{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":228,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":228,"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":"1788740cb6df","filters":{"venue":"IEEE Transactions on Cybernetics"}},"results":[{"id":"W2944466752","doi":"10.1109/tcyb.2019.2902868","title":"Adaptive Fuzzy Finite-Time Control of Nonlinear Systems With Actuator Faults","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":332,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University; Carleton University","funders":"Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Control theory (sociology); Backstepping; Actuator; Nonlinear system; Controller (irrigation); Tracking error; Fuzzy logic; Variable structure control; Computer science; Fault tolerance; Adaptive control; Mathematics; Sliding mode control; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.007514784480100385,"gpt":0.1898770611687079,"spread":0.1823622766886075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001256411,0.0003472409,0.0006058294,0.0001804869,0.0000373212,0.00002077688,0.0002180914,0.0001911097,0.00007170407],"category_scores_gemma":[0.000005270485,0.0003073296,0.000137964,0.0002380803,0.00007206664,0.0001206738,8.142208e-7,0.0003539027,0.0007546972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001114887,"about_ca_system_score_gemma":0.00005647253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000419739,"about_ca_topic_score_gemma":0.00002124769,"domain_scores_codex":[0.9984062,0.00006620328,0.0004795158,0.0002803265,0.0004240564,0.0003436557],"domain_scores_gemma":[0.9985852,0.0004577882,0.0001211866,0.0004782485,0.0002192743,0.000138302],"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":[0.0003039787,0.0001244878,0.00002748922,0.00008806774,0.0004588345,0.000008895006,0.0001834982,0.9912456,0.006389405,0.00003764142,0.00004753584,0.001084549],"study_design_scores_gemma":[0.003130111,0.001059491,0.00008194862,0.0002645077,0.0001667982,0.00001667578,0.0001845023,0.9871939,0.005981399,0.0000036254,0.001481821,0.0004351905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1333257,0.0002868919,0.8572803,0.00002900948,0.00138828,0.00164358,0.0008516207,0.0004542682,0.0047403],"genre_scores_gemma":[0.9963387,0.00002198633,0.001966714,0.0000204708,0.0001160822,0.0000465785,0.000005253851,0.0001108512,0.001373425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8630129,"threshold_uncertainty_score":0.9999379,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3124774482","doi":"10.1109/tcyb.2020.3046316","title":"Finite-Time-Prescribed Performance-Based Adaptive Fuzzy Control for Strict-Feedback Nonlinear Systems With Dynamic Uncertainty and Actuator Faults","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":291,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Department of Education of Liaoning Province; National Natural Science Foundation of China","keywords":"Control theory (sociology); Actuator; Fuzzy logic; Controller (irrigation); Nonlinear system; Tracking error; Computer science; Bounded function; Fuzzy control system; Fault (geology); Adaptive control; Scheme (mathematics); Control engineering; Control (management); Engineering; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01021667281502786,"gpt":0.2024559308727539,"spread":0.192239258057726,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001679719,0.0004438403,0.0005813825,0.0001579759,0.0001591147,0.00007708854,0.0001575962,0.0002231755,0.00001760322],"category_scores_gemma":[0.00002156619,0.0004131221,0.0001327725,0.0002782744,0.00009909448,0.0001344929,0.000001323629,0.0003535796,0.00004215543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002414145,"about_ca_system_score_gemma":0.0001684553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002658522,"about_ca_topic_score_gemma":0.0001280384,"domain_scores_codex":[0.9981951,0.00009918706,0.0004587789,0.0004309595,0.0003391166,0.0004768188],"domain_scores_gemma":[0.9979098,0.0009581462,0.00009548712,0.0004149599,0.0004131124,0.0002084556],"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":[0.0007424143,0.0001120217,0.00001097184,0.0001651285,0.0003625153,0.00001406589,0.00009645529,0.9929314,0.002173494,0.000007053722,0.00005015422,0.003334307],"study_design_scores_gemma":[0.005485747,0.0007442124,0.000108959,0.0002458318,0.0002711802,0.00001899761,0.0001976407,0.9887388,0.002536666,0.000002588118,0.001180811,0.0004685604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1065688,0.0003757605,0.8888072,0.00007541505,0.0006672179,0.001335815,0.001572823,0.0003335614,0.0002634343],"genre_scores_gemma":[0.9921362,0.00007010796,0.006507165,0.00005493367,0.0001186361,0.0002354116,0.00004729388,0.0001254159,0.0007048122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8855674,"threshold_uncertainty_score":0.999832,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2066173509","doi":"10.1109/tsmcb.2012.2213808","title":"Gaussian Bare-Bones Differential Evolution","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":268,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"","keywords":"Benchmark (surveying); Differential evolution; Gaussian; Task (project management); Mathematical optimization; Algorithm; Computer science; Differential (mechanical device); Gaussian process; Optimization problem; Mathematics; Engineering; Physics; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.02244593156429011,"gpt":0.2691512136448326,"spread":0.2467052820805425,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002085604,0.0001831013,0.0001624295,0.0002657336,0.0002276246,0.0001398139,0.0005363713,0.0001573254,0.0004745433],"category_scores_gemma":[0.00001166944,0.0001746144,0.00009699297,0.000540684,0.00007568356,0.0004055464,0.000006321534,0.0004225082,0.0005592357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001254523,"about_ca_system_score_gemma":0.00006423795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003599055,"about_ca_topic_score_gemma":0.00001044906,"domain_scores_codex":[0.9981172,0.0001555782,0.0002759226,0.0003011876,0.0006331899,0.0005169095],"domain_scores_gemma":[0.9987737,0.0001253423,0.00004038082,0.0006300189,0.000117625,0.0003129529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001829303,0.008952024,0.0009136617,0.0002109951,0.0006405753,0.00004391774,0.009791532,0.1664613,0.01203127,0.2372821,0.007054206,0.5564355],"study_design_scores_gemma":[0.001107989,0.0002478869,0.005125289,0.00003457605,0.00006340379,0.00005706132,0.00006823177,0.9584576,0.02976305,0.0007914736,0.003600652,0.0006827874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002569627,0.00005678643,0.9930427,0.0003715489,0.0019868,0.0001976601,0.00001181549,0.0002057601,0.001557303],"genre_scores_gemma":[0.9434506,0.00004570125,0.05419144,0.00006435391,0.0001426296,0.00003266866,0.000002073719,0.00002086061,0.002049708],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.940881,"threshold_uncertainty_score":0.718803,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2808787830","doi":"10.1109/tcyb.2018.2842158","title":"Multidirectional Prediction Approach for Dynamic Multiobjective Optimization Problems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":241,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Multi-objective optimization; Particle swarm optimization; Mathematical optimization; Evolutionary algorithm; Population; Computer science; Set (abstract data type); Optimization problem; Pareto principle; Multi-swarm optimization; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01507246840311829,"gpt":0.2555491429524204,"spread":0.2404766745493021,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001964944,0.0003049944,0.0002161356,0.0003388353,0.0005970408,0.0001169015,0.0003819673,0.0001908634,0.00002640931],"category_scores_gemma":[0.00002912746,0.0003268805,0.0001411112,0.0007685686,0.0001920936,0.0006714681,0.000005167702,0.0002457518,0.00002456485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003765267,"about_ca_system_score_gemma":0.0001021249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000145142,"about_ca_topic_score_gemma":0.00002243759,"domain_scores_codex":[0.9979234,0.00008604055,0.000398231,0.0008257783,0.0003807233,0.0003858594],"domain_scores_gemma":[0.9981661,0.000166049,0.0001755268,0.0004908582,0.0008670032,0.0001344223],"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":[0.00003998083,0.0004590969,0.000003202663,0.00001220377,0.00005290251,2.500318e-7,0.0006792755,0.9766106,0.0003849933,0.0002262379,0.00003292252,0.02149832],"study_design_scores_gemma":[0.001446262,0.0005018659,0.00008194282,0.00001839168,0.00003016795,0.00002119085,0.00005293632,0.9894587,0.007574208,0.0002188417,0.0002871109,0.0003083953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007139052,0.00001528125,0.9953471,0.00006692156,0.001508987,0.001387039,0.0001270766,0.0006393195,0.0008368828],"genre_scores_gemma":[0.1776446,0.00004254932,0.8204163,0.00008571438,0.0001148231,0.0005172943,0.00003362632,0.00004935336,0.001095794],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1775732,"threshold_uncertainty_score":0.9999183,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2153260109","doi":"10.1109/tcyb.2013.2279211","title":"Differential Evolution With Two-Level Parameter Adaptation","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":226,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Beijing Information Science and Technology University; Huazhong University of Science and Technology; Shenyang Institute of Automation; National Natural Science Foundation of China; Ministère de l'Économie, de l’Innovation et des Exportations du Québec","keywords":"Population; Convergence (economics); Computer science; Adaptive control; Mathematical optimization; Mathematics; Algorithm; Artificial intelligence; Control (management)","retraction":null,"screen_n_in":null,"score":{"opus":0.03422211415081033,"gpt":0.2601096161588607,"spread":0.2258875020080504,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001667977,0.0001817579,0.0001638202,0.0002363143,0.0001839658,0.0001885818,0.0004477528,0.00007124583,0.0001290431],"category_scores_gemma":[0.00002403288,0.0001574767,0.0000604793,0.0004852735,0.00008480435,0.0002425145,0.000003504812,0.0002718079,0.0001638566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009027038,"about_ca_system_score_gemma":0.00007880192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006479174,"about_ca_topic_score_gemma":0.00007046354,"domain_scores_codex":[0.998139,0.0001982028,0.0002496086,0.0004196634,0.0006863571,0.0003072067],"domain_scores_gemma":[0.9986348,0.0003006483,0.00007822849,0.0006001306,0.0002312384,0.0001549092],"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":[0.0000602955,0.000420141,0.00001704668,0.00001614625,0.00006925615,0.000004207933,0.000471817,0.7455037,0.0004801896,0.01573602,0.00008708268,0.2371341],"study_design_scores_gemma":[0.0008775725,0.000312057,0.0003689529,0.00001577407,0.00002330842,0.00001257548,0.00001138556,0.9924703,0.004530087,0.001008475,0.0001688133,0.0002007289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002534359,0.000003497275,0.9955922,0.0002350677,0.0005002602,0.0002266717,0.00000933295,0.0001599939,0.000738659],"genre_scores_gemma":[0.7237379,0.00000638039,0.2750639,0.00005619949,0.00004041809,0.00003252799,0.000002412763,0.00001675578,0.001043542],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7212035,"threshold_uncertainty_score":0.6421715,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2345097924","doi":"10.1109/tcyb.2015.2509646","title":"A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":200,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Flocking (texture); Reinforcement learning; Markov decision process; Computer science; Drone; Q-learning; Mathematical optimization; Markov process; Distributed computing; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01222864924067867,"gpt":0.2000832340893112,"spread":0.1878545848486325,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001935618,0.0002104025,0.0002098823,0.0002150708,0.00009072213,0.00008047083,0.0004921363,0.00007064876,0.00001028349],"category_scores_gemma":[0.000006868663,0.0001547772,0.00005265294,0.0003353186,0.00003533421,0.0001568023,0.000005145791,0.0002083031,0.0002087647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002499162,"about_ca_system_score_gemma":0.00003786656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004350558,"about_ca_topic_score_gemma":0.00002886416,"domain_scores_codex":[0.998268,0.0001019248,0.0002703499,0.0005279966,0.0004193453,0.0004123511],"domain_scores_gemma":[0.999095,0.0001371688,0.00006600774,0.000508389,0.00002509514,0.0001683684],"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":[0.00003795203,0.0003235631,0.00003917724,0.000006355514,0.00003392526,0.00001028202,0.001128264,0.9418593,0.002021508,0.0004863872,0.00001289258,0.05404036],"study_design_scores_gemma":[0.006820632,0.001711145,0.002194484,0.0006821871,0.00007459276,0.0001092978,0.0003372712,0.9770948,0.006230516,0.0001606656,0.00313375,0.001450677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01370424,0.000010153,0.9847373,0.0003202474,0.0001679551,0.0004607647,0.000008110486,0.0001327691,0.0004584115],"genre_scores_gemma":[0.9863148,0.000003998115,0.01274396,0.00005813924,0.00002307758,0.0001798665,4.663502e-7,0.00002265222,0.0006529829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9726106,"threshold_uncertainty_score":0.6311629,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3043172417","doi":"10.1109/tcyb.2020.3004572","title":"Prescribed-Time Event-Triggered Bipartite Consensus of Multiagent Systems","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":193,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Project of Shandong Province Higher Educational Science and Technology Program; Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Bipartite graph; Lyapunov stability; Settling time; Multi-agent system; Control theory (sociology); Computer science; Lyapunov function; Algebraic graph theory; Mathematics; Control (management); Graph; Theoretical computer science; Artificial intelligence; Engineering; Control engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02538535915877381,"gpt":0.2325033385913612,"spread":0.2071179794325874,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021678,0.0003021332,0.0004962917,0.000126428,0.0001027535,0.0001283988,0.0008444026,0.0001495922,0.00003836278],"category_scores_gemma":[0.0000234777,0.0003037083,0.0002427183,0.0005887304,0.00008569605,0.0001256525,0.00000758586,0.0002538708,0.0005318963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007990108,"about_ca_system_score_gemma":0.0001120058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001456911,"about_ca_topic_score_gemma":0.000009251912,"domain_scores_codex":[0.9972787,0.0002622531,0.0008293204,0.0005700767,0.0006387173,0.0004209345],"domain_scores_gemma":[0.9980665,0.0002555431,0.0002994518,0.000795816,0.0002323688,0.0003502864],"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":[0.000218506,0.001173146,0.00004605571,0.0003316897,0.0007613314,0.0001085148,0.002911972,0.8489388,0.1227665,0.00208191,0.008311343,0.01235028],"study_design_scores_gemma":[0.00173474,0.000340641,0.00006010188,0.000101124,0.00009202599,0.00001344342,0.0000806844,0.9399017,0.0532395,0.00001526291,0.004058484,0.0003622609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01672521,0.0002472765,0.9789488,0.001027093,0.001205823,0.0008512432,0.000285661,0.0003513839,0.0003574821],"genre_scores_gemma":[0.9969451,0.00002050951,0.002147175,0.0001599591,0.00006322707,0.00006287948,0.000004650135,0.00002915431,0.0005673505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9802199,"threshold_uncertainty_score":0.9999415,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3123524846","doi":"10.1109/tcyb.2020.3043361","title":"Efficient Nonlinear Model Predictive Control for Quadrotor Trajectory Tracking: Algorithms and Experiment","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":177,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Key Research and Development Projects of Shaanxi Province; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Stability (learning theory); Model predictive control; Algorithm; Constraint (computer-aided design); Convergence (economics); Computer science; Nonlinear system; Residual; Trajectory; Mathematics; Mathematical optimization; Control (management); Artificial intelligence; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.01291092148416412,"gpt":0.2382214871178214,"spread":0.2253105656336573,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000660685,0.0002113899,0.0002473648,0.00006984932,0.00009781909,0.00003417164,0.00005732222,0.0001222128,0.000008157697],"category_scores_gemma":[0.00000649977,0.0002372975,0.00009434026,0.00009618011,0.0000353382,0.00004667055,4.768867e-7,0.0001577683,0.00000275185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483035,"about_ca_system_score_gemma":0.00003976288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000217399,"about_ca_topic_score_gemma":0.000008104207,"domain_scores_codex":[0.9989784,0.00002563775,0.0002924729,0.0002782873,0.000176525,0.0002486432],"domain_scores_gemma":[0.9993807,0.0001267622,0.00003536651,0.0002056644,0.0001427762,0.000108698],"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":[0.00004974071,0.0001118753,4.717888e-7,0.00003350329,0.00008729514,0.000002153179,0.0004772981,0.9800153,0.01572631,0.00003212145,0.00001153952,0.003452418],"study_design_scores_gemma":[0.001968531,0.0001089523,0.000006264602,0.00003031711,0.00007890588,0.000007586502,0.0001318443,0.9453535,0.0519577,0.00002675717,0.0001207322,0.0002089281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008239831,0.0004435073,0.989269,0.00003164118,0.0005244898,0.0008394626,0.0002773083,0.0002434576,0.0001313214],"genre_scores_gemma":[0.9484997,0.00005584093,0.05060895,0.00003920682,0.00007824226,0.0004698949,0.000006574049,0.00007141838,0.0001702199],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9402598,"threshold_uncertainty_score":0.9676712,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3043869778","doi":"10.1109/tcyb.2020.3005283","title":"Resilient Distributed Fuzzy Load Frequency Regulation for Power Systems Under Cross-Layer Random Denial-of-Service Attacks","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":175,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Thousand Young Talents Program of China; National Key Research and Development Program of China; State Key Laboratory of Robotics and System; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Control theory (sociology); Electric power system; Denial-of-service attack; Phasor measurement unit; Computer science; Lyapunov function; Controller (irrigation); Fuzzy logic; Automatic frequency control; Lyapunov stability; Fuzzy control system; Nonlinear system; Power (physics); Phasor; Control (management); The Internet; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.02216089797944819,"gpt":0.2526315274621564,"spread":0.2304706294827082,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001171549,0.0002251232,0.0002894646,0.0000549771,0.0001276047,0.00006012814,0.0002057111,0.0002208477,0.00005686324],"category_scores_gemma":[0.00001497609,0.0002266979,0.0001449279,0.00038709,0.00007049736,0.0001241651,0.000001433753,0.0002379444,0.00004291891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000129211,"about_ca_system_score_gemma":0.00005810975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000753417,"about_ca_topic_score_gemma":0.0001196901,"domain_scores_codex":[0.9985585,0.00003815482,0.00048302,0.0002747989,0.0003592974,0.0002862917],"domain_scores_gemma":[0.9990147,0.0002035855,0.00006920608,0.0002875877,0.000269837,0.0001550419],"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":[0.0002039354,0.00006285081,0.00002880073,0.0002149403,0.0000741511,0.000001451616,0.0006827068,0.9824532,0.01529832,0.0003739258,0.0005301332,0.00007564235],"study_design_scores_gemma":[0.00735147,0.0005290034,0.002521931,0.0003511401,0.0002985437,0.00001900616,0.0004118117,0.835506,0.1457644,0.0007905022,0.005413726,0.001042448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2021035,0.0003112872,0.79412,0.0003224318,0.001574874,0.0006101998,0.0003747701,0.0001973216,0.0003856638],"genre_scores_gemma":[0.9990722,0.00006137035,0.0004913075,0.000104666,0.00008488429,0.00006063581,0.00002179038,0.00004361608,0.00005951099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7969687,"threshold_uncertainty_score":0.9244472,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2944413439","doi":"10.1109/tcyb.2019.2915094","title":"Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":164,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Discriminative model; Conditional random field; Artificial intelligence; Pattern recognition (psychology); Softmax function; CRFS; Computer science; Hyperspectral imaging; Machine learning; Deep learning","retraction":null,"screen_n_in":null,"score":{"opus":0.0135549603455905,"gpt":0.2282175832358199,"spread":0.2146626228902294,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008196742,0.0001580972,0.0001583628,0.00007784131,0.00008784456,0.00006400051,0.000060682,0.0001595368,0.00005264571],"category_scores_gemma":[0.000006388605,0.0001723029,0.00007728449,0.00008751504,0.00006937635,0.0001294434,4.273765e-7,0.0002234658,0.00003420452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008990295,"about_ca_system_score_gemma":0.00001851063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003596754,"about_ca_topic_score_gemma":0.00001172469,"domain_scores_codex":[0.9992363,0.00002772483,0.0002044467,0.000225423,0.0001202763,0.0001858639],"domain_scores_gemma":[0.9994079,0.0002167401,0.00003576478,0.0001928209,0.0000851184,0.00006161332],"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":[0.000208792,0.00006661539,0.000007817167,0.00003808906,0.0001188146,0.00000112371,0.0003253831,0.8928559,0.09481416,0.0008695768,0.001604298,0.009089461],"study_design_scores_gemma":[0.001902974,0.00008808894,0.0004142742,0.00001323917,0.00005827618,0.000008342719,0.00007567736,0.969793,0.02651371,0.0003231685,0.0006105134,0.0001987681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04910187,0.00003568532,0.9477854,0.0002549332,0.001048204,0.0005189925,0.00004969736,0.0001484559,0.001056723],"genre_scores_gemma":[0.9857606,0.0001047141,0.01329596,0.00006039408,0.0001748786,0.0000291511,0.00004616884,0.00003866667,0.0004894137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9366588,"threshold_uncertainty_score":0.702631,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2802585477","doi":"10.1109/tcyb.2018.2826519","title":"Adaptive Estimated Inverse Output-Feedback Quantized Control for Piezoelectric Positioning Stage","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":154,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Control theory (sociology); Observer (physics); Piezoelectricity; Inverse; Controller (irrigation); Piezoelectric motor; Quantization (signal processing); Computer science; Mathematics; Engineering; Algorithm; Control (management); Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01868841363906721,"gpt":0.2343191971950376,"spread":0.2156307835559704,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000126466,0.0003111566,0.0003368734,0.000237899,0.0002541957,0.00006619073,0.0001770382,0.0001864677,0.0001284667],"category_scores_gemma":[0.0000114215,0.0003283873,0.0001743538,0.0003886785,0.00008423623,0.0001246333,5.377361e-7,0.0002999498,0.000190147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817332,"about_ca_system_score_gemma":0.00005795518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004638236,"about_ca_topic_score_gemma":0.00008239353,"domain_scores_codex":[0.9985721,0.00003586151,0.0003470782,0.0002876232,0.0002124893,0.0005448465],"domain_scores_gemma":[0.9990624,0.0002553625,0.00006277942,0.0002677625,0.0001927951,0.0001589405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001661626,0.0004426611,0.00002419178,0.00007792213,0.001230094,0.00001578599,0.0009603206,0.319999,0.01100253,0.001240679,0.005569058,0.6577761],"study_design_scores_gemma":[0.003230249,0.0008412353,0.00002901188,0.00002924946,0.0001988345,0.00000655648,0.00003690378,0.9851096,0.008935437,0.0001894018,0.001024971,0.0003685817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02410743,0.00008970782,0.9725052,0.00005046485,0.0006727686,0.0006795841,0.0001724279,0.0005417893,0.001180629],"genre_scores_gemma":[0.9940433,0.00005633388,0.004386703,0.0002201256,0.0001565718,0.0001505637,0.000006756899,0.00008812697,0.0008915062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9699359,"threshold_uncertainty_score":0.9999168,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039420041","doi":"10.1109/tcyb.2013.2257745","title":"Biometric Recognition Based on Free-Text Keystroke Dynamics","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":150,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Keystroke dynamics; Word error rate; Computer science; Biometrics; Keystroke logging; Digraph; Relation (database); Speech recognition; Pattern recognition (psychology); Artificial intelligence; Text messaging; Dynamics (music); Data mining; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01674208564071165,"gpt":0.2233365226711794,"spread":0.2065944370304677,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002985685,0.0001942732,0.0001775849,0.0007485111,0.0001703538,0.0001887621,0.0007494582,0.0001366795,0.00006440185],"category_scores_gemma":[0.00002798012,0.0001983338,0.0001331756,0.001189261,0.00004770165,0.0001424318,0.00000279071,0.0002471817,0.0007699488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001238062,"about_ca_system_score_gemma":0.00003650978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004768787,"about_ca_topic_score_gemma":0.00008653248,"domain_scores_codex":[0.9983224,0.0001654478,0.0003203203,0.000423919,0.0004999504,0.0002680017],"domain_scores_gemma":[0.9982524,0.0003190617,0.0001023955,0.001038911,0.0001294356,0.0001578223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007800489,0.003210076,0.0001052239,0.0001474206,0.0001155384,0.000009397591,0.004739982,0.009662509,0.0008155087,0.01247842,0.002304696,0.9663332],"study_design_scores_gemma":[0.0006928843,0.0003440575,0.0002181297,0.00004087815,0.00002011619,0.000004712966,0.00001530505,0.9898791,0.00463704,0.001339057,0.002562467,0.0002462181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009979508,0.000005710162,0.9834495,0.001139238,0.001302372,0.0002162866,0.00005545852,0.0002817457,0.003570162],"genre_scores_gemma":[0.9926181,0.00001002319,0.005809568,0.0006616092,0.00004738279,0.00003256787,0.0000106419,0.00002139757,0.0007887206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9826386,"threshold_uncertainty_score":0.989639,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2591344039","doi":"10.1109/tcyb.2016.2645123","title":"Virtual Network Embedding via Monte Carlo Tree Search","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":150,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Network virtualization; Monte Carlo tree search; Distributed computing; Embedding; Virtual network; Node (physics); Virtualization; Monte Carlo method; Cloud computing; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02488330108598738,"gpt":0.2713734207189075,"spread":0.2464901196329201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000289682,0.0002643472,0.0002596022,0.00009202591,0.001163958,0.0005750502,0.001537974,0.0001748546,0.00003493778],"category_scores_gemma":[0.000008201153,0.0002635045,0.0001816176,0.0002125393,0.0001384647,0.0004032663,0.00001870444,0.0005359539,0.0001642287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007275015,"about_ca_system_score_gemma":0.00006427772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002414622,"about_ca_topic_score_gemma":0.0003230435,"domain_scores_codex":[0.9979691,0.00007536557,0.0002891874,0.0005461497,0.0004756541,0.0006445253],"domain_scores_gemma":[0.9977055,0.0002409684,0.0001104055,0.00161415,0.0001010057,0.000228008],"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":[0.00002409349,0.0001117127,0.0001297376,0.000004643906,0.00005980649,0.00003428604,0.0004723374,0.6473292,0.00006567295,0.001041332,0.001594535,0.3491327],"study_design_scores_gemma":[0.0007971438,0.000415173,0.002397393,0.00008439547,0.00004244611,0.00003519683,0.00002331852,0.9896823,0.00195927,0.000766093,0.003278928,0.0005183892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01769697,0.0001041216,0.977363,0.0005007412,0.002486831,0.0001823936,0.000006839301,0.0002947037,0.001364387],"genre_scores_gemma":[0.9794237,0.0001404964,0.01765713,0.0001997285,0.0003610684,0.00002377087,4.773536e-7,0.00003601902,0.002157636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9617267,"threshold_uncertainty_score":0.9999817,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2342992012","doi":"10.1109/tcyb.2015.2490802","title":"Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":139,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Korea Advanced Institute of Science and Technology; Khalifa University of Science, Technology and Research; National Research Foundation of Korea","keywords":"Computer science; Payload (computing); Botnet; Header; Network packet; Intrusion detection system; Deep packet inspection; Computer network; Data mining; The Internet; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.04886312676214855,"gpt":0.2713130838605043,"spread":0.2224499570983558,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006052222,0.0001449376,0.0001502225,0.0001500726,0.000306324,0.0001929705,0.0003236361,0.0001254568,0.000006707447],"category_scores_gemma":[0.00004123403,0.0001480971,0.00004100057,0.0003068156,0.00004825308,0.0005582846,0.000009437508,0.0001700848,0.00001189861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005932522,"about_ca_system_score_gemma":0.00005668174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002738411,"about_ca_topic_score_gemma":0.000300584,"domain_scores_codex":[0.9987237,0.0001264415,0.0002729784,0.0004338357,0.0002443171,0.0001986814],"domain_scores_gemma":[0.9987977,0.0002425478,0.00009974936,0.0005739114,0.0001447775,0.0001413194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001314701,0.0003678061,0.00000807985,0.00005289667,0.00004728973,0.000001971123,0.0007574719,0.3728835,0.001473381,0.0008105379,0.001689951,0.6205924],"study_design_scores_gemma":[0.003523865,0.0004088062,0.00001223749,0.00003073255,0.00003306919,0.00001144627,0.00001756176,0.9635876,0.01983461,0.001592064,0.01077568,0.0001723011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01059121,0.00006175746,0.9867567,0.0004981014,0.001343334,0.0004607859,0.00002981008,0.0001924248,0.00006589083],"genre_scores_gemma":[0.9723342,0.00006312979,0.02696113,0.00034444,0.0001273936,0.00006484608,0.00002113371,0.00001633483,0.00006737657],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.961743,"threshold_uncertainty_score":0.6039225,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012135745","doi":"10.1109/tcyb.2020.2978003","title":"Neural-Network-Based Sliding-Mode Control of an Uncertain Robot Using Dynamic Model Approximated Switching Gain","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":135,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Control theory (sociology); Artificial neural network; Sliding mode control; Scheme (mathematics); Computer science; Trajectory; Robot; Lyapunov function; Control (management); Mode (computer interface); Control engineering; Engineering; Mathematics; Nonlinear system; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.03205167178672245,"gpt":0.2619411326004206,"spread":0.2298894608136981,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001551969,0.0003535989,0.0005158803,0.0001085166,0.0001004091,0.00003847348,0.0002553013,0.0001779855,0.000009501583],"category_scores_gemma":[0.000008542504,0.000387191,0.0001711959,0.0003144711,0.00003350325,0.0001497507,0.00000112759,0.0004569448,0.000005843315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001639156,"about_ca_system_score_gemma":0.000062006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006441537,"about_ca_topic_score_gemma":0.0001169613,"domain_scores_codex":[0.998237,0.0001154114,0.0005770262,0.0003277737,0.0003125359,0.0004302105],"domain_scores_gemma":[0.9990885,0.0001443519,0.0001185369,0.0003245579,0.0001016808,0.0002223584],"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":[0.0001219898,0.00006116891,0.000005237444,0.00007533491,0.00008994638,0.000007562247,0.0002166195,0.9114496,0.08630686,0.00001601717,0.000004192052,0.001645549],"study_design_scores_gemma":[0.001564159,0.000162785,0.000006875995,0.00008138747,0.0001439856,0.000004373174,0.00004479196,0.9928509,0.004764894,0.00002783265,0.000005937244,0.0003420821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1116078,0.00007886824,0.8869928,0.00008556597,0.0002570011,0.0004296336,0.0001115353,0.0003963911,0.00004041571],"genre_scores_gemma":[0.9719794,0.000006239703,0.02758642,0.0001714399,0.00008635722,0.00001988078,0.000008720486,0.000131977,0.000009502417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8603717,"threshold_uncertainty_score":0.999858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2912832158","doi":"10.1109/tcyb.2018.2890046","title":"Optimal Output Regulation of Linear Discrete-Time Systems With Unknown Dynamics Using Reinforcement Learning","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Higher Education Discipline Innovation Project; Northeastern University; National Natural Science Foundation of China","keywords":"Reinforcement learning; Optimization problem; Optimal control; Mathematical optimization; Control theory (sociology); Computer science; Discrete time and continuous time; Discrete optimization; Noise (video); System dynamics; Control (management); Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.009236036983152505,"gpt":0.2210814403115666,"spread":0.2118454033284141,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000220691,0.000223811,0.0002988975,0.0001746528,0.0001271518,0.00007851372,0.0003880321,0.0001074578,0.000008389435],"category_scores_gemma":[0.000004187186,0.0002048854,0.00009157255,0.0003518274,0.00007821956,0.0002824537,0.000006892122,0.0002989393,0.00004149703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002589643,"about_ca_system_score_gemma":0.00009505002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001114432,"about_ca_topic_score_gemma":0.0000104207,"domain_scores_codex":[0.9983357,0.00009001292,0.0003924385,0.0003737748,0.0004980206,0.0003100441],"domain_scores_gemma":[0.9987833,0.0001119133,0.0002715271,0.0005453208,0.0002115954,0.00007628662],"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":[0.00004886964,0.00004748647,0.00004815929,0.00002585362,0.00007060875,0.000001602188,0.000267196,0.9925767,0.0009848162,0.002200963,6.952109e-7,0.003727091],"study_design_scores_gemma":[0.0006707042,0.0006743278,0.00005939414,0.0001312147,0.00005210214,0.00001616909,0.00005753947,0.9970777,0.0008823477,0.000009718563,0.0001352555,0.0002335321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06811907,0.00001433037,0.930522,0.00003264903,0.0003056104,0.0005023485,0.00000413216,0.0001360873,0.0003637435],"genre_scores_gemma":[0.9428082,0.000002904211,0.053389,0.000009933794,0.00002023783,0.00001120303,0.000005184946,0.0000292577,0.003724102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.877133,"threshold_uncertainty_score":0.8354985,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012655144","doi":"10.1109/tcyb.2013.2263131","title":"Approximation-Based Adaptive Neural Control Design for a Class of Nonlinear Systems","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":123,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University","funders":"National Natural Science Foundation of China","keywords":"Backstepping; Nonlinear system; Control theory (sociology); Bounding overwatch; Class (philosophy); Controller (irrigation); Adaptive control; Artificial neural network; Property (philosophy); Computer science; Mathematics; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02440769489776224,"gpt":0.2201643056086202,"spread":0.195756610710858,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001635588,0.0002649914,0.0004220188,0.0001624051,0.00005880539,0.00004013147,0.000176022,0.0001625045,0.00002072316],"category_scores_gemma":[0.00001267466,0.0002600072,0.0001767271,0.0001562276,0.00006785346,0.0001157702,3.188033e-7,0.0001961408,0.00005204083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001050405,"about_ca_system_score_gemma":0.00004798571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006398224,"about_ca_topic_score_gemma":0.00001219868,"domain_scores_codex":[0.9986152,0.00009436885,0.0005307667,0.0002063259,0.0002520196,0.0003013175],"domain_scores_gemma":[0.9983267,0.0007970063,0.0001114016,0.0002961132,0.0003587829,0.0001099933],"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":[0.00008734484,0.00009189102,0.000002946325,0.0000938876,0.00013769,6.064577e-7,0.0000615693,0.9933932,0.0037679,0.00005883092,0.000244218,0.002059893],"study_design_scores_gemma":[0.002039194,0.0004234273,0.00002198745,0.00006403156,0.00009573001,0.000002576305,0.00008981438,0.9884338,0.008281016,0.00001639905,0.0002998869,0.0002321337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004712695,0.0001360262,0.991236,0.00006246912,0.0008363204,0.002384686,0.0002573836,0.0002211338,0.0001532302],"genre_scores_gemma":[0.976593,0.000003824316,0.0222667,0.00003680915,0.0001218795,0.0007428597,0.000005131426,0.00008288558,0.0001468929],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9718803,"threshold_uncertainty_score":0.9999852,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969839206","doi":"10.1109/tcyb.2014.2360368","title":"A Multirobot Path-Planning Strategy for Autonomous Wilderness Search and Rescue","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":122,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motion planning; Search and rescue; Path (computing); Robot; Computer science; Software deployment; Piecewise; Set (abstract data type); Mathematical optimization; Rescue robot; Operations research; Artificial intelligence; Mobile robot; Engineering; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.04285276070436285,"gpt":0.293325741213344,"spread":0.2504729805089812,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004101132,0.0002321086,0.0002423559,0.0001546747,0.0002951105,0.0002137787,0.0004880029,0.0001461288,0.000002639644],"category_scores_gemma":[0.00001311901,0.0002349048,0.00007049239,0.0002075408,0.00009170538,0.0001864493,0.000005543519,0.0003240331,0.00001898665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005108144,"about_ca_system_score_gemma":0.00007811672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000116808,"about_ca_topic_score_gemma":0.000008888965,"domain_scores_codex":[0.9982951,0.0001088295,0.0002811177,0.0005618745,0.0002828266,0.0004702123],"domain_scores_gemma":[0.9987504,0.0003863645,0.00003640243,0.0005349769,0.00009765698,0.000194153],"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":[0.00001289201,0.00009670706,0.0000201217,0.00003061974,0.00002353588,0.000009244553,0.0009943772,0.869621,0.0004097925,0.0009922043,0.00005118613,0.1277383],"study_design_scores_gemma":[0.0007845983,0.0004612071,0.0008566314,0.00007027106,0.00002036217,0.00004764133,0.00005215773,0.9931204,0.003687314,0.0003081333,0.0003049862,0.0002862666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0188222,0.00004710814,0.9796064,0.0002219424,0.0005241563,0.0003336278,0.00001484652,0.0002484577,0.0001812065],"genre_scores_gemma":[0.7678994,0.000009741379,0.2312446,0.0001034571,0.00006026828,0.00004932797,0.000001871713,0.0000261047,0.0006052082],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7490772,"threshold_uncertainty_score":0.9579138,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2464909783","doi":"10.1109/tcyb.2016.2533545","title":"Multilayered Echo State Machine: A Novel Architecture and Algorithm","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":118,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Engineering and Physical Sciences Research Council","keywords":"Reservoir computing; Benchmark (surveying); Echo state network; Echo (communications protocol); Computer science; Recurrent neural network; Architecture; State (computer science); Artificial intelligence; Algorithm; Machine learning; Artificial neural network","retraction":null,"screen_n_in":null,"score":{"opus":0.01115130030647548,"gpt":0.2205179056549789,"spread":0.2093666053485034,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009696541,0.0001977304,0.0001552265,0.0001038612,0.0001796525,0.0001061407,0.0004091696,0.00006869193,0.000008560944],"category_scores_gemma":[0.000002663447,0.0001281885,0.00007360917,0.0002198772,0.00007093707,0.000120369,0.00001097321,0.0002550796,0.00001599494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002534974,"about_ca_system_score_gemma":0.0000227882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003913485,"about_ca_topic_score_gemma":0.00004953195,"domain_scores_codex":[0.9987568,0.00004171217,0.0002067157,0.0004220671,0.000231679,0.0003409753],"domain_scores_gemma":[0.9991006,0.0002273426,0.00005850965,0.0004053486,0.0000458351,0.0001623667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008441336,0.00008929767,0.000004855062,0.000005415883,0.00002284537,0.00001236451,0.000225221,0.02453553,0.003500291,0.00004260816,0.00003769484,0.9715154],"study_design_scores_gemma":[0.00143367,0.000251141,0.0002456699,0.0001126889,0.00001335917,0.000121383,0.000004766427,0.9734491,0.01999288,0.001086738,0.002880041,0.0004086048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009726011,0.00007431273,0.9879877,0.001220553,0.0005570965,0.0001548047,0.00003083319,0.0001777064,0.00007101377],"genre_scores_gemma":[0.8289171,0.0001581774,0.1694779,0.000254802,0.00005686237,0.000008264615,1.836477e-7,0.00002091977,0.001105775],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9711068,"threshold_uncertainty_score":0.5227374,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3024223975","doi":"10.1109/tcyb.2020.2987811","title":"Compound Adaptive Fuzzy Quantized Control for Quadrotor and Its Experimental Verification","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Japan Society for the Promotion of Science; National Natural Science Foundation of China","keywords":"Control theory (sociology); Underactuation; Backstepping; Initialization; Fuzzy logic; Computer science; Attitude control; Scheme (mathematics); Fuzzy control system; Control engineering; Trajectory; Adaptive control; Control (management); Mathematics; Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.03967711694185177,"gpt":0.2518110424600821,"spread":0.2121339255182303,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005776143,0.000203371,0.000272353,0.00004625313,0.00008340057,0.00003363873,0.0000934176,0.00009781254,0.00001574172],"category_scores_gemma":[0.000006077177,0.0002224213,0.00008770108,0.00007868418,0.00003493745,0.0000930715,4.890462e-7,0.0001515059,0.00004949868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006657589,"about_ca_system_score_gemma":0.00001497732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005605016,"about_ca_topic_score_gemma":0.000007659297,"domain_scores_codex":[0.9991252,0.00003665672,0.000269809,0.0002307679,0.0001445474,0.0001929796],"domain_scores_gemma":[0.9994521,0.0001698455,0.00004363094,0.0001153394,0.00007066803,0.0001483864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002238636,0.0003634508,0.000008803871,0.0001993469,0.000773237,0.00001132108,0.002896083,0.3027903,0.6829472,0.002819948,0.0008498846,0.004101786],"study_design_scores_gemma":[0.003760677,0.0005865447,0.00004736931,0.00002401624,0.0000765393,0.000005138843,0.0003116624,0.9138495,0.07830701,0.00001251946,0.002728853,0.000290135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05474424,0.0006944122,0.9416724,0.0002188034,0.0004994922,0.001355577,0.0002684518,0.0002876926,0.0002589541],"genre_scores_gemma":[0.9977744,0.00002760663,0.001562642,0.0001221691,0.0001524897,0.0002378002,0.000004334449,0.00005959173,0.00005895995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9430302,"threshold_uncertainty_score":0.9070078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2789411207","doi":"10.1109/tcyb.2018.2804759","title":"New Results on Sliding-Mode Control for Takagi–Sugeno Fuzzy Multiagent Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Control theory (sociology); Weighting; Fuzzy logic; Mathematical optimization; Mathematics; Controller (irrigation); Constraint (computer-aided design); Fuzzy control system; Computer science; Control (management); Artificial intelligence; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02593210850899168,"gpt":0.2714775517240211,"spread":0.2455454432150294,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000497391,0.0004703544,0.0005115702,0.0002615881,0.000416404,0.00042018,0.001211634,0.0002618662,0.00001038311],"category_scores_gemma":[0.00005258931,0.0004548824,0.0002966501,0.0004194865,0.00006157358,0.000238752,0.000004542823,0.0003015451,0.0006431472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000312919,"about_ca_system_score_gemma":0.0001982243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005442267,"about_ca_topic_score_gemma":0.0001940057,"domain_scores_codex":[0.996445,0.0001866139,0.0008656959,0.0009883543,0.0007202648,0.0007940771],"domain_scores_gemma":[0.996729,0.0006296372,0.0003216747,0.001462169,0.0004019949,0.0004555772],"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":[0.004298628,0.003214872,0.00002459701,0.0002960798,0.002071487,0.0001022526,0.006930511,0.573075,0.03153853,0.08003435,0.1059893,0.1924244],"study_design_scores_gemma":[0.01365531,0.002471038,0.00009055961,0.0002708625,0.0001830939,0.00003234923,0.0000858156,0.8903534,0.02540541,0.0003362288,0.06614165,0.0009742719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009034653,0.00007161464,0.9863994,0.0009384893,0.006854381,0.001880153,0.0007369429,0.0004923462,0.001723269],"genre_scores_gemma":[0.9859596,0.00001547754,0.008274996,0.0003521968,0.000683481,0.0002346118,0.00001231493,0.00005895807,0.004408387],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9850561,"threshold_uncertainty_score":0.9997903,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2472390602","doi":"10.1109/tcyb.2015.2481713","title":"Multilayer Extreme Learning Machine With Subnetwork Nodes for Representation Learning","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":115,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subnetwork; Extreme learning machine; Computer science; Feature learning; Artificial intelligence; Unsupervised learning; Machine learning; Cluster analysis; Semi-supervised learning; Sparse approximation; Pattern recognition (psychology); Representation (politics); Feature (linguistics); Supervised learning; Artificial neural network; Competitive learning; Generalization; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05347264596570197,"gpt":0.2781317548242277,"spread":0.2246591088585257,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003844162,0.0002147878,0.0001981885,0.0001386078,0.0003500418,0.0001707683,0.0003301169,0.00009017878,0.00001459402],"category_scores_gemma":[0.00003860855,0.0001908892,0.00008597135,0.000397385,0.00004465826,0.0002299723,0.00000415365,0.0004869646,0.00005083201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005748646,"about_ca_system_score_gemma":0.0000564718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001873818,"about_ca_topic_score_gemma":0.00009127089,"domain_scores_codex":[0.9983906,0.0001793372,0.0002351305,0.0004658613,0.0003733067,0.0003558007],"domain_scores_gemma":[0.9988675,0.0002940804,0.0001238408,0.0003524751,0.0001813188,0.000180787],"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":[0.00009387056,0.00009799873,0.0009534135,0.000009233639,0.00003210753,0.000004863141,0.001453815,0.8857215,0.00009288268,0.0002112985,0.0001292262,0.1111998],"study_design_scores_gemma":[0.001380918,0.0006546086,0.000340801,0.00003759274,0.00003502464,0.00002477351,0.0001431621,0.9838393,0.002272621,0.0001621365,0.01082132,0.000287759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01940825,0.00006367499,0.977851,0.0004513323,0.0003945696,0.0002234811,0.000001681649,0.0004325222,0.001173482],"genre_scores_gemma":[0.927817,0.00002231167,0.06495845,0.00008322777,0.00008833245,0.00005047825,0.000006352682,0.00003762385,0.006936149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9128926,"threshold_uncertainty_score":0.7784234,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3009350896","doi":"10.1109/tcyb.2020.2974688","title":"A Multimodal Emotional Human–Robot Interaction Architecture for Social Robots Engaged in Bidirectional Communication","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":113,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Human–robot interaction; Robot; Computer science; Social robot; Human–computer interaction; Humanoid robot; Affect (linguistics); Arousal; Hidden Markov model; Psychology; Artificial intelligence; Cognitive psychology; Mobile robot; Robot control; Communication; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.08859556103709411,"gpt":0.3488916193731837,"spread":0.2602960583360897,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000262691,0.0001983972,0.0002006641,0.0002198972,0.0005716639,0.00003455831,0.0001456626,0.0002415961,0.0009423508],"category_scores_gemma":[0.00002417443,0.0002278823,0.0001933296,0.0002694622,0.00008190513,0.00008541399,0.000001823655,0.001151557,0.0001336215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073774,"about_ca_system_score_gemma":0.0000286156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008824849,"about_ca_topic_score_gemma":0.0005964051,"domain_scores_codex":[0.9982565,0.0005584562,0.0003906968,0.0003627235,0.000192034,0.0002395944],"domain_scores_gemma":[0.9991401,0.0003815628,0.0001217112,0.0001545931,0.0001080431,0.00009394301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004924566,0.009971377,0.0003668271,0.000353072,0.001056744,0.0000200082,0.1082547,0.3226418,0.06344327,0.007680895,0.01944275,0.461844],"study_design_scores_gemma":[0.1203497,0.013331,0.3111944,0.001974237,0.002198591,0.0006600556,0.0370522,0.2047291,0.130056,0.02306327,0.1443722,0.01101924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1259343,0.00003214999,0.8588196,0.00795635,0.001496431,0.001127396,0.0002056539,0.0002837788,0.004144261],"genre_scores_gemma":[0.9945448,0.00001741006,0.003289231,0.0008809062,0.000270693,0.0002619892,0.0001448198,0.00004273727,0.0005473832],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8686105,"threshold_uncertainty_score":0.9999709,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3125674422","doi":"10.1109/tcyb.2020.3043798","title":"Impedance Variation and Learning Strategies in Human–Robot Interaction","year":2021,"lang":"en","type":"review","venue":"IEEE Transactions on Cybernetics","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"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; Government of Alberta","keywords":"Admittance; Robot; Computer science; Nonlinear system; Electrical impedance; Gaussian; Stability (learning theory); Variation (astronomy); Artificial intelligence; Control theory (sociology); Mechanical impedance; Machine learning; Control (management); Engineering; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02822696361212393,"gpt":0.2940563852533856,"spread":0.2658294216412617,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009526395,0.0003083812,0.0006182381,0.0003773853,0.0001295832,0.0001076971,0.00006553873,0.0002111188,0.00003603046],"category_scores_gemma":[0.000004519166,0.0003318067,0.0001552415,0.0004699583,0.00002663947,0.0001575851,0.000001067678,0.001056117,0.00000274581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001384513,"about_ca_system_score_gemma":0.00003295481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004625028,"about_ca_topic_score_gemma":0.0001320697,"domain_scores_codex":[0.998887,0.0001178124,0.0004032468,0.0002598672,0.0001240982,0.0002079442],"domain_scores_gemma":[0.9995199,0.0001868274,0.00007949426,0.0001437219,0.00003269485,0.00003739974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001097136,0.00003815829,3.191786e-7,0.001761738,0.0001710982,0.000003227105,0.0005633907,0.03925748,0.00005102067,0.0000857573,0.00002309682,0.9580436],"study_design_scores_gemma":[0.0008695036,0.0003389949,0.0003968691,0.01710636,0.001195396,0.0000842895,0.00125448,0.01078155,0.0003305553,0.0001494982,0.9653614,0.002131076],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002265088,0.8943108,0.1032252,0.000006445716,0.0005356427,0.0002887262,0.000007264888,0.0002216408,0.001177793],"genre_scores_gemma":[0.04093906,0.9584917,0.0002249388,0.000004707008,0.00004576749,0.0001006533,0.00001441607,0.00005415894,0.0001245532],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9653383,"threshold_uncertainty_score":0.9999134,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2751593041","doi":"10.1109/tcyb.2017.2731601","title":"Scaled Group Consensus in Multiagent Systems With First/Second-Order Continuous Dynamics","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Subnetwork; Multi-agent system; Group (periodic table); Lyapunov function; Stability theory; Consensus; Lyapunov stability; Uniform consensus; Graph theory; Computer science; Order (exchange); Directed graph; Graph; Stability (learning theory); Mathematical optimization; Mathematics; Theoretical computer science; Artificial intelligence; Algorithm; Nonlinear system; Control (management); Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.01290294976963088,"gpt":0.2264547223004822,"spread":0.2135517725308513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003424482,0.0004057109,0.0005409798,0.0002107121,0.0005278988,0.0007738769,0.001436434,0.0002158474,0.00001993492],"category_scores_gemma":[0.0000278411,0.0003777023,0.0001156514,0.0002436607,0.0002105631,0.0002634847,0.00001099666,0.0004348402,0.000117826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003486701,"about_ca_system_score_gemma":0.0001083981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001432879,"about_ca_topic_score_gemma":0.0217985,"domain_scores_codex":[0.9973263,0.0001417826,0.0006258256,0.0007440629,0.000531208,0.0006308333],"domain_scores_gemma":[0.996914,0.0003189824,0.0003907616,0.001921163,0.0002242531,0.0002308683],"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":[0.001249672,0.008471788,0.01553378,0.001186945,0.001996016,0.003550515,0.005198744,0.8357164,0.001751882,0.03336203,0.002783711,0.08919854],"study_design_scores_gemma":[0.005827574,0.000373292,0.007058631,0.0003713642,0.00005833989,0.0001384786,0.0001873422,0.982915,0.000408256,0.00003835532,0.001917247,0.0007061188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05737487,0.0000826238,0.9366642,0.0006307994,0.002217241,0.001104324,0.000163701,0.000230824,0.001531376],"genre_scores_gemma":[0.9936184,0.00002282156,0.004313947,0.00005718076,0.00004353414,0.0001842912,0.000006295485,0.00004263113,0.001710929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9362435,"threshold_uncertainty_score":0.9998675,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979380794","doi":"10.1109/tcyb.2014.2352291","title":"Network-Based Robust <inline-formula> <tex-math notation=\"LaTeX\">$\\mathscr {H}_{2}/\\mathscr {H}_\\infty $ </tex-math></inline-formula> Control for Linear Systems With Two-Channel Random Packet Dropouts and Time Delays","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Natural Science Foundation of Anhui Province; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Network packet; Control theory (sociology); Lyapunov function; Mathematics; Controller (irrigation); Markov chain; Discrete time and continuous time; Computer science; Control (management); Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.0102904839158886,"gpt":0.2034080382404193,"spread":0.1931175543245306,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001892384,0.00156319,0.002241056,0.000450089,0.0008047419,0.0004633774,0.0006740071,0.0008625883,0.00003459236],"category_scores_gemma":[0.0001052844,0.001405878,0.0006760166,0.000722372,0.0003366874,0.0005515115,0.00001010488,0.0008580966,0.0001911934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004454229,"about_ca_system_score_gemma":0.0002329401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001024359,"about_ca_topic_score_gemma":0.0007376696,"domain_scores_codex":[0.9930874,0.0003680526,0.002237082,0.001289275,0.001240844,0.001777352],"domain_scores_gemma":[0.9938978,0.002365762,0.0005862137,0.001463668,0.000937288,0.0007492944],"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":[0.00178376,0.0003769892,0.00002337335,0.000705539,0.0007295316,0.00001708302,0.0006568161,0.98756,0.002527742,0.002896618,0.0004607478,0.002261831],"study_design_scores_gemma":[0.02132129,0.001146238,0.00005597376,0.000710811,0.0009900938,0.00009359522,0.00007352468,0.9645811,0.0005086996,0.000275608,0.008718812,0.001524301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09760748,0.001217611,0.8916827,0.000351496,0.001978129,0.004283844,0.001065855,0.001173693,0.0006391226],"genre_scores_gemma":[0.9905309,0.0001621087,0.005369077,0.000298139,0.001130076,0.001108278,0.0002244918,0.0004348306,0.0007420731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8929235,"threshold_uncertainty_score":0.9997116,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2062644434","doi":"10.1109/tcyb.2014.2314294","title":"A Learning-Based Semi-Autonomous Controller for Robotic Exploration of Unknown Disaster Scenes While Searching for Victims","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Urban search and rescue; Teleoperation; Search and rescue; Robot; Rescue robot; Computer science; Robustness (evolution); Rubble; Artificial intelligence; Controller (irrigation); Reinforcement learning; Robotics; Disaster area; Mobile robot; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03400015539494928,"gpt":0.2683356846515418,"spread":0.2343355292565926,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004675319,0.0002182223,0.0003412036,0.0001964479,0.0002561905,0.0001125656,0.0004033612,0.0001137932,0.000003400918],"category_scores_gemma":[0.00005383049,0.0002142245,0.0001869332,0.0002204349,0.00006711546,0.0003028683,0.000002847964,0.0002139776,0.00001116879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006297356,"about_ca_system_score_gemma":0.00009144041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001516277,"about_ca_topic_score_gemma":0.00001081451,"domain_scores_codex":[0.998372,0.0001434268,0.000402524,0.0004260006,0.000281567,0.0003744683],"domain_scores_gemma":[0.9979061,0.001193027,0.000178217,0.0003763399,0.0002368628,0.0001094279],"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":[0.0000528114,0.0001529849,0.000006924289,0.00005511154,0.00003270755,2.740245e-7,0.001094985,0.965389,0.0008802849,0.0003799789,0.00003838135,0.03191662],"study_design_scores_gemma":[0.001789808,0.001055481,0.00002811696,0.0000888315,0.00005080364,0.000002175974,0.0000457432,0.9850081,0.01038201,0.0005528245,0.00077526,0.0002208239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001080064,0.00001328051,0.9967033,0.0004963844,0.0006541718,0.0007922916,0.00001058222,0.0001686107,0.00008136093],"genre_scores_gemma":[0.8237193,0.000003032082,0.1753448,0.0001018159,0.00006861929,0.000230018,0.000007072921,0.00003287213,0.0004924324],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8226393,"threshold_uncertainty_score":0.8735822,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012175404","doi":"10.1109/tcyb.2020.2978216","title":"A Subvision System for Enhancing the Environmental Adaptability of the Powered Transfemoral Prosthesis","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":100,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Shenzhen and Hong Kong Joint Innovation Project; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Stairs; Adaptability; Prosthesis; Computer science; Obstacle; Simulation; Robot; Computer vision; Artificial intelligence; Engineering; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.01074500019008423,"gpt":0.1848479483267442,"spread":0.17410294813666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001304039,0.0001418052,0.0001636368,0.00001777626,0.0001343226,0.00001486654,0.0002001832,0.0000786564,0.00001274589],"category_scores_gemma":[0.000006271912,0.00009087076,0.0002155096,0.0001228381,0.0001167037,0.00002807343,0.000001169904,0.0001728864,0.000005250016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006955337,"about_ca_system_score_gemma":0.00001764068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004165903,"about_ca_topic_score_gemma":0.00002526353,"domain_scores_codex":[0.9990982,0.00004753795,0.0003387782,0.0001515315,0.0002067463,0.0001572405],"domain_scores_gemma":[0.9994221,0.0001902276,0.0000362364,0.0002727667,0.00002124849,0.00005746401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001136356,0.0001861812,0.0000851955,0.0005986339,0.0001009511,3.758639e-7,0.006622791,0.8320168,0.1472737,0.0002954335,0.00004286692,0.01266351],"study_design_scores_gemma":[0.000792772,0.0003974534,0.001565572,0.00009503476,0.0001624542,0.000004067468,0.001685996,0.2954528,0.698553,0.00006635071,0.0009682208,0.0002562145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3792249,0.0001075602,0.617596,0.001003412,0.0005316805,0.001142079,0.0002141052,0.0001051252,0.00007508883],"genre_scores_gemma":[0.9988371,0.00002456523,0.0009777083,0.00003799227,0.00001892937,0.00005211517,0.000001098187,0.00003243084,0.00001806326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6196122,"threshold_uncertainty_score":0.3705602,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999954621","doi":"10.1109/tcyb.2014.2328659","title":"Semi-Flocking Algorithm for Motion Control of Mobile Sensors in Large-Scale Surveillance Systems","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Flocking (texture); Computer science; Algorithm; Wireless sensor network; Distributed computing; Real-time computing; Artificial intelligence; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.006583218962908225,"gpt":0.2159047349912012,"spread":0.209321516028293,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006089512,0.0001962426,0.0003690356,0.000196785,0.0000958457,0.00005226053,0.0003771799,0.0001639571,0.000002519511],"category_scores_gemma":[0.000007066617,0.0002078262,0.000122612,0.0004325073,0.00004617461,0.0000986431,0.000002501593,0.0002077868,0.000005530927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007880379,"about_ca_system_score_gemma":0.00001991466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000598726,"about_ca_topic_score_gemma":0.000126956,"domain_scores_codex":[0.9981391,0.0002086069,0.0004914934,0.0004281857,0.0003158099,0.0004167762],"domain_scores_gemma":[0.9984573,0.0005779875,0.0001751069,0.0005385375,0.000171089,0.00008002081],"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":[0.000007606191,0.0002006506,0.00008058065,0.00002300761,0.00001346637,8.456788e-7,0.0002823111,0.9636296,0.0003264691,0.0002922921,0.00001073468,0.03513245],"study_design_scores_gemma":[0.001235476,0.0001850529,0.0001387294,0.00006867437,0.000009103375,0.000005792187,0.00005598391,0.9922154,0.005268542,0.00002061768,0.0005990737,0.0001975337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03901726,0.0000752595,0.9588705,0.00003150323,0.001267889,0.0004723516,0.00004759345,0.0001171415,0.0001004999],"genre_scores_gemma":[0.9798363,0.00003471294,0.01972333,0.00003280972,0.00007247211,0.0001019983,0.000002973573,0.00002713773,0.0001682337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9408191,"threshold_uncertainty_score":0.8474905,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2772102164","doi":"10.1109/tcyb.2017.2748418","title":"Adaptive Neural Network Control for Robotic Manipulators With Unknown Deadzone","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Science Foundation of Beijing Municipality; National Natural Science Foundation of China","keywords":"Dead zone; Control theory (sociology); Robot manipulator; Computer science; Artificial neural network; Observer (physics); Adaptive control; Scheme (mathematics); Control engineering; Control (management); Artificial intelligence; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.024282525157901,"gpt":0.2323845908515563,"spread":0.2081020656936553,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001047514,0.0003220483,0.0004060289,0.00006063863,0.0003976893,0.0001104047,0.0003110206,0.0001402975,0.00001366006],"category_scores_gemma":[0.00000576277,0.0002944275,0.0001471032,0.00005909438,0.0001148391,0.0001599939,9.489372e-7,0.0002944674,0.00003635504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001038982,"about_ca_system_score_gemma":0.00002412389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003368289,"about_ca_topic_score_gemma":0.0005759181,"domain_scores_codex":[0.9987237,0.00002938527,0.0002867816,0.0002699089,0.0002123515,0.0004778949],"domain_scores_gemma":[0.998836,0.0001919912,0.0001055506,0.0005914934,0.0001227207,0.0001521876],"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":[0.000188939,0.00003830819,0.00005467917,0.00001959676,0.0002670086,0.00001016917,0.0000437919,0.9943358,0.0001097565,0.0002688092,0.0001850715,0.004478041],"study_design_scores_gemma":[0.002605032,0.000520588,0.001302483,0.00008503725,0.0002515153,0.00001838416,0.00002221272,0.9931129,0.0004590805,0.00006614382,0.001168622,0.0003879626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009123774,0.0001408037,0.9872881,0.0001101457,0.001568041,0.0008573961,0.00003698507,0.0002565392,0.0006182455],"genre_scores_gemma":[0.9934112,0.00001330982,0.005017916,0.000049285,0.0004430331,0.000139261,0.000002065387,0.0001201942,0.000803713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9842874,"threshold_uncertainty_score":0.9999508,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3011001830","doi":"10.1109/tcyb.2020.2974924","title":"A Dynamic Adaptive Subgroup-to-Subgroup Compatibility-Based Conflict Detection and Resolution Model for Multicriteria Large-Scale Group Decision Making","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":93,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Conflict resolution; Cluster analysis; Conflict analysis; Computer science; Group decision-making; Compatibility (geochemistry); Group conflict; Data mining; Artificial intelligence; Psychology; Social psychology; Political science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1135105891774499,"gpt":0.374537989599287,"spread":0.2610274004218371,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002077531,0.0005243107,0.0007329345,0.0006683685,0.0007225439,0.0005323678,0.000690115,0.0003307132,0.00009753047],"category_scores_gemma":[0.00070465,0.0005010364,0.0003468332,0.001142517,0.0001634927,0.0003965514,0.00002519477,0.0004864277,0.0001040924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002635116,"about_ca_system_score_gemma":0.00006705525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002511473,"about_ca_topic_score_gemma":0.00165244,"domain_scores_codex":[0.9941335,0.0003855627,0.001488121,0.001693235,0.00160684,0.0006926933],"domain_scores_gemma":[0.9944874,0.003042236,0.0003442104,0.0009552194,0.0006671827,0.0005037695],"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":[0.005551834,0.0005241758,0.00005981059,0.00003920343,0.00003824339,0.000006996794,0.005739759,0.7362921,0.03289688,0.00007666244,0.0001889274,0.2185854],"study_design_scores_gemma":[0.002642456,0.0008226346,0.001319721,0.000131765,0.00007647218,0.000006867144,0.0006656791,0.9895368,0.001639124,0.001612199,0.00102974,0.0005165305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2589022,0.00003963796,0.7380871,0.0003317491,0.0006205448,0.001322151,0.0005233477,0.000154038,0.00001917071],"genre_scores_gemma":[0.7607306,0.000007751974,0.2378256,0.001151901,0.00004125358,0.0001334339,0.000006059359,0.00006730487,0.00003611658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5018284,"threshold_uncertainty_score":0.9997441,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393033973","doi":"10.1109/tcyb.2024.3372591","title":"Industrial Metaverse for Smart Manufacturing: Model, Architecture, and Applications","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"National Natural Science Foundation of China","keywords":"Metaverse; Computer science; Architecture; Upgrade; Virtual reality; Systems engineering; Human–computer interaction; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04586038090234743,"gpt":0.274907784118839,"spread":0.2290474032164916,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001367717,0.0001560949,0.0001273241,0.0001778674,0.0001900246,0.0002768005,0.0002920831,0.0001114217,0.00000700288],"category_scores_gemma":[0.000003095626,0.0001449276,0.00009180067,0.0002277195,0.00006198356,0.0001690284,0.000004073648,0.000255515,0.0000318883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004549162,"about_ca_system_score_gemma":0.00009323428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002131454,"about_ca_topic_score_gemma":0.00002202152,"domain_scores_codex":[0.998994,0.00001821688,0.000196552,0.0004011543,0.0001672072,0.000222871],"domain_scores_gemma":[0.9991351,0.0002111643,0.00002644732,0.0004415301,0.00002893667,0.0001567846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001476443,0.0001370483,1.754464e-7,0.00004200522,0.00008219896,9.813707e-7,0.0003929398,0.1045829,0.0004589543,0.06479367,0.0008991967,0.8285952],"study_design_scores_gemma":[0.0005157083,0.000222697,0.000007252194,0.00003522597,0.0001141185,0.000028003,0.0000213725,0.670749,0.04620902,0.04929142,0.2324439,0.0003622928],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001076087,0.00006187624,0.9959654,0.001006184,0.0001910423,0.000658312,0.0001152992,0.000232702,0.0006931296],"genre_scores_gemma":[0.960511,0.0001156706,0.03710595,0.0002537763,0.00009869021,0.0005197789,0.000005833906,0.00002532555,0.001363984],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9594349,"threshold_uncertainty_score":0.5909974,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2336159922","doi":"10.1109/tcyb.2015.2428056","title":"Synchronous Hybrid Event- and Time-Driven Consensus in Multiagent Networks With Time Delays","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Program for New Century Excellent Talents in University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Robustness (evolution); Network topology; Control theory (sociology); Consensus; Time shifting; LTI system theory; Discrete time and continuous time; Multi-agent system; Distributed computing; Control (management); Mathematics; Artificial intelligence; Computer network; Linear system","retraction":null,"screen_n_in":null,"score":{"opus":0.01187333208788884,"gpt":0.2155225235764033,"spread":0.2036491914885144,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000258547,0.0002851145,0.0003312727,0.000153329,0.00008722047,0.0001405686,0.0004099574,0.0001021574,0.00001476273],"category_scores_gemma":[0.000007458299,0.0002684707,0.00005837637,0.0003053122,0.0001036141,0.0001284942,0.00000710665,0.0003007683,0.0002624935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002145383,"about_ca_system_score_gemma":0.0001383916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001645946,"about_ca_topic_score_gemma":0.0001235466,"domain_scores_codex":[0.9980801,0.0001813143,0.0003909023,0.0005242198,0.0003706002,0.0004528398],"domain_scores_gemma":[0.998665,0.0001840808,0.0001195816,0.0005798785,0.0001306723,0.0003208263],"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":[0.00008320079,0.0003483927,0.0001170374,0.000008173098,0.00009251472,0.0002103124,0.0003855338,0.9830484,0.0002633167,0.0000546223,0.0007714285,0.014617],"study_design_scores_gemma":[0.002415234,0.0003889583,0.0002263808,0.00007384992,0.00003989126,0.0001833819,0.00002496744,0.9952716,0.0006266739,0.0000181889,0.0004078763,0.0003230024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05858602,0.0001383986,0.9395199,0.0002435622,0.0003517159,0.0005765731,0.00004191286,0.0001841091,0.0003578495],"genre_scores_gemma":[0.9924035,0.0000137371,0.006821289,0.00009308015,0.00003528318,0.00005144985,0.000005941193,0.00002862684,0.0005470981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9338174,"threshold_uncertainty_score":0.9999768,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2885245712","doi":"10.1109/tcyb.2018.2859801","title":"Functional Nonlinear Model Predictive Control Based on Adaptive Dynamic Programming","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Model predictive control; Control theory (sociology); Optimal control; Robustness (evolution); Nonlinear system; Dynamic programming; Computer science; Mathematical optimization; Artificial neural network; Lyapunov function; Mathematics; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01443954020173,"gpt":0.2358165193500147,"spread":0.2213769791482847,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002892789,0.0004189312,0.0003168505,0.00031562,0.0004235445,0.000135215,0.0006915094,0.0002040388,0.00002225251],"category_scores_gemma":[0.00001945514,0.0004137735,0.0002357611,0.0005215288,0.0003801333,0.0002814698,0.000005179082,0.0005984151,0.0002023663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00036445,"about_ca_system_score_gemma":0.0003123199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001599659,"about_ca_topic_score_gemma":0.00006917866,"domain_scores_codex":[0.9971793,0.0001335954,0.0003935723,0.0008660631,0.000785697,0.0006418314],"domain_scores_gemma":[0.9979177,0.0003583516,0.0001633765,0.0008369252,0.000487749,0.0002358812],"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":[0.0005915494,0.0008558883,0.000007007808,0.000005118742,0.0001370143,0.00001096427,0.0002422424,0.8772695,0.000186937,0.001880747,0.00006304107,0.11875],"study_design_scores_gemma":[0.002217538,0.00243869,0.0001358404,0.00004790682,0.00007655918,0.000007437991,0.00002206039,0.9931522,0.0005256954,0.0007431299,0.000250222,0.0003827137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004754764,0.00001060521,0.9959368,0.0005989567,0.0008691679,0.000838486,0.0001123737,0.0005971235,0.0005610235],"genre_scores_gemma":[0.8477375,0.000001979948,0.150741,0.0007573437,0.00009998155,0.0001973588,0.000005032484,0.00004469456,0.0004151362],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.847262,"threshold_uncertainty_score":0.9998314,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3006321946","doi":"10.1109/tcyb.2019.2963141","title":"Integral-Type Event-Triggered Model Predictive Control of Nonlinear Systems With Additive Disturbance","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Victoria","keywords":"Control theory (sociology); Model predictive control; Robustness (evolution); Nonlinear system; Rendering (computer graphics); Contraction (grammar); Computer science; Mathematics; Constraint (computer-aided design); Mathematical optimization; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.008332796021869343,"gpt":0.2000219770158134,"spread":0.191689180993944,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003774063,0.0002475046,0.0003927834,0.00006690709,0.00004301341,0.00001731602,0.0001363747,0.0001133337,0.000008412792],"category_scores_gemma":[0.00001002992,0.0002262278,0.00007110268,0.0003416814,0.00006257359,0.000144144,5.438018e-7,0.0002900364,0.0000125352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001078104,"about_ca_system_score_gemma":0.00004470247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001112998,"about_ca_topic_score_gemma":0.000009370171,"domain_scores_codex":[0.998853,0.0000387719,0.0003883152,0.0002386103,0.0002676093,0.0002136787],"domain_scores_gemma":[0.9991984,0.0000985626,0.0001053994,0.0002156424,0.0002530009,0.0001289447],"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":[0.0003426514,0.00004635919,0.000005021093,0.00006613597,0.0001968791,0.000002542253,0.0004363098,0.9969707,0.001227169,0.00004696813,0.00005828419,0.0006010038],"study_design_scores_gemma":[0.00146217,0.0004325269,0.000006903295,0.0001295022,0.0001240954,0.000002484378,0.0001603085,0.9927419,0.004608393,0.00001171775,0.0001106935,0.0002093509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002089039,0.0002377727,0.9951694,0.00004363682,0.0003146247,0.0007003642,0.0007698748,0.0002742355,0.0004010308],"genre_scores_gemma":[0.9959778,0.0001061547,0.003509711,0.00003594061,0.00006796016,0.00008981854,0.00001476665,0.00007180237,0.0001261137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9938887,"threshold_uncertainty_score":0.9225304,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3135822842","doi":"10.1109/tcyb.2021.3055770","title":"Information Fusion Fault Diagnosis Method for Deep-Sea Human Occupied Vehicle Thruster Based on Deep Belief Network","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"National Natural Science Foundation of China","keywords":"Fault (geology); Deep belief network; Information fusion; Fusion; Artificial neural network; Artificial intelligence; Sensor fusion; Computer science; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.01095363605417745,"gpt":0.2463050191412417,"spread":0.2353513830870643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001952513,0.0002565903,0.0002679243,0.0001359843,0.0003021498,0.000130163,0.0001158916,0.000237685,0.0002170388],"category_scores_gemma":[0.00001133741,0.0002726223,0.0002230013,0.0003403482,0.00001648201,0.0001740161,0.000001112666,0.0003040792,0.00009768866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446512,"about_ca_system_score_gemma":0.00002014652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003829601,"about_ca_topic_score_gemma":0.0004521464,"domain_scores_codex":[0.9986131,0.00009193669,0.0004557359,0.000191159,0.000293756,0.000354321],"domain_scores_gemma":[0.9989824,0.0003231405,0.0000616888,0.000370226,0.0001375142,0.000124976],"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":[0.00005340859,0.00008757731,0.00002110092,0.00006617826,0.00005808572,0.000001612911,0.0002271507,0.928557,0.0009874617,0.00005827407,0.0007075007,0.06917468],"study_design_scores_gemma":[0.001654683,0.000212388,0.0002142761,0.00007050312,0.00008887421,0.000003793622,0.0001198032,0.943191,0.02670426,0.00006441447,0.02737395,0.0003020612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007660989,0.00006809454,0.9867347,0.0001497147,0.0015766,0.0005454518,0.0000598286,0.0003874877,0.002817058],"genre_scores_gemma":[0.9922438,0.00004592278,0.00582451,0.0008696591,0.000180403,0.0005407087,0.00004229997,0.00005551807,0.0001972019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9845828,"threshold_uncertainty_score":0.9999726,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4224027514","doi":"10.1109/tcyb.2022.3163301","title":"Fault Detection for Nonlinear Dynamic Systems With Consideration of Modeling Errors: A Data-Driven Approach","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Beijing Municipality; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Nonlinear system; Fault detection and isolation; Residual; Control theory (sociology); Generator (circuit theory); Process (computing); Realization (probability)","retraction":null,"screen_n_in":null,"score":{"opus":0.02309666793942626,"gpt":0.2359949469070155,"spread":0.2128982789675892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001650984,0.0001709496,0.0002447806,0.0001690049,0.0002250231,0.00003693564,0.000166276,0.000072982,0.000006997566],"category_scores_gemma":[0.000002799858,0.0001763173,0.00006272076,0.0002216814,0.00002201335,0.0001083945,0.000001793952,0.0002686458,0.000002209153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001509036,"about_ca_system_score_gemma":0.00003309198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001161524,"about_ca_topic_score_gemma":0.000249594,"domain_scores_codex":[0.9988303,0.00005987192,0.0003753675,0.0002676233,0.0002857869,0.000181057],"domain_scores_gemma":[0.999317,0.00005682405,0.00006945997,0.0004254179,0.00008174461,0.00004952286],"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":[0.00009032609,0.0000754366,2.952814e-7,0.0001142779,0.000112448,5.406952e-7,0.0002148268,0.9933604,0.00384368,0.000007158257,0.00001355729,0.00216708],"study_design_scores_gemma":[0.0009443716,0.0002828305,4.295562e-7,0.00002051356,0.00009887982,0.00005245558,0.00117862,0.9954769,0.001184251,0.000004553144,0.0005686879,0.0001875102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0551449,0.0000864843,0.9422304,0.00001060955,0.0008135223,0.0008088203,0.0005487033,0.0002418928,0.0001146925],"genre_scores_gemma":[0.9962286,0.00001410453,0.003012164,0.000008279789,0.00003765636,0.0004585366,0.00006266087,0.00005942715,0.0001185709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9410837,"threshold_uncertainty_score":0.7190012,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390075398","doi":"10.1109/tcyb.2023.3337792","title":"Adaptive Fixed-Time Control for High-Order Stochastic Nonlinear Time-Delay Systems: An Improved Lyapunov–Krasovskii Function","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Nonlinear system; Control theory (sociology); Order (exchange); Function (biology); Control (management); Mathematics; Computer science; Physics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01133414777429423,"gpt":0.2146372245278035,"spread":0.2033030767535093,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003675144,0.0005530042,0.0006843811,0.000389699,0.0002308122,0.0001040811,0.0002749424,0.0003776411,0.00008069731],"category_scores_gemma":[0.00002516561,0.0005777441,0.0002122584,0.0005799296,0.00008023818,0.0002712668,0.000001999696,0.0004326333,0.001458374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002460374,"about_ca_system_score_gemma":0.00008065539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000770874,"about_ca_topic_score_gemma":0.00005295079,"domain_scores_codex":[0.9975241,0.0001200936,0.000700325,0.0005601224,0.0003866864,0.0007086967],"domain_scores_gemma":[0.9979312,0.0006487684,0.0001306186,0.0005854332,0.0004423533,0.0002615968],"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":[0.0003245139,0.0001342977,3.786943e-7,0.00005304079,0.0005107276,0.000005123312,0.0001223597,0.9772823,0.01740044,0.00004251632,0.0006024729,0.00352178],"study_design_scores_gemma":[0.003052968,0.0011934,0.00003319448,0.00008155788,0.0004000013,0.00001080762,0.0001418946,0.9929851,0.0005154527,0.00003126478,0.0009715937,0.0005827965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008094604,0.0001175135,0.9838015,0.00005539109,0.002629062,0.002047044,0.001342157,0.001789902,0.0001228233],"genre_scores_gemma":[0.9918874,0.00001258491,0.00276558,0.00005164542,0.000776963,0.0006497602,0.0001177281,0.0002962519,0.003442083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9837928,"threshold_uncertainty_score":0.9996674,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3132678854","doi":"10.1109/tcyb.2020.3045786","title":"Adaptive Finite-Time Fault-Tolerant Control for Uncertain Flexible Flapping Wings Based on Rigid Finite Element Method","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"University of Science and Technology Beijing; Natural Science Foundation of Beijing Municipality; China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Control theory (sociology); Flapping; Controller (irrigation); Finite element method; Actuator; Vibration; Wing; Engineering; Lyapunov stability; Fault tolerance; Control engineering; Computer science; Structural engineering; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02091173346732525,"gpt":0.2511888611620167,"spread":0.2302771276946915,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003348076,0.0003777313,0.0004237004,0.0002066155,0.0002088379,0.00007181602,0.0001730557,0.0002348082,0.0006735331],"category_scores_gemma":[0.00001955421,0.0003801821,0.0002840084,0.000359965,0.00002926313,0.00005610042,0.000001264627,0.0003765764,0.0001587787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001441882,"about_ca_system_score_gemma":0.0000783997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001614065,"about_ca_topic_score_gemma":0.00001387788,"domain_scores_codex":[0.998138,0.000122179,0.0004636672,0.000431173,0.0003550329,0.0004899243],"domain_scores_gemma":[0.9979883,0.001217074,0.00006038419,0.000408898,0.0001597163,0.0001655876],"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":[0.0002016158,0.000144486,1.741151e-7,0.00005811161,0.0001403751,0.0000119481,0.0001832813,0.951619,0.02127946,0.000211449,0.0004125921,0.02573746],"study_design_scores_gemma":[0.001730941,0.0003491654,9.564102e-7,0.0001054983,0.0001267444,0.0000019098,0.00004677845,0.6646758,0.3241032,0.0005007777,0.008053941,0.0003042907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002697395,0.00007251382,0.9957072,0.0004799401,0.0008953516,0.0006260441,0.0003907144,0.000325725,0.001232842],"genre_scores_gemma":[0.7879465,0.00004919295,0.2070775,0.001220601,0.0001315047,0.0003499903,0.0000506245,0.0001407142,0.003033432],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7886297,"threshold_uncertainty_score":0.999865,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2748811888","doi":"10.1109/tcyb.2017.2715560","title":"Balance Preferences with Performance in Group Role Assignment","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Nipissing University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Science and Technology Planning Project of Guangdong Province; Zhejiang University; Nipissing University","keywords":"Balance (ability); Task (project management); Association rule learning; Process (computing); Association (psychology); Computer science; Group decision-making; Group (periodic table); Decision maker; Operations research; Artificial intelligence; Data mining; Machine learning; Psychology; Mathematics; Social psychology; Economics; Management","retraction":null,"screen_n_in":null,"score":{"opus":0.0102152573455956,"gpt":0.2150476537282152,"spread":0.2048323963826196,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001003633,0.0001785881,0.0001506098,0.00009856097,0.0003356198,0.0002356704,0.001225726,0.00006382075,0.00001480632],"category_scores_gemma":[4.566881e-7,0.0001410785,0.00003270125,0.0001492764,0.00006194144,0.0004450559,0.000007992249,0.0002678359,0.00003902044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003388099,"about_ca_system_score_gemma":0.00003627636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002481142,"about_ca_topic_score_gemma":0.002260629,"domain_scores_codex":[0.9987863,0.00003292941,0.000170381,0.0003837007,0.0003308991,0.0002958044],"domain_scores_gemma":[0.9988133,0.0000463627,0.0001069907,0.0009146454,0.0000348139,0.00008388662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003381899,0.001899203,0.04402961,0.0002076703,0.0001725064,0.00006692127,0.01336754,0.1431339,0.002866751,0.006448251,0.00002784402,0.7874416],"study_design_scores_gemma":[0.004751747,0.003424364,0.4367408,0.001036478,0.00007910041,0.00007360086,0.0005754568,0.4176194,0.1186248,0.003753793,0.01141989,0.001900525],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4696517,0.00004401492,0.5210273,0.0004924911,0.0004247675,0.0002150759,0.000005070306,0.0001000915,0.008039564],"genre_scores_gemma":[0.9923553,0.00009481789,0.007076854,0.0002333112,0.0000281285,0.00004507699,6.72295e-7,0.0000103635,0.0001554855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7855411,"threshold_uncertainty_score":0.5753013,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2064297441","doi":"10.1109/tcyb.2013.2252339","title":"A Robust Vision-Based Sensor Fusion Approach for Real-Time Pose Estimation","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer vision; Artificial intelligence; Robustness (evolution); Computer science; Pose; Sensor fusion; Kalman filter; Monocular; Visual servoing; Fusion; 3D pose estimation; Robot","retraction":null,"screen_n_in":null,"score":{"opus":0.0140655496782952,"gpt":0.2123321274404958,"spread":0.1982665777622006,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008334372,0.0002305462,0.0001938947,0.0001754586,0.0001471658,0.00009171158,0.00009546651,0.0001865774,0.0001658336],"category_scores_gemma":[0.000006563319,0.0002340163,0.0001158056,0.0002259693,0.00003550073,0.0001074118,4.645199e-7,0.000143007,0.0001471106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001033131,"about_ca_system_score_gemma":0.00002223429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000568189,"about_ca_topic_score_gemma":0.00000489803,"domain_scores_codex":[0.9989112,0.00003073781,0.0003151224,0.0002469241,0.000222407,0.0002736353],"domain_scores_gemma":[0.9992358,0.0001537808,0.00004075199,0.0003041789,0.0001425804,0.0001228722],"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":[0.00001671738,0.0001454781,0.000001167506,0.00007045668,0.00001864856,4.199792e-7,0.00005690982,0.9746635,0.01431725,0.00002504731,0.001062633,0.009621748],"study_design_scores_gemma":[0.0006161391,0.0001547847,0.00005059897,0.00003288816,0.00005336183,0.000002039753,0.00001968835,0.9802183,0.01844704,0.00005758838,0.00008890085,0.0002587009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01869954,0.00000765811,0.9785597,0.00008892071,0.0003090183,0.0008299793,0.00004266129,0.0004155697,0.001046985],"genre_scores_gemma":[0.7717202,0.000039271,0.2271839,0.00006342047,0.0000603411,0.0001415858,0.0001096136,0.00009822958,0.0005833461],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7530207,"threshold_uncertainty_score":0.9542909,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3005908894","doi":"10.1109/tcyb.2020.2964430","title":"Adaptive Event-Triggered Control for Unknown Second-Order Nonlinear Multiagent Systems","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"China Scholarship Council; China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Control theory (sociology); Nonlinear system; Controller (irrigation); Multi-agent system; Bounded function; Computer science; Consensus; Adaptive control; Event (particle physics); Control (management); Zeno's paradoxes; Tracking (education); Control engineering; Mathematics; Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02790231579190492,"gpt":0.246342983239788,"spread":0.2184406674478831,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002553072,0.0004230921,0.0005684384,0.0001187568,0.0002376454,0.0002622204,0.0009424968,0.0002163206,0.00004200378],"category_scores_gemma":[0.00003194382,0.0004207617,0.0003247082,0.0005282529,0.00005794682,0.0002813113,0.0000049824,0.0003524907,0.0002584595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001603776,"about_ca_system_score_gemma":0.0001881716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005362682,"about_ca_topic_score_gemma":0.00005374521,"domain_scores_codex":[0.9970939,0.0002038435,0.0007555826,0.0008139094,0.000527607,0.0006051978],"domain_scores_gemma":[0.9976976,0.00044988,0.0002633042,0.0006833632,0.0004714494,0.0004343978],"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":[0.000665642,0.001408634,0.00001294546,0.0002935837,0.001346866,0.00006344512,0.002466643,0.9406028,0.007831496,0.006299307,0.004328678,0.03467989],"study_design_scores_gemma":[0.004908002,0.000608733,0.00001506685,0.00005009674,0.000103353,0.000007416303,0.0001141127,0.9724382,0.004194664,0.00002263608,0.01709534,0.0004424438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007956915,0.0002139542,0.9918286,0.001137454,0.00225572,0.002246365,0.0009442655,0.0004068573,0.0001710972],"genre_scores_gemma":[0.9853826,0.00001291497,0.01206146,0.0008508146,0.0002265449,0.0004670545,0.00001380933,0.00005376078,0.0009310245],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.984587,"threshold_uncertainty_score":0.9998244,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3197686036","doi":"10.1109/tcyb.2021.3106485","title":"Multiview PCA: A Methodology of Feature Extraction and Dimension Reduction for High-Order Data","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":71,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Dimensionality reduction; Computer science; Principal component analysis; Artificial intelligence; Dimension (graph theory); Projection (relational algebra); Tensor (intrinsic definition); Feature (linguistics); Pattern recognition (psychology); Mathematics; Algorithm; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.1529325046986833,"gpt":0.3962758409918483,"spread":0.243343336293165,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000242655,0.0001403377,0.0002650383,0.00007741821,0.0001396282,0.00001717381,0.0001017582,0.0001652879,0.00005777981],"category_scores_gemma":[0.00006143824,0.0001415606,0.00005665774,0.0002312298,0.00007162851,0.0000995263,0.000003983103,0.000205621,0.000004168248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002487221,"about_ca_system_score_gemma":0.00004030639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000017991,"about_ca_topic_score_gemma":0.00006838643,"domain_scores_codex":[0.9989264,0.0001431192,0.0002871853,0.0003779194,0.0001313028,0.0001340999],"domain_scores_gemma":[0.998126,0.0007640264,0.0001462806,0.0006264523,0.0002807716,0.00005652843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002327892,0.00236445,0.000004129701,0.0005408794,0.0003932884,0.000005122342,0.0009668765,0.001176266,0.7818839,0.04802538,0.007567612,0.1568393],"study_design_scores_gemma":[0.00232873,0.0002668195,0.0003315722,0.0001927071,0.001035077,0.0003631868,0.0007489287,0.008322064,0.9175751,0.05642943,0.01191744,0.0004889808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04511934,0.0001684087,0.9514614,0.001951778,0.0004189196,0.0004316529,0.0003138531,0.0000686811,0.00006598372],"genre_scores_gemma":[0.451054,0.0004354063,0.546994,0.0000582413,0.00005226115,0.00006206328,0.00008185589,0.00002986827,0.001232302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4059347,"threshold_uncertainty_score":0.5772675,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2530431744","doi":"10.1109/tcyb.2016.2612226","title":"Granular Data Description: Designing Ellipsoidal Information Granules","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Recruitment Program of Global Experts; Science and Technology Development Fund; National Natural Science Foundation of China","keywords":"Granular computing; Granularity; Cluster analysis; Rough set; Computer science; Data mining; Ellipsoid; Set (abstract data type); Fuzzy logic; Information processing; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.04496259630264402,"gpt":0.2393635532230098,"spread":0.1944009569203657,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649404,0.0001804392,0.000140527,0.0001547256,0.0002419912,0.0002504689,0.001197727,0.0001023981,0.00003711994],"category_scores_gemma":[0.000008506708,0.0001291037,0.00006240897,0.0002875654,0.00007710603,0.002210263,0.00001074483,0.0001462234,0.0004826917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005183365,"about_ca_system_score_gemma":0.00005223848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002855231,"about_ca_topic_score_gemma":0.00002474775,"domain_scores_codex":[0.9986057,0.0000688162,0.0003272301,0.0003262904,0.000371227,0.0003007625],"domain_scores_gemma":[0.9984141,0.0001153651,0.00008624341,0.001187185,0.000081162,0.0001159673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002960078,0.0001700232,0.00004302711,0.00001824565,0.00002897799,0.00001077729,0.0005940394,0.005874294,0.001355514,0.006954193,0.002831149,0.9820902],"study_design_scores_gemma":[0.008525456,0.002174058,0.002978307,0.0006678515,0.00032232,0.000407524,0.0003438834,0.5832082,0.07640988,0.05479696,0.2662006,0.003964997],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001240912,0.00003807786,0.9953874,0.0009329736,0.0009063705,0.0001650061,0.00005411846,0.0002533049,0.001021795],"genre_scores_gemma":[0.8891419,0.0002400774,0.1100067,0.0003619829,0.00005811688,0.00001516933,0.000007247324,0.00001085075,0.0001579364],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9781252,"threshold_uncertainty_score":0.6204186,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2884043659","doi":"10.1109/tcyb.2018.2850368","title":"Robust Consensus Nonlinear Information Filter for Distributed Sensor Networks With Measurement Outliers","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Outlier; Filter (signal processing); Computer science; Nonlinear system; Consensus; Gaussian; Estimator; Divergence (linguistics); Convergence (economics); Nonlinear filter; Information filtering system; Algorithm; Mathematical optimization; Mathematics; Artificial intelligence; Machine learning; Statistics; Filter design; Multi-agent system","retraction":null,"screen_n_in":null,"score":{"opus":0.03414656309257745,"gpt":0.2254839410680587,"spread":0.1913373779754813,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002991382,0.0002486675,0.0001989351,0.0001137586,0.0004001469,0.0002375425,0.0003931781,0.0001544036,0.00002643108],"category_scores_gemma":[0.00001577132,0.0002128816,0.00008941555,0.0003777007,0.0001651417,0.0002320528,0.000004073423,0.000269846,0.00007494666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009439827,"about_ca_system_score_gemma":0.0000737529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002119283,"about_ca_topic_score_gemma":0.00007100317,"domain_scores_codex":[0.9982713,0.00005556241,0.0003934613,0.0003398512,0.0004995347,0.0004402893],"domain_scores_gemma":[0.9981397,0.0001677421,0.0001439868,0.0006606009,0.0007213865,0.0001665924],"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":[0.0002587207,0.0001762689,0.00001464366,0.00001747992,0.0000972879,0.000003937771,0.0003867091,0.9454039,0.00003882501,0.0001874853,0.01324487,0.04016983],"study_design_scores_gemma":[0.001343912,0.0006678775,0.00006975378,0.00006591684,0.0000585505,0.00003153351,0.00007000236,0.9523543,0.002950332,0.00002348171,0.04199125,0.000373084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001188634,0.00001055469,0.9955142,0.0005443385,0.00143387,0.0004586322,0.0003626682,0.0003020517,0.0001850406],"genre_scores_gemma":[0.6774311,0.00002442815,0.3212245,0.0007608752,0.0002639108,0.00006399364,0.00009509342,0.00002552359,0.0001105579],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6762425,"threshold_uncertainty_score":0.8681061,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3199842479","doi":"10.1109/tcyb.2021.3109618","title":"Toward Robust Fault Identification of Complex Industrial Processes Using Stacked Sparse-Denoising Autoencoder With Softmax Classifier","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"National Science Fund for Distinguished Young Scholars; National Natural Science Foundation of China; Education Department of Hunan Province","keywords":"Softmax function; Pattern recognition (psychology); Artificial intelligence; Autoencoder; Computer science; Noise reduction; Classifier (UML); Robustness (evolution); Sparse approximation; Machine learning; Feature learning; Fault detection and isolation; Deep learning","retraction":null,"screen_n_in":null,"score":{"opus":0.08324951348829113,"gpt":0.251822423041248,"spread":0.1685729095529569,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009669054,0.0002119988,0.0002927207,0.0001393477,0.0001116107,0.0001010175,0.0001079447,0.0001823099,0.00008760055],"category_scores_gemma":[0.00001311909,0.0002151895,0.00007321207,0.0006079783,0.00006832363,0.0001465417,9.032702e-7,0.0003046919,0.00001439299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001375126,"about_ca_system_score_gemma":0.0001587439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005523485,"about_ca_topic_score_gemma":0.0002236762,"domain_scores_codex":[0.9985689,0.00005683823,0.0005227801,0.0002544326,0.0003620007,0.0002350402],"domain_scores_gemma":[0.9991685,0.00006778438,0.0001124623,0.0002740803,0.0002942679,0.00008296862],"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":[0.00004335205,0.00008736918,0.00001566603,0.0001427624,0.0001253864,0.000007197926,0.0004560144,0.9261901,0.06937613,0.000009105465,0.00006478513,0.003482174],"study_design_scores_gemma":[0.001355236,0.00007939807,0.00008462343,0.0001802471,0.0001749366,0.00006866598,0.001027858,0.7408086,0.2544566,0.00001473295,0.001415266,0.0003338045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1658615,0.00006919278,0.8323447,0.00004685835,0.0007980633,0.0002366234,0.00005722438,0.0002395526,0.000346332],"genre_scores_gemma":[0.9979068,0.00003387546,0.001443757,0.00001686375,0.00009058054,0.0000214333,0.000007160809,0.00005873778,0.0004208123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8320453,"threshold_uncertainty_score":0.8775172,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2887269903","doi":"10.1109/tcyb.2018.2859342","title":"Multiple Relevant Feature Ensemble Selection Based on Multilayer Co-Evolutionary Consensus MapReduce","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Australian Research Council; Six Talent Peaks Project in Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Feature selection; Computer science; Selection (genetic algorithm); Feature (linguistics); Artificial intelligence; Pattern recognition (psychology); Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.0200130637100457,"gpt":0.2518735351632771,"spread":0.2318604714532314,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001553755,0.0002975851,0.000208186,0.0002234676,0.0005211818,0.0001057661,0.0004228904,0.0002468166,0.00006040982],"category_scores_gemma":[0.00001848594,0.0002745635,0.0001442436,0.000511101,0.0001700252,0.00009970889,0.000002976491,0.0004806152,0.0004830308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001791292,"about_ca_system_score_gemma":0.0001479883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006464037,"about_ca_topic_score_gemma":0.0000929628,"domain_scores_codex":[0.9980163,0.0001396034,0.0002591863,0.0006517101,0.0004730825,0.0004601055],"domain_scores_gemma":[0.9985019,0.0003554661,0.00009712662,0.0006575371,0.000214837,0.0001731534],"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":[0.001600915,0.005689687,0.0005954908,0.0001021554,0.0002824063,0.0001602794,0.002544879,0.531037,0.0541627,0.002901928,0.1481741,0.2527484],"study_design_scores_gemma":[0.001092047,0.001076442,0.001415527,0.00004511723,0.00002466846,0.00005394898,0.00002100317,0.9210044,0.05870532,0.0002749058,0.01588943,0.0003972269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01613226,0.00002765621,0.9734215,0.002215643,0.001772772,0.0004251401,0.00005673003,0.0004605205,0.005487785],"genre_scores_gemma":[0.9007719,0.00001614597,0.09679332,0.0009311817,0.0001661116,0.00003074746,0.0000047069,0.00002804023,0.001257804],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8846397,"threshold_uncertainty_score":0.9999707,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2342468814","doi":"10.1109/tcyb.2015.2490165","title":"Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Handwriting recognition; Pattern recognition (psychology); Recurrent neural network; Classifier (UML); Feature (linguistics); Artificial neural network; Handwriting; Benchmark (surveying); Machine learning; Feature extraction","retraction":null,"screen_n_in":null,"score":{"opus":0.07700851734809266,"gpt":0.3149699149892884,"spread":0.2379613976411958,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001459599,0.000214146,0.0001852339,0.000128733,0.000291956,0.0002522579,0.0004880266,0.0001493413,0.000001947293],"category_scores_gemma":[0.00004290412,0.0001840136,0.0001016287,0.0005420978,0.00002559109,0.0002697672,0.000006030029,0.0002857715,0.00005565742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002119321,"about_ca_system_score_gemma":0.0001191023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001782755,"about_ca_topic_score_gemma":0.0000882387,"domain_scores_codex":[0.998058,0.000206346,0.0003307205,0.0004780886,0.0005960216,0.0003308513],"domain_scores_gemma":[0.9979511,0.0001840346,0.0001567048,0.0005509855,0.0009807013,0.0001764796],"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":[0.00003090278,0.00006293994,6.979482e-7,0.00001581826,0.00001484759,1.861276e-7,0.0004007134,0.5551502,0.00008955062,0.0002117822,0.01309153,0.4309309],"study_design_scores_gemma":[0.0004873953,0.0002652674,0.000003535166,0.00008835188,0.00006995549,0.00001539738,0.00007084884,0.9887458,0.003104131,0.003002888,0.003914881,0.0002315187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001492277,0.0001150434,0.9908955,0.003188123,0.001022897,0.002619549,0.0001177669,0.0003679523,0.0001808925],"genre_scores_gemma":[0.8851062,0.00003575401,0.1100807,0.000794511,0.0004306725,0.003129245,0.00009557224,0.00003856664,0.0002887779],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8836139,"threshold_uncertainty_score":0.7503859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2977880070","doi":"10.1109/tcyb.2019.2940987","title":"Synchronization in Kuramoto Oscillator Networks With Sampled-Data Updating Law","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Synchronization (alternating current); Asynchronous communication; Computer science; Linearization; Coupling (piping); Control theory (sociology); Stability (learning theory); Lyapunov stability; Synchronization networks; Lyapunov function; Nonlinear system; Control (management); Physics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01339436598406899,"gpt":0.2285499570289957,"spread":0.2151555910449267,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001777458,0.0001330546,0.0001249653,0.00008975908,0.00007897829,0.0001550669,0.0005697656,0.00007791453,0.00002929141],"category_scores_gemma":[0.000001153679,0.0001230103,0.00002100069,0.0003950379,0.00002344607,0.0005446839,0.000008384299,0.0002278399,0.00007609864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007056338,"about_ca_system_score_gemma":0.00004015044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001982546,"about_ca_topic_score_gemma":0.001511553,"domain_scores_codex":[0.9989358,0.00004188532,0.0002360258,0.0003320145,0.0002322235,0.0002220085],"domain_scores_gemma":[0.998929,0.00007375555,0.00008096735,0.0008105487,0.000052436,0.00005332226],"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":[0.00001454692,0.0001119661,0.001058802,0.00002206525,0.00001783665,0.000003077126,0.0002753575,0.9596527,0.00003713726,0.006570475,0.00001755303,0.03221849],"study_design_scores_gemma":[0.0004021855,0.0001077509,0.0003848067,0.00005889596,0.000006213182,0.000009022609,0.00001648114,0.9980896,0.0001332926,0.0000907814,0.0005363387,0.0001646477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04089473,0.000009461058,0.9573796,0.0001265341,0.0004105294,0.0002539809,0.00002331863,0.00007757734,0.000824314],"genre_scores_gemma":[0.9708346,0.00002192829,0.02871631,0.0002609331,0.00002981181,0.000005549342,0.00003823903,0.00001675222,0.00007592374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9299398,"threshold_uncertainty_score":0.5016212,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2344244807","doi":"10.1109/tcyb.2015.2492468","title":"Extreme Learning Machine With Subnetwork Hidden Nodes for Regression and Classification","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Extreme learning machine; Subnetwork; Bottleneck; Computer science; Artificial intelligence; Generalization; Artificial neural network; Backpropagation; Machine learning; Support vector machine; Residual; Feedforward neural network; Feed forward; Pattern recognition (psychology); Algorithm; Engineering; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.05160575226254047,"gpt":0.2679118930501463,"spread":0.2163061407876058,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002616996,0.000149599,0.0001322727,0.00008856218,0.0002262396,0.0001160589,0.0002065818,0.00007450728,0.000004046077],"category_scores_gemma":[0.00001199849,0.0001160761,0.00003239734,0.0002033118,0.00004675865,0.0001442701,0.000002689356,0.0002329447,0.00001409928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003396493,"about_ca_system_score_gemma":0.00004035792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003916712,"about_ca_topic_score_gemma":0.00004746252,"domain_scores_codex":[0.9990154,0.00008477688,0.0001473911,0.0003238946,0.0002241238,0.0002044169],"domain_scores_gemma":[0.9992552,0.0001428372,0.00008275278,0.0002789908,0.0000965725,0.0001435813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002403061,0.0002397363,0.002412144,0.00004040284,0.00004977507,0.00000581989,0.002630627,0.08669832,0.000390405,0.003244146,0.0008590601,0.9031892],"study_design_scores_gemma":[0.001106988,0.000608762,0.001704923,0.00007626026,0.00003134101,0.00002983639,0.00006946367,0.9836458,0.0007014918,0.0006238107,0.01115386,0.0002474406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0191422,0.0001372802,0.9782784,0.0009474171,0.0002232436,0.0001541841,0.000001896603,0.0002037725,0.0009115957],"genre_scores_gemma":[0.9403904,0.00004995407,0.05665236,0.00006572373,0.00005065673,0.00002874552,0.000003662227,0.00001959599,0.002738876],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.921626,"threshold_uncertainty_score":0.4733444,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}