015513,0.00028513503,0.00033615847],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0022101486,0.0003035478,0.00074645743,0.00038653158,0.0003414756,0.00044927775,0.0009157438,0.00016263114,0.000003031088],"category_scores_gemma":[0.0006448262,0.00026818068,0.00022261289,0.00045223028,0.000111861096,0.00080323924,0.00009280431,0.00048984686,0.0000172917],"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":[0.0006413967,0.0013895298,0.019721523,0.0029298116,0.0036089283,0.007782723,0.042772714,0.44987872,0.08795431,0.0032067157,0.04506975,0.33504388],"study_design_scores_gemma":[0.002247888,0.0004607382,0.01866254,0.0010771235,0.00009718784,0.0007484481,0.00016899823,0.972252,0.0002826876,0.0034812898,0.00018190517,0.0003391738],"about_ca_topic_score_codex":0.000002982622,"about_ca_topic_score_gemma":2.1113777e-7,"teacher_disagreement_score":0.8086345,"about_ca_system_score_codex":0.00008698802,"about_ca_system_score_gemma":0.00031215558,"threshold_uncertainty_score":0.99997705},"labels":[],"label_agreement":null},{"id":"W4391305708","doi":"10.1109/jas.2024.124227","title":"Reinforcement Learning in Process Industries: Review and Perspective","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":87,"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":"Reinforcement learning; Markov decision process; Computer science; Process (computing); Control (management); Perspective (graphical); Scheduling (production processes); Process management; Engineering; Artificial intelligence; Markov process; Operations management","score_opus":0.0109358515700378,"score_gpt":0.28140642518813014,"score_spread":0.27047057361809235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391305708","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4025948,0.50352645,0.008093875,0.014880189,0.0056396807,0.002542136,0.0000067959027,0.001972408,0.060743652],"genre_scores_gemma":[0.9963223,0.0032134173,0.00003744999,0.00008530513,0.00010583443,0.000010029689,1.3473073e-7,0.000019972218,0.00020557045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988209,0.000054895943,0.0006660306,0.00009176163,0.00021317991,0.00015321327],"domain_scores_gemma":[0.9995174,0.00012994764,0.00009733112,0.000075520904,0.0000957778,0.0000840564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005753964,0.00012527453,0.0003819212,0.00018806652,0.000027665537,0.00007900815,0.000094089264,0.00007263738,0.000065163455],"category_scores_gemma":[0.00024175567,0.00010220275,0.00006404611,0.00037159876,0.000028358203,0.0002356946,0.0000066441644,0.0005833705,0.000018431814],"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":[0.00024158927,0.0003551985,0.0008110457,0.0654542,0.0050523905,0.0019914242,0.05518695,0.54131407,0.010889329,0.0045753918,0.08028746,0.23384094],"study_design_scores_gemma":[0.0021826618,0.0010301735,0.00061014004,0.034292042,0.00059768173,0.0018545806,0.007209823,0.86764747,0.00140105,0.00070574816,0.08164854,0.00082006975],"about_ca_topic_score_codex":0.000003982762,"about_ca_topic_score_gemma":0.0000020977589,"teacher_disagreement_score":0.59372747,"about_ca_system_score_codex":0.00015698833,"about_ca_system_score_gemma":0.00010560769,"threshold_uncertainty_score":0.4167707},"labels":[],"label_agreement":null},{"id":"W4399060798","doi":"10.1109/jas.2024.124416","title":"Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":11,"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 Victoria","funders":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China; National Natural Science Foundation of China; National Science Foundation","keywords":"Jump; Computer science; Asynchronous communication; Control theory (sociology); Output feedback; Mode (computer interface); Asynchronous learning; Control (management); Markov chain; Hidden Markov model; Artificial intelligence; Mathematics; Machine learning; Physics; Human–computer interaction; Mathematics education; Telecommunications","score_opus":0.01291698917640091,"score_gpt":0.2447246408806657,"score_spread":0.2318076517042648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399060798","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029909097,0.0066373763,0.9552533,0.0002526121,0.0044125128,0.0011748491,0.000047463,0.00092702394,0.0013857844],"genre_scores_gemma":[0.98975164,0.0000155633,0.008000548,0.000055935427,0.001432427,0.00012187464,0.000007832856,0.00022015919,0.00039401487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99576694,0.0005318365,0.0018961233,0.00037244445,0.0006832351,0.0007494364],"domain_scores_gemma":[0.9964568,0.0019373915,0.0005104684,0.00035854254,0.00042672793,0.0003100741],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002160422,0.00054587924,0.0013854073,0.00055551267,0.00019784107,0.00081860577,0.0005091112,0.00031015932,0.000019406805],"category_scores_gemma":[0.0006944236,0.0004719362,0.00065645186,0.0003580618,0.00006992136,0.00049364805,0.00001536379,0.0011260572,0.0000692214],"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":[0.00014137985,0.00009812023,0.00010539195,0.002986164,0.0012339661,0.000080263395,0.0013763517,0.9707774,0.010182014,0.00027632283,0.01113063,0.001611978],"study_design_scores_gemma":[0.002622969,0.0005371247,0.00005931281,0.002214027,0.0003710254,0.00027645513,0.00025486428,0.9785401,0.00030497275,0.000029496083,0.014322127,0.00046747763],"about_ca_topic_score_codex":0.00000636968,"about_ca_topic_score_gemma":8.217724e-7,"teacher_disagreement_score":0.95984256,"about_ca_system_score_codex":0.0006558664,"about_ca_system_score_gemma":0.0003605563,"threshold_uncertainty_score":0.9997732},"labels":[],"label_agreement":null},{"id":"W4399411102","doi":"10.1109/jas.2024.124356","title":"Semi-Decentralized Convex Optimization on $\\mathcal{SO}(3)$","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"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 Toronto","funders":"National Key Research and Development Program of China; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Conic optimization; Regular polygon; Convex optimization; Mathematical optimization; Convex analysis; Mathematics; Computer science; Geometry","score_opus":0.020985921517236397,"score_gpt":0.30264534218709926,"score_spread":0.2816594206698629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399411102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017398567,0.0005938624,0.98039305,0.011508862,0.002114398,0.00024900152,0.000003970352,0.00037400093,0.003023011],"genre_scores_gemma":[0.55864257,0.0014667311,0.43588075,0.002527136,0.000385254,0.000010827122,0.0000047655844,0.00007152059,0.0010104715],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99705267,0.00028956358,0.001047692,0.00029769982,0.00092521025,0.0003871531],"domain_scores_gemma":[0.9978953,0.0006396456,0.00032786813,0.0004541201,0.00035757947,0.00032549998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012303301,0.00021697815,0.00042298654,0.00040500364,0.00014465633,0.001031019,0.0009609839,0.00012940212,0.0003732741],"category_scores_gemma":[0.00031098386,0.00016978131,0.0002465814,0.00077583344,0.00011129879,0.0009478994,0.00007334154,0.00047530595,0.00022062448],"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":[0.00010628753,0.0008855184,0.000043257907,0.00040839493,0.0005377785,0.00074532104,0.0046441765,0.75291634,0.0017657675,0.101301745,0.08902424,0.047621183],"study_design_scores_gemma":[0.0006899096,0.00040644474,0.00004161322,0.0005376848,0.000027023,0.00021225539,0.000015731954,0.97631776,0.0007550652,0.0017840286,0.019014724,0.00019773853],"about_ca_topic_score_codex":0.0000015540078,"about_ca_topic_score_gemma":2.9188544e-7,"teacher_disagreement_score":0.5569027,"about_ca_system_score_codex":0.00011604243,"about_ca_system_score_gemma":0.0005737553,"threshold_uncertainty_score":0.99421406},"labels":[],"label_agreement":null},{"id":"W4403210875","doi":"10.1109/jas.2024.124692","title":"On Zero Dynamics and Controllable Cyber-Attacks in Cyber-Physical Systems and Dynamic Coding Schemes as Their Countermeasures","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Cybersecurity and Information Systems","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":"Concordia University","funders":"Qatar National Research Fund; North Atlantic Treaty Organization","keywords":"Cyber-physical system; Computer security; Coding (social sciences); Computer science; Zero (linguistics); Mathematics; Philosophy","score_opus":0.010418405129985871,"score_gpt":0.27061781175722,"score_spread":0.2601994066272341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403210875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9654942,0.0019417874,0.025582429,0.0015301098,0.0015744915,0.00035743008,0.000020942221,0.00013783766,0.0033607278],"genre_scores_gemma":[0.999115,0.00016774173,0.0003564564,0.0001596526,0.000075112366,0.000006143371,9.905222e-7,0.000015696407,0.00010319228],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99762166,0.00019196924,0.0010332857,0.00025468663,0.00058800675,0.00031038705],"domain_scores_gemma":[0.9977044,0.0012186237,0.0004130124,0.0003115428,0.00017292178,0.00017951963],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014335993,0.00025329128,0.00067072327,0.00039856986,0.00012359176,0.0012005848,0.00046677614,0.0001258299,0.0000040873215],"category_scores_gemma":[0.00019497052,0.00019207568,0.00011678687,0.00035281086,0.00014068272,0.0014708957,0.00008386353,0.0004977986,0.00003185282],"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":[0.00031916233,0.0008525341,0.0005278084,0.002688529,0.0012722837,0.000830014,0.043199446,0.003688701,0.0049804426,0.8667921,0.009487828,0.065361194],"study_design_scores_gemma":[0.0009845265,0.0003824563,0.00033007725,0.002025738,0.00002480815,0.00088080333,0.00052352715,0.9893823,0.0001516829,0.0036583524,0.0014239961,0.00023169792],"about_ca_topic_score_codex":0.00002113128,"about_ca_topic_score_gemma":0.000014327443,"teacher_disagreement_score":0.98569363,"about_ca_system_score_codex":0.00021006586,"about_ca_system_score_gemma":0.00022457486,"threshold_uncertainty_score":0.99983627},"labels":[],"label_agreement":null},{"id":"W4404294068","doi":"10.1109/jas.2024.124902","title":"From Static and Dynamic Perspectives: A Survey on Historical Data Benchmarks of Control Performance Monitoring","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Fault Detection and Control Systems","field":"Engineering","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":"State Key Laboratory of Industrial Control Technology; National Natural Science Foundation of China","keywords":"Computer science; Control (management); Data science; Artificial intelligence","score_opus":0.019937709763800646,"score_gpt":0.27385551709435985,"score_spread":0.2539178073305592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404294068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987482,0.006024984,0.003117369,0.00016037747,0.0027037247,0.00012913247,0.00012420636,0.00008968914,0.00016851383],"genre_scores_gemma":[0.99885035,0.0003970455,0.00042857308,0.000005212477,0.00025398214,0.000002415163,0.0000037730013,0.000029218201,0.000029438814],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832314,0.00014388321,0.00080583105,0.00018281036,0.00036912196,0.00017523809],"domain_scores_gemma":[0.9981436,0.00112719,0.00016508612,0.00035349498,0.00009046274,0.00012017963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008311356,0.00017360334,0.0005307059,0.00019689566,0.00003670401,0.00007738968,0.00030526778,0.00008641582,0.00003350058],"category_scores_gemma":[0.00024004187,0.00014459263,0.00008056206,0.00017673797,0.000041596682,0.00029519043,0.000017355198,0.0004092016,0.000007811922],"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":[0.004449577,0.0026079882,0.025734885,0.010060176,0.022499228,0.0013644131,0.069582015,0.18018916,0.16683371,0.00019697043,0.09644785,0.42003402],"study_design_scores_gemma":[0.0009868164,0.0004126015,0.029952219,0.0010579498,0.00013788616,0.000051670835,0.0005383269,0.96553326,0.00015868228,0.000035888657,0.00095011713,0.00018461341],"about_ca_topic_score_codex":0.00008156256,"about_ca_topic_score_gemma":0.000012017985,"teacher_disagreement_score":0.78534406,"about_ca_system_score_codex":0.00035690248,"about_ca_system_score_gemma":0.00007628145,"threshold_uncertainty_score":0.5896317},"labels":[],"label_agreement":null},{"id":"W4404563140","doi":"10.1109/jas.2024.125013","title":"Analysis and Control of Frequency Stability in Low-Inertia Power Systems: A Review","year":2024,"lang":"en","type":"review","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"National Natural Science Foundation of China","keywords":"Stability (learning theory); Inertia; Control theory (sociology); Automatic frequency control; Frequency analysis; Power (physics); Control (management); Mathematics; Computer science; Physics; Statistics; Telecommunications; Artificial intelligence; Thermodynamics","score_opus":0.02197325406891956,"score_gpt":0.30680152733500893,"score_spread":0.2848282732660894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404563140","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011110398,0.9958654,0.0004532632,0.00007715633,0.001513554,0.0006061824,0.00009783166,0.00003909793,0.0012364155],"genre_scores_gemma":[0.029372614,0.97004324,0.00013972002,0.00004213362,0.00014537867,0.000043122393,0.000007832901,0.00008526268,0.00012067372],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9893908,0.0018082319,0.006896171,0.0005532016,0.0008537822,0.0004978072],"domain_scores_gemma":[0.9931004,0.0010710212,0.0039987448,0.0010673363,0.00042869462,0.00033380493],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0039780107,0.0007734126,0.009225869,0.0013328191,0.00003621063,0.0001018599,0.0007668878,0.000582254,0.00021976861],"category_scores_gemma":[0.0007298935,0.00048318328,0.0024613568,0.0023526016,0.00018760715,0.00020136037,0.000072733885,0.0008484846,0.000022677024],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049393882,0.0011018035,0.00014106803,0.8544065,0.033880357,0.0013678592,0.0004448274,0.00056613487,0.00006693963,0.0020627012,0.0028935857,0.10301884],"study_design_scores_gemma":[0.00093332207,0.000400332,0.00003890394,0.50681204,0.038273223,0.0007729195,0.0000550029,0.0007414494,0.000005538739,0.0001407309,0.45090783,0.00091871165],"about_ca_topic_score_codex":0.0007728262,"about_ca_topic_score_gemma":0.0002284637,"teacher_disagreement_score":0.44801426,"about_ca_system_score_codex":0.0003225648,"about_ca_system_score_gemma":0.0010866995,"threshold_uncertainty_score":0.999762},"labels":[],"label_agreement":null},{"id":"W4406657782","doi":"10.1109/jas.2024.124824","title":"Deep Synchronization Control of Grid-Forming Converters: A Reinforcement Learning Approach","year":2025,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":5,"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 Victoria","funders":"Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Reinforcement learning; Converters; Grid; Synchronization (alternating current); Reinforcement; Computer science; Control (management); Distributed computing; Artificial intelligence; Engineering; Telecommunications; Electrical engineering; Geology; Structural engineering; Voltage","score_opus":0.004196161012852592,"score_gpt":0.2033903837280886,"score_spread":0.199194222715236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406657782","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005120241,0.0014558064,0.99039465,0.000086648935,0.00059993245,0.00021163355,9.581671e-7,0.0000891852,0.0020409254],"genre_scores_gemma":[0.9927056,0.00032585798,0.0067037717,0.000074066826,0.00011794468,0.0000055959526,0.0000047752487,0.00002074616,0.000041664705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825037,0.00006762238,0.0011074931,0.00009506432,0.0002575485,0.00022191182],"domain_scores_gemma":[0.9989132,0.00017362586,0.00042942396,0.00015723471,0.00025641677,0.00007005256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047692424,0.00016981312,0.0004989606,0.00027632015,0.00006514713,0.00004865315,0.00021800531,0.00010625954,0.0000483145],"category_scores_gemma":[0.0001567398,0.00015265982,0.00016602027,0.00029177207,0.00004883515,0.00028647264,0.000014241718,0.00027165987,0.0000042739543],"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":[0.00004113996,0.00004047245,0.00011647984,0.00029524328,0.00033347434,0.000003035301,0.00037363704,0.97478014,0.002342076,0.00012282735,0.000368852,0.021182647],"study_design_scores_gemma":[0.00204048,0.00013125675,0.00010391325,0.00032987993,0.00020057595,0.000024490711,0.00013112681,0.9950012,0.0012690899,0.000042498912,0.0006004133,0.00012508452],"about_ca_topic_score_codex":0.0000015094291,"about_ca_topic_score_gemma":4.1244812e-7,"teacher_disagreement_score":0.9875853,"about_ca_system_score_codex":0.0001226481,"about_ca_system_score_gemma":0.000098123935,"threshold_uncertainty_score":0.6225287},"labels":[],"label_agreement":null},{"id":"W4411232151","doi":"10.1109/jas.2024.125037","title":"Adaptive Sliding Mode Control with Linear Extended State Observer for Active Magnetic Bearing-Rotor Systems","year":2025,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Magnetic Bearings and Levitation Dynamics","field":"Engineering","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":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Magnetic bearing; Control theory (sociology); State observer; Rotor (electric); Observer (physics); Sliding mode control; Bearing (navigation); State (computer science); Mode (computer interface); Computer science; Physics; Control (management); Engineering; Nonlinear system; Mechanical engineering; Artificial intelligence; Algorithm","score_opus":0.011176608880496545,"score_gpt":0.2472697035075819,"score_spread":0.23609309462708536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411232151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49285018,0.00089679746,0.5000285,0.00036077236,0.0016072026,0.0018825711,0.0001188469,0.0002648373,0.0019903176],"genre_scores_gemma":[0.9744957,0.000043992844,0.024631266,0.000064232634,0.00011355501,0.00006330921,0.0000016422089,0.000052871466,0.000533423],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981311,0.000075367025,0.0009195297,0.00018098802,0.0003285793,0.00036441904],"domain_scores_gemma":[0.99804705,0.00073008926,0.00035513585,0.0002429676,0.00047093775,0.00015383707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041700606,0.00027095067,0.00064388424,0.00023343784,0.00009355489,0.00011460174,0.0002866302,0.00010961995,0.000024059267],"category_scores_gemma":[0.00014922654,0.00022459251,0.00017211368,0.00023881915,0.000057775742,0.0002474749,0.000015676831,0.00037250455,0.0000050507965],"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":[0.0013181914,0.00026823947,0.00017906739,0.0013245773,0.0015035107,0.00006239702,0.0018031386,0.9619784,0.008415104,0.003529016,0.0017497981,0.017868599],"study_design_scores_gemma":[0.003115526,0.0009387835,0.0029941448,0.00075879943,0.00027247646,0.0000364017,0.000310988,0.98952276,0.00046606682,0.0004116465,0.00091687875,0.00025555803],"about_ca_topic_score_codex":0.000012315841,"about_ca_topic_score_gemma":0.000008085019,"teacher_disagreement_score":0.48164552,"about_ca_system_score_codex":0.00015483747,"about_ca_system_score_gemma":0.00018484404,"threshold_uncertainty_score":0.9158617},"labels":[],"label_agreement":null}]}