{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":519,"total_is_capped":false,"direct_labels_cover":1,"predictions_cover":519,"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":"55eb1e3618f8","filters":{"venue":"IFAC-PapersOnLine"}},"results":[{"id":"W2196218134","doi":"10.1016/j.ifacol.2015.09.022","title":"Model Predictive Control in Industry: Challenges and Opportunities","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":290,"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; Honeywell (Canada)","funders":"","keywords":"Automation; Usability; Workforce; Control (management); Model predictive control; Computer science; Work (physics); Risk analysis (engineering); Project commissioning; Process management; Engineering; Business; Publishing; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.07174965562319378,"gpt":0.2438944537197352,"spread":0.1721447980965414,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001552188,0.0001710515,0.000258613,0.0001014157,0.00001580011,0.0000128246,0.00007129125,0.0002113226,0.00000260168],"category_scores_gemma":[0.00004854398,0.0001728759,0.00001719101,0.00004565885,0.00003543281,0.0002897854,0.00001564232,0.0002616206,0.00000235852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001002273,"about_ca_system_score_gemma":0.00003544526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007305884,"about_ca_topic_score_gemma":0.00006198358,"domain_scores_codex":[0.9992309,0.0000311917,0.000206735,0.0001690786,0.0001415364,0.0002205179],"domain_scores_gemma":[0.9996068,0.00003875657,0.000034536,0.0001366385,0.00005980309,0.0001234168],"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":[0.0000372734,0.00001600525,0.00009610498,0.00002782011,0.0000310625,0.00001263409,0.001596148,0.9855186,0.0002394773,0.0007872473,0.000005250604,0.01163238],"study_design_scores_gemma":[0.001848246,0.00005054681,0.0001926886,0.00004846965,0.00001347,0.00000772255,0.001728927,0.995391,0.000009011943,0.000381403,0.0001606071,0.0001679361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3473274,0.09566218,0.4768324,0.01068151,0.001257964,0.003072005,0.0006646981,0.002798265,0.06170354],"genre_scores_gemma":[0.980815,0.001316927,0.01726823,0.000120594,0.0001364576,0.00006479323,0.00001682354,0.00004236375,0.00021881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6334876,"threshold_uncertainty_score":0.7049675,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2984707533","doi":"10.1016/j.ifacol.2019.10.066","title":"Customization of Automotive Structural Components using Additive Manufacturing and Topology Optimization","year":2019,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Automotive industry; Topology optimization; Personalization; Rapid prototyping; Manufacturing engineering; Computer science; Constraint (computer-aided design); Quality (philosophy); Topology (electrical circuits); Engineering; Mechanical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.006813350206688599,"gpt":0.2138463280073652,"spread":0.2070329778006766,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005183582,0.0002041728,0.0002892686,0.0001869106,0.00004816501,0.00001200788,0.00009083145,0.0001547666,0.0003409576],"category_scores_gemma":[0.00002609823,0.0002214959,0.00003631606,0.0001208802,0.00008113997,0.0002445432,0.0000432869,0.0001558585,0.000005406306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009030771,"about_ca_system_score_gemma":0.00001026633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001957019,"about_ca_topic_score_gemma":0.000003047693,"domain_scores_codex":[0.999134,0.00002886532,0.0002841285,0.0002127875,0.0001117037,0.0002285072],"domain_scores_gemma":[0.9995765,0.00006738576,0.0000827161,0.000146674,0.00007014736,0.00005658518],"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":[0.00001101931,0.000005404476,0.0008733958,0.00005262409,0.00005824434,0.000001503568,0.0003552635,0.9937709,0.004351861,0.00005070625,9.605058e-7,0.0004681406],"study_design_scores_gemma":[0.0006378783,0.00002661776,0.003905382,0.00003778193,0.00002800242,0.00002562304,0.0001835214,0.9807201,0.01420832,0.00001000812,0.0000147894,0.0002019612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8809527,0.0001060077,0.1173804,0.00003087477,0.0006256602,0.0002421736,0.0000726843,0.0002185552,0.0003710381],"genre_scores_gemma":[0.7297124,0.00004318737,0.2699696,0.00001938506,0.00005388921,0.000002757528,0.0001244976,0.0000384708,0.00003576653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1525892,"threshold_uncertainty_score":0.903234,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2889527387","doi":"10.1016/j.ifacol.2018.07.332","title":"A Note on Predefined-Time Stability","year":2018,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":97,"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":"Consejo Nacional de Ciencia y Tecnología","keywords":"Stability (learning theory); Control theory (sociology); Computer science; Time complexity; Lyapunov function; Characterization (materials science); Contrast (vision); Mathematical optimization; Mathematics; Algorithm; Control (management); Artificial intelligence; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.0147260605932504,"gpt":0.2298605092749539,"spread":0.2151344486817035,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002593424,0.0003270093,0.0003988632,0.00008613433,0.00008506695,0.00003520606,0.0002629715,0.0001589822,0.001031318],"category_scores_gemma":[0.0001768896,0.0002970106,0.0001352124,0.0002051278,0.0001240123,0.0001224545,0.00004155023,0.000252554,0.003335118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001846736,"about_ca_system_score_gemma":0.00003538362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002112324,"about_ca_topic_score_gemma":0.00009139934,"domain_scores_codex":[0.9984202,0.00005586125,0.0003647028,0.0003789375,0.0003215811,0.0004587568],"domain_scores_gemma":[0.9988973,0.0001703792,0.00005273716,0.0005792379,0.0001327996,0.0001676118],"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":[0.001270553,0.001029405,0.002304774,0.0004477781,0.0009011024,0.0001542967,0.00487664,0.006172996,0.8898408,0.000927692,0.002182526,0.08989146],"study_design_scores_gemma":[0.003619615,0.00157944,0.007456045,0.0002456181,0.0001103332,0.00003579771,0.0001727433,0.8821847,0.02412233,0.00009695179,0.07883023,0.001546204],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8571391,0.0004723186,0.01297588,0.001524728,0.002163006,0.001258689,0.0008782014,0.002756417,0.1208317],"genre_scores_gemma":[0.926423,0.000009023614,0.06875328,0.000330036,0.002508765,0.00002883726,0.0000538053,0.0001198623,0.00177343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8760117,"threshold_uncertainty_score":0.9999482,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2555341372","doi":"10.1016/j.ifacol.2017.08.1980","title":"Autonomous Landing of a Multirotor Micro Air Vehicle on a High Velocity Ground Vehicle","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"","keywords":"Quadcopter; Multirotor; Extended Kalman filter; Software deployment; Computer science; Micro air vehicle; Aerospace engineering; Range (aeronautics); Automotive engineering; Controller (irrigation); Obstacle avoidance; Kalman filter; Simulation; Aeronautics; Engineering; Aerodynamics; Artificial intelligence; Robot; Mobile robot","retraction":null,"screen_n_in":null,"score":{"opus":0.0266065438266657,"gpt":0.2754260592645171,"spread":0.2488195154378514,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003762374,0.0002697056,0.000409085,0.0001085232,0.0005206192,0.000181885,0.001693425,0.0001428133,0.00001138776],"category_scores_gemma":[0.0002412253,0.0002487864,0.000122622,0.000131358,0.0001532804,0.000484856,0.0003919205,0.0003029709,0.0001100092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000132668,"about_ca_system_score_gemma":0.0001266114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213599,"about_ca_topic_score_gemma":0.00002300171,"domain_scores_codex":[0.9980764,0.00006925352,0.0003510611,0.0006078526,0.000400095,0.000495302],"domain_scores_gemma":[0.9977947,0.0001881115,0.0003887748,0.001355809,0.0001019958,0.0001705608],"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":[0.0005542972,0.003854409,0.08120376,0.0005336942,0.000727748,0.001932791,0.01721933,0.01292794,0.5424029,0.01072441,0.0002620229,0.3276567],"study_design_scores_gemma":[0.00277034,0.0005169016,0.4402277,0.000244284,0.00002548047,0.00003446576,0.00007544974,0.534385,0.02055813,0.0002407148,0.0003254059,0.0005961193],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767068,0.00005391975,0.01870683,0.002453886,0.0008664216,0.000339217,0.00005837002,0.0002513207,0.0005632481],"genre_scores_gemma":[0.534534,0.000003413627,0.4645509,0.0002442438,0.0001895251,0.00001268106,0.000007517389,0.00001733443,0.0004403953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5218448,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2494792419","doi":"10.1016/j.ifacol.2016.07.089","title":"Grey Wolf Optimizer-Based Approach to the Tuning of Pi-Fuzzy Controllers with a Reduced Process Parametric Sensitivity","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"National Authority for Scientific Research and Innovation","keywords":"Control theory (sociology); Sensitivity (control systems); Parametric statistics; Nonlinear system; Servomechanism; Mathematics; Fuzzy control system; Fuzzy logic; Servo; Position (finance); Engineering; Computer science; Control engineering; Control (management); Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01720699442260362,"gpt":0.226488579917011,"spread":0.2092815854944073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046655,0.0003232932,0.0006153321,0.0002039287,0.0001768545,0.00009703983,0.0008588952,0.0001052295,0.000002121752],"category_scores_gemma":[0.0003896646,0.0001553603,0.0001455485,0.001306476,0.0001405506,0.0002689528,0.0000937507,0.0001690439,0.00001769224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007539901,"about_ca_system_score_gemma":0.0002776124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001194521,"about_ca_topic_score_gemma":0.0000263463,"domain_scores_codex":[0.9973419,0.0003230826,0.0004031694,0.000705652,0.0006792886,0.0005469185],"domain_scores_gemma":[0.9976539,0.000665199,0.0002304328,0.0008841187,0.0003505653,0.0002157674],"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":[0.006688482,0.004279962,0.006705671,0.000700694,0.00172985,0.000359665,0.01188402,0.5429763,0.1575195,0.03024559,0.0002369629,0.2366733],"study_design_scores_gemma":[0.02082679,0.002327671,0.004768945,0.0007901829,0.0002068276,0.0002220381,0.001830452,0.9605067,0.005772943,0.0005046547,0.0003171337,0.0019256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1882239,0.0001705208,0.7934051,0.009000059,0.0002231739,0.001450633,0.00002869609,0.0002498105,0.007248111],"genre_scores_gemma":[0.8699486,0.000002602162,0.1289182,0.0006684251,0.0001196243,0.0001045135,0.000002724837,0.00001906339,0.000216231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6817247,"threshold_uncertainty_score":0.6335407,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2997791715","doi":"10.1016/j.ifacol.2019.11.585","title":"An Efficient Two-Stage Genetic Algorithm for Flexible Job-Shop Scheduling","year":2019,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":50,"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":"","keywords":"Mathematical optimization; Job shop scheduling; Population; Computer science; Genetic algorithm; Coding (social sciences); Benchmark (surveying); Scheduling (production processes); Greedy algorithm; Single-machine scheduling; Algorithm; Mathematics; Schedule","retraction":null,"screen_n_in":null,"score":{"opus":0.01132974474597966,"gpt":0.259915158024321,"spread":0.2485854132783414,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002168898,0.000320852,0.0003228794,0.0001636486,0.0001176877,0.0001064697,0.0002944856,0.0001478016,0.0003428396],"category_scores_gemma":[0.00002528493,0.0003279231,0.0001348014,0.0003115589,0.00002984985,0.0001141885,0.00002679719,0.0002261594,0.0002410162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008693151,"about_ca_system_score_gemma":0.0000454652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001382452,"about_ca_topic_score_gemma":0.000004305007,"domain_scores_codex":[0.9983506,0.00002299559,0.0003610553,0.0004483941,0.0002719118,0.0005450671],"domain_scores_gemma":[0.9990339,0.00007944546,0.00005394491,0.0004842388,0.0001229077,0.0002255526],"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":[0.000008538172,0.00007335647,0.0001425235,0.00005412808,0.0000397653,0.000003438013,0.0002256139,0.9707511,0.003044248,0.00006193035,0.000001037238,0.02559429],"study_design_scores_gemma":[0.001557841,0.0001341607,0.000117405,0.0000400096,0.0000304495,0.000007804756,0.0004505312,0.9937747,0.00316298,0.000008106214,0.0002800333,0.0004359522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3107082,0.000582161,0.6852921,0.00006570983,0.00114728,0.0005030184,0.0001202663,0.0009716089,0.0006096768],"genre_scores_gemma":[0.01772,0.00003920211,0.9797328,0.0001598759,0.0005629175,0.00004521435,0.0001577246,0.0001262841,0.001455979],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2944407,"threshold_uncertainty_score":0.9999173,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2214862624","doi":"10.1016/j.ifacol.2015.06.297","title":"A Framework for Modelling Reconfigurable Manufacturing Systems Using Hybridized Discrete-Event and Agent-based Simulation","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Flexible and Reconfigurable Manufacturing Systems","field":"Engineering","cited_by":46,"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":"","keywords":"Reconfigurability; Discrete event simulation; Computer science; Unified Modeling Language; Variety (cybernetics); Systems engineering; Event (particle physics); Factory (object-oriented programming); Mechatronics; Manufacturing engineering; Engineering; Simulation; Software; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.073438443600579,"gpt":0.2933995109847268,"spread":0.2199610673841478,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004499662,0.0004188502,0.0005589395,0.0001925784,0.0001791272,0.0002112585,0.0001591802,0.0002481867,0.00001431068],"category_scores_gemma":[0.00004820395,0.0003892046,0.0001446445,0.00009579779,0.00003463749,0.000246113,0.00001343492,0.0002636719,0.00001277736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002455772,"about_ca_system_score_gemma":0.00005356045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002140372,"about_ca_topic_score_gemma":0.000008064117,"domain_scores_codex":[0.9980507,0.00005677756,0.0005839427,0.0004442358,0.0002835663,0.0005807696],"domain_scores_gemma":[0.9988324,0.0003040816,0.0001425684,0.0003490699,0.00007715595,0.0002947018],"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":[0.00007182407,0.00001728946,0.00001647758,0.0006335588,0.00008905646,0.000006716956,0.0002417623,0.9967089,0.0009902276,0.00006850265,0.000005023482,0.001150647],"study_design_scores_gemma":[0.00122377,0.00006442217,0.000005186678,0.0005847708,0.00007677865,0.00001510894,0.0004138316,0.9781041,0.01707942,0.0003072649,0.001627261,0.0004981371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3954585,0.001541171,0.6002201,0.0000554131,0.00125521,0.0007707776,0.00006925697,0.000377425,0.0002520202],"genre_scores_gemma":[0.8932703,0.00003248056,0.1056555,0.00003589299,0.0005138277,0.00006330279,0.00007634128,0.0001178805,0.0002345178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4978117,"threshold_uncertainty_score":0.999856,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3154766860","doi":"10.1016/j.ifacol.2020.12.126","title":"Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey","year":2020,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta; University of British Columbia","funders":"","keywords":"Monitoring and control; Control (management); Process (computing); Computer science; Scale (ratio); Process control; Industrial engineering; Machine learning; Artificial intelligence; Data science; Engineering; Control engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04777662155701773,"gpt":0.247363262092676,"spread":0.1995866405356582,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002058167,0.0001592153,0.000348249,0.00003643037,0.00005228496,0.00005234314,0.00008438069,0.0001137189,0.000005718772],"category_scores_gemma":[0.0009330938,0.0001521586,0.0000491426,0.0001607441,0.00001605932,0.0001449804,0.00001085904,0.0002150167,0.000001926565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001849665,"about_ca_system_score_gemma":0.00002607144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007300165,"about_ca_topic_score_gemma":0.00004405949,"domain_scores_codex":[0.9991707,0.00004545645,0.0002856519,0.0001787474,0.0001303335,0.0001891276],"domain_scores_gemma":[0.9993406,0.0003366496,0.00006313135,0.00006804372,0.00008132721,0.0001102311],"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":[0.002460686,0.0001046436,0.09239373,0.002295855,0.0009617569,0.00001105254,0.005523092,0.1664293,0.457673,0.0000122406,0.00001415176,0.2721205],"study_design_scores_gemma":[0.005051623,0.00028588,0.0006809305,0.00008282044,0.00004404379,0.000003763538,0.0003230503,0.9867895,0.005219057,0.000003369188,0.001267198,0.0002487514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408084,0.003125481,0.05317074,0.0003522944,0.0005445943,0.0009508222,0.0004827211,0.0004631809,0.0001018181],"genre_scores_gemma":[0.9978338,0.0000509328,0.001297938,0.00002496405,0.0006496724,0.0000466405,0.00002743092,0.00003746624,0.00003110364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8203602,"threshold_uncertainty_score":0.6204846,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2200990036","doi":"10.1016/j.ifacol.2015.10.013","title":"An Optimal Energy Management System for Battery Electric Vehicles","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":44,"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":"Automotive engineering; Drivetrain; Battery electric vehicle; Driving range; Automotive industry; Battery (electricity); Powertrain; Range (aeronautics); Internal combustion engine; Energy management; Computer science; Power (physics); Energy (signal processing); Engineering; Torque","retraction":null,"screen_n_in":null,"score":{"opus":0.02061943467214622,"gpt":0.2660092692019976,"spread":0.2453898345298514,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001567062,0.0002358386,0.0002401715,0.0002597459,0.0000623514,0.00004826254,0.0004895363,0.0001316334,0.00001009903],"category_scores_gemma":[0.00001922097,0.0002290181,0.00005998334,0.0003424487,0.00003257015,0.0002249434,0.00007623746,0.0001637688,0.00003387728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003564016,"about_ca_system_score_gemma":0.00001587248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006056242,"about_ca_topic_score_gemma":0.000005687629,"domain_scores_codex":[0.9985269,0.00002114568,0.0002323965,0.0003295812,0.0002834003,0.0006065689],"domain_scores_gemma":[0.9991992,0.00005080648,0.00002824108,0.0004884773,0.00007282951,0.0001604104],"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":[0.0003555008,0.000217551,0.0002157877,0.0008548073,0.0003749323,0.0002443201,0.0001769117,0.3140481,0.1090542,0.002219999,0.0008844542,0.5713534],"study_design_scores_gemma":[0.001846089,0.0005822553,0.0002416176,0.00008283992,0.00004658488,0.00005168306,0.001783696,0.8925796,0.08319963,0.0001234727,0.01871635,0.0007462443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4058191,0.001726218,0.5833383,0.0004820501,0.0005658287,0.0007777925,0.0001019478,0.004619027,0.002569744],"genre_scores_gemma":[0.6304882,0.00009962233,0.3683021,0.0000760169,0.0002321439,0.0002466622,0.00008102222,0.00009881902,0.0003754113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5785314,"threshold_uncertainty_score":0.9339086,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2202633017","doi":"10.1016/j.ifacol.2015.06.451","title":"A Learning-Based Approach for Automatic Defect Detection in Textile Images","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Contourlet; Classifier (UML); Feature extraction; Textile; Naive Bayes classifier; Computer vision; Machine learning; Support vector machine","retraction":null,"screen_n_in":null,"score":{"opus":0.02512465594607666,"gpt":0.2468364359907549,"spread":0.2217117800446783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005769916,0.0001968714,0.0002826878,0.0002325785,0.00006545438,0.00005132289,0.00007650255,0.0002050311,0.00001436954],"category_scores_gemma":[0.0002845703,0.0001840556,0.0001754813,0.0003629464,0.00001639675,0.000116801,0.000009216137,0.0002821572,0.00003247054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001995849,"about_ca_system_score_gemma":0.00003816043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000924304,"about_ca_topic_score_gemma":0.00005299965,"domain_scores_codex":[0.9989002,0.00007832067,0.0003098023,0.0002294897,0.0001919456,0.0002901978],"domain_scores_gemma":[0.9995137,0.0001038656,0.00005661905,0.0001561131,0.0000662259,0.0001035117],"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":[0.0001314827,0.0001139221,0.0004252362,0.0003102175,0.00006089028,0.000005181365,0.0006017133,0.850553,0.02096356,0.000002981932,0.00007625393,0.1267556],"study_design_scores_gemma":[0.002071785,0.0003738341,0.0002490301,0.00004269621,0.0000246294,0.00001199409,0.000520072,0.9858075,0.009298003,0.000009000801,0.001345332,0.0002461413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6907996,0.0003499784,0.3027845,0.00003141685,0.0009524488,0.001322269,0.00002766518,0.001296029,0.002436087],"genre_scores_gemma":[0.9757351,0.000001589922,0.02346003,0.00001637352,0.0003144605,0.0001882932,0.00003594409,0.00005334018,0.0001949222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2849354,"threshold_uncertainty_score":0.7505568,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2767149636","doi":"10.1016/j.ifacol.2017.08.1991","title":"Constrained Bayesian Optimization with Particle Swarms for Safe Adaptive Controller Tuning","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Bayesian optimization; Particle swarm optimization; Controller (irrigation); Computer science; Discretization; Process (computing); Heuristic; Control theory (sociology); Adaptive control; Fine-tuning; Mathematical optimization; Bayesian probability; Field (mathematics); Control engineering; Control (management); Artificial intelligence; Algorithm; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01999078508450606,"gpt":0.2552093204145486,"spread":0.2352185353300425,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002024819,0.0002307808,0.0002964695,0.0000417813,0.0007191681,0.0005424332,0.0008684788,0.00008094947,0.00004115661],"category_scores_gemma":[0.0001405978,0.0001758319,0.00007333575,0.0001126245,0.0001890277,0.0009076429,0.0001052523,0.0001213388,0.00001086741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003103763,"about_ca_system_score_gemma":0.0001655328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002635895,"about_ca_topic_score_gemma":0.00003130084,"domain_scores_codex":[0.9985454,0.00002557111,0.0002507555,0.0005036514,0.0002297928,0.0004448253],"domain_scores_gemma":[0.9986058,0.0001019825,0.0002981421,0.0005741686,0.0002411689,0.0001787442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002129653,0.001074536,0.007254531,0.0002961374,0.0007655484,0.0002431937,0.006558405,0.06848817,0.01020904,0.5451636,0.00008815561,0.357729],"study_design_scores_gemma":[0.002789562,0.0004633855,0.0009097052,0.00008309257,0.00002822136,0.00002245428,0.0001840958,0.9931297,0.000923053,0.001038725,0.0001112532,0.0003167722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00134714,0.0000536896,0.9911204,0.004405695,0.0001126371,0.0004316118,0.0000251362,0.000121092,0.002382576],"genre_scores_gemma":[0.4854351,0.000006333491,0.5139326,0.0002594526,0.00007353345,0.00003428477,0.000004929266,0.0000111241,0.0002425778],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9246415,"threshold_uncertainty_score":0.7170216,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1888509780","doi":"10.1016/j.ifacol.2015.06.251","title":"Applying Complex Network Theory to the Assessment of Organizational Resilience","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Resilience (materials science); Plan (archaeology); Test (biology); Organizational theory; Network theory; Organizational network analysis; Computer science; Process management; Risk analysis (engineering); Business; Knowledge management; Organizational learning; Management; Economics; Geography; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03150342910953326,"gpt":0.28224288753296,"spread":0.2507394584234267,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113938,0.0001830376,0.0002130145,0.0001172182,0.0002606273,0.000125708,0.0006301179,0.0000404602,0.0004462002],"category_scores_gemma":[0.000201742,0.0001225961,0.00005750894,0.001080752,0.00009819501,0.0002937754,0.0004107329,0.0001175245,0.0001911323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004711621,"about_ca_system_score_gemma":0.00006461215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001328636,"about_ca_topic_score_gemma":0.0001389917,"domain_scores_codex":[0.9983522,0.0000344303,0.0003196471,0.0003112346,0.0006373684,0.0003450748],"domain_scores_gemma":[0.999019,0.0001074146,0.0001881128,0.0003800586,0.0002710045,0.00003444884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001515796,0.0004559941,0.235167,0.000196169,0.0001666808,0.00002724611,0.0006852348,0.3196619,0.001245072,0.3791893,0.02340844,0.03964534],"study_design_scores_gemma":[0.001916621,0.000118008,0.1921386,0.0002015029,0.0002331335,0.000006806103,0.0143237,0.1725413,0.00005051523,0.01679691,0.600619,0.001053898],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3464107,0.001057141,0.3490529,0.07473574,0.00533988,0.01007776,0.00007256842,0.001017469,0.2122358],"genre_scores_gemma":[0.8747677,0.00001968935,0.1047427,0.01517791,0.003415991,0.0001545096,0.0001386498,0.00004899488,0.001533847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5772105,"threshold_uncertainty_score":0.4999325,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2986988833","doi":"10.1016/j.ifacol.2019.10.020","title":"A Digital Twin for Integrated Inspection System in Digital Manufacturing","year":2019,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Engineering drawing; Manufacturing engineering; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005187551930563196,"gpt":0.1889343837926808,"spread":0.1837468318621176,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005103496,0.0002145921,0.0002299464,0.0001666078,0.00003492118,0.0002043979,0.0001144964,0.0001127609,0.00001998157],"category_scores_gemma":[0.00001523519,0.000200089,0.00007005118,0.000123626,0.00001085305,0.0006310182,0.00001956571,0.0001570235,0.00006962059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002161624,"about_ca_system_score_gemma":0.00001365504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001540612,"about_ca_topic_score_gemma":0.00002495329,"domain_scores_codex":[0.999078,0.000002656111,0.0002718981,0.0002484128,0.0001235478,0.0002754894],"domain_scores_gemma":[0.9996858,0.00003807326,0.00004042335,0.0001475132,0.00003158453,0.00005662157],"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":[0.0001995805,0.0001403804,0.005716347,0.002369571,0.0001226365,0.00001813251,0.0009740106,0.875448,0.001032838,0.0002893182,0.00003448356,0.1136547],"study_design_scores_gemma":[0.001925083,0.0001229158,0.002380471,0.0004068324,0.00001523256,0.00002283614,0.001285569,0.9761075,0.01194585,0.00003175906,0.005123512,0.0006323844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706782,0.00008546668,0.01961621,0.00002794148,0.0004110906,0.000556352,0.0001560378,0.001295978,0.007172742],"genre_scores_gemma":[0.9905252,0.000008509699,0.008361149,0.00001172858,0.0001147739,0.00003516391,0.0003027114,0.00005611419,0.0005846309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1130223,"threshold_uncertainty_score":0.8159391,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2186765959","doi":"10.1016/j.ifacol.2015.06.436","title":"Topologically Optimized Diesel Engine Support Manufactured with Additive Manufacturing","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Chassis; Powertrain; Design for manufacturability; Automotive engineering; Diesel engine; Computer science; Mechanical engineering; Manufacturing engineering; Engineering; Torque","retraction":null,"screen_n_in":null,"score":{"opus":0.01154460997219657,"gpt":0.212101327277265,"spread":0.2005567173050684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001669355,0.0005171116,0.0005303958,0.0001969794,0.00008163815,0.00004919813,0.0003314128,0.0002682359,0.001011248],"category_scores_gemma":[0.00007726756,0.0004339534,0.00009217818,0.0001822883,0.0001496115,0.0002873961,0.00007148744,0.0004940142,0.0001306502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001961384,"about_ca_system_score_gemma":0.00004649464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001006747,"about_ca_topic_score_gemma":0.00001714362,"domain_scores_codex":[0.9981263,0.00003251159,0.0003935788,0.0004233691,0.0003405244,0.0006837157],"domain_scores_gemma":[0.9989381,0.0001100711,0.0000650803,0.0004088499,0.00009734234,0.0003804863],"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":[0.0001101616,0.00004254965,0.00006249344,0.0000321881,0.0002044967,0.0001535053,0.0005758971,0.9952796,0.000267506,0.00007581546,0.0002982666,0.00289755],"study_design_scores_gemma":[0.02193264,0.002041467,0.004826083,0.0002456622,0.0004959504,0.001336524,0.004456504,0.7736097,0.1313432,0.0004345783,0.05324127,0.006036355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2500627,0.0008412019,0.6918478,0.002193243,0.003209558,0.001572463,0.0006009582,0.007673825,0.04199827],"genre_scores_gemma":[0.3208189,0.0001212815,0.6765796,0.0002313332,0.0003804668,0.00008857179,0.0003625604,0.0001461577,0.001271182],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2216699,"threshold_uncertainty_score":0.999902,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2557098366","doi":"10.1016/j.ifacol.2016.10.739","title":"The Role and Importance of Real Time Digital Simulation in the Development and Testing of Power System Control and Protection Equipment","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"RTDS Technologies (Canada)","funders":"","keywords":"Real-time simulation; Control (management); Computer science; Reliability engineering; Power (physics); Real Time Digital Simulator; Systems engineering; Electric power system; Risk analysis (engineering); Engineering; Embedded system; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.007696089779278225,"gpt":0.1993035231974546,"spread":0.1916074334181764,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003230852,0.00008891828,0.000148802,0.00002904502,0.00004617748,0.00003022059,0.00003685924,0.00003703911,9.285937e-7],"category_scores_gemma":[0.00005898269,0.00004652619,0.00001161884,0.00006033163,0.00003176855,0.0001122416,0.000009729947,0.00003301055,7.023182e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000316048,"about_ca_system_score_gemma":0.00001049246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001680735,"about_ca_topic_score_gemma":0.0000186868,"domain_scores_codex":[0.99932,0.00002899734,0.0003224334,0.00009765623,0.0001284893,0.0001024086],"domain_scores_gemma":[0.9994467,0.0003126205,0.00009459572,0.0000837843,0.00003906908,0.00002316617],"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":[0.0003717911,0.00007335833,0.1818,0.0004750033,0.0002303817,0.000005226619,0.006012326,0.030296,0.3269078,0.0005205723,5.688251e-7,0.453307],"study_design_scores_gemma":[0.002176085,0.0001086234,0.1596434,0.0003177634,0.00001498468,0.00001163244,0.001226767,0.83562,0.0005256211,0.00003013495,0.0001701344,0.0001548576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972766,0.0002817989,0.0007848506,0.00005952503,0.00001839846,0.0004605509,0.000009195892,0.00003065502,0.001078441],"genre_scores_gemma":[0.9994323,0.000004925118,0.0004875577,0.00000244274,0.00001847582,0.00001976604,0.000001090529,0.000008449225,0.00002501115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.805324,"threshold_uncertainty_score":0.1897283,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1802249127","doi":"10.1016/j.ifacol.2015.08.157","title":"Well Placement Optimization with Geological Uncertainty Reduction","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":31,"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":"","keywords":"Reduction (mathematics); Realization (probability); Computer science; Mathematical optimization; Representation (politics); Optimization problem; Plan (archaeology); Production (economics); Algorithm; Mathematics; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.02566668333936791,"gpt":0.2592092352627665,"spread":0.2335425519233986,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002364724,0.0001659926,0.0001621617,0.00007025789,0.00003595611,0.0000271664,0.00008752439,0.00009744452,0.0001372458],"category_scores_gemma":[0.00004576713,0.0001320603,0.00003016464,0.0002093874,0.00002703672,0.0001142309,0.0000138844,0.0001578088,0.00002944008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001200495,"about_ca_system_score_gemma":0.00002153659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001288644,"about_ca_topic_score_gemma":0.000002953438,"domain_scores_codex":[0.999164,0.00003936874,0.000177676,0.0001773015,0.0002267909,0.0002148321],"domain_scores_gemma":[0.9995255,0.00003140253,0.00002391158,0.0001867063,0.00008231952,0.0001501504],"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":[0.00005226645,0.0000193775,0.0001227114,0.00001518487,0.00002360978,0.000003962031,0.0001416885,0.9989827,0.0002222175,0.00003323187,0.00004326374,0.0003397487],"study_design_scores_gemma":[0.0008987963,0.0001187826,0.00007250413,0.00001569164,0.00001453047,0.00001740108,0.000239941,0.9961153,0.0002691219,0.0000123755,0.002039962,0.0001856453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4156796,0.0001833996,0.5781423,0.0002709657,0.0004118191,0.0001947865,0.000006109476,0.000673075,0.004437852],"genre_scores_gemma":[0.2289291,0.00004287536,0.7697502,0.00002269094,0.0002679302,0.00001811766,0.0001089289,0.00003368608,0.0008264926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1916078,"threshold_uncertainty_score":0.5385262,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2413557228","doi":"10.1016/j.ifacol.2015.09.005","title":"Soft Sensor Model Maintenance: A Case Study in Industrial Processes∗∗The authors would like to acknowledge the support from the DOW chemical company and the natural sciences and engineering research council of Canada (NSERC).","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"McMaster University","funders":"","keywords":"Soft sensor; Partial least squares regression; Process (computing); Kalman filter; Data mining; Computer science; Set (abstract data type); Engineering; Industrial engineering; Machine learning; Artificial intelligence; Control engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.09478916515296334,"gpt":0.2908371682373549,"spread":0.1960480030843916,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003469303,0.0001752983,0.0002676705,0.00003541973,0.0002207921,0.0001079922,0.0003570728,0.0001018854,0.000002910213],"category_scores_gemma":[0.001817941,0.00007885363,0.00002302786,0.0005762434,0.0002709302,0.00006706193,0.0001068808,0.0009870229,8.800696e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003602321,"about_ca_system_score_gemma":0.001430368,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08918914,"about_ca_topic_score_gemma":0.457793,"domain_scores_codex":[0.9980596,0.0001410041,0.0002993045,0.0002410866,0.0008891633,0.0003697849],"domain_scores_gemma":[0.9984005,0.0008163485,0.00003549359,0.0002416417,0.0003848112,0.0001211985],"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":[0.003768325,0.0004720296,0.01021254,0.0004435517,0.0010401,0.0008786178,0.4270217,0.5035527,0.0226121,0.0001978877,0.01584795,0.01395254],"study_design_scores_gemma":[0.002550237,0.00006628488,0.0001741029,0.00005498781,0.00002459611,0.0001813951,0.0514483,0.9430444,0.00009282197,0.000009392836,0.00219402,0.0001595212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945374,0.0006948901,0.00002853143,0.003210379,0.0004056507,0.000942831,0.00004754486,0.00003075574,0.0001020253],"genre_scores_gemma":[0.9992397,0.000006613313,0.0001436959,0.0001153705,0.0002187781,0.00008535638,9.20052e-7,0.0000154516,0.0001740466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4394917,"threshold_uncertainty_score":0.916876,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1473715434","doi":"10.1016/j.ifacol.2015.06.054","title":"The Evolution of Rapid Production: How to Adopt Novel Manufacturing Technology","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Production (economics); Business; Disadvantage; Business model; Competitive advantage; Service (business); Product (mathematics); Industrial organization; Manufacturing engineering; Commerce; Computer science; Marketing; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01961996899439879,"gpt":0.2187592498291591,"spread":0.1991392808347603,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000244287,0.0002025743,0.0002039273,0.0002220221,0.0001200548,0.00002671198,0.0003991311,0.0001546063,0.000005100289],"category_scores_gemma":[0.0005090018,0.0001550284,0.00005339092,0.0002971875,0.0001584085,0.00008823952,0.0001554665,0.0003115668,0.00002522358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002067344,"about_ca_system_score_gemma":0.0000281898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001275937,"about_ca_topic_score_gemma":0.00002661632,"domain_scores_codex":[0.9989899,0.0000110721,0.0001971396,0.0002569623,0.0002035222,0.0003414375],"domain_scores_gemma":[0.9992034,0.00004974281,0.00006237316,0.0005202681,0.00009894615,0.00006525808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001367802,0.0001971334,0.0008464482,0.0002771686,0.0004464092,0.00001614795,0.001300759,0.05608165,0.1414156,0.004220812,0.00232389,0.7927372],"study_design_scores_gemma":[0.0004177624,0.0001974719,0.002125787,0.00009913269,0.00002805121,0.00004834964,0.004958982,0.001807172,0.9499545,0.0008862348,0.03906971,0.0004068232],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624179,0.0009968781,0.01924363,0.01265098,0.001152575,0.0003617795,0.00002784715,0.002144875,0.001003533],"genre_scores_gemma":[0.8992276,0.00004550425,0.09993125,0.00001088829,0.0002174572,0.0000333012,0.00000471158,0.0000313913,0.0004979394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8085389,"threshold_uncertainty_score":0.6321875,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312733588","doi":"10.1016/j.ifacol.2022.10.217","title":"Machine Learning Models for Efficient Port Terminal Operations: Case of Vessels’ Arrival Times Prediction","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Port (circuit theory); Terminal (telecommunication); Computer science; Work (physics); Supply chain; Operations research; Artificial intelligence; Engineering; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.01966376198464235,"gpt":0.2342855123939905,"spread":0.2146217504093482,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002289189,0.0001416178,0.0001930127,0.00008796227,0.0002535431,0.00001712798,0.00008352593,0.00004076834,0.0005299776],"category_scores_gemma":[0.00004702189,0.0001450322,0.00007550177,0.000103992,0.00002926824,0.00005363508,0.00004757298,0.0002255068,0.000001120033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005853205,"about_ca_system_score_gemma":0.00003307757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001131511,"about_ca_topic_score_gemma":0.00002206063,"domain_scores_codex":[0.9991267,0.00002257806,0.0003158585,0.0001775784,0.000162946,0.0001943647],"domain_scores_gemma":[0.9996467,0.0000567373,0.00003938172,0.0001439902,0.000052965,0.00006026024],"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":[0.00002007797,0.00008143327,0.00007834961,0.00007602925,0.0000333875,0.0001466234,0.0004285403,0.9938082,0.0008597045,0.0005434699,0.00002218746,0.003902056],"study_design_scores_gemma":[0.0003995092,0.0001724188,0.00002338284,0.00001014209,0.00005747966,0.0006220059,0.0003668002,0.996493,0.0002155117,0.00005549345,0.001446003,0.0001382691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7177271,0.002017495,0.2638796,0.0003230468,0.001486372,0.001467498,0.005041459,0.0008119735,0.007245429],"genre_scores_gemma":[0.9454105,0.00002827997,0.05280374,0.00002409774,0.0001510106,0.00008672106,0.0004941255,0.0000370514,0.0009644149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2276834,"threshold_uncertainty_score":0.5914243,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897080808","doi":"10.1016/j.ifacol.2018.09.347","title":"State of Health Estimation for Lithium-Ion Batteries","year":2018,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":28,"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":"","keywords":"State of health; Battery (electricity); State of charge; Lithium-ion battery; Lithium (medication); Computer science; Reliability engineering; Internal resistance; Automotive engineering; Engineering; Power (physics); Medicine; Physics; Thermodynamics","retraction":null,"screen_n_in":null,"score":{"opus":0.02640901257541478,"gpt":0.319066289631067,"spread":0.2926572770556523,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001893772,0.0001300172,0.0002215912,0.0001222759,0.00007204092,0.00001240275,0.0001732173,0.00005353278,0.00003792538],"category_scores_gemma":[0.0001335247,0.0001237986,0.00003769908,0.0001934012,0.0001544871,0.0001631147,0.00004389819,0.0001145816,0.00002479475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009489087,"about_ca_system_score_gemma":0.00002718636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001193093,"about_ca_topic_score_gemma":0.00003693715,"domain_scores_codex":[0.999039,0.00001503253,0.0002922507,0.0001637121,0.0001543246,0.000335676],"domain_scores_gemma":[0.9994545,0.00008179383,0.000061712,0.0002650722,0.00009768697,0.00003923094],"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":[0.00005938298,0.00004354557,0.0001887082,0.0005945262,0.00004496304,0.000001049619,0.0007895453,0.01100244,0.08215909,0.000107536,0.0002207681,0.9047884],"study_design_scores_gemma":[0.001384001,0.00167641,0.00388611,0.0002813546,0.00001172969,0.00001099629,0.0005368173,0.5528924,0.4227494,0.004220656,0.01176948,0.00058064],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.473716,0.0003654236,0.5212317,0.002588878,0.0003256446,0.00057606,0.0002210458,0.0007506952,0.0002246462],"genre_scores_gemma":[0.3775058,0.0001294528,0.6217232,0.0001094023,0.00008848936,0.00004967389,0.00007919395,0.00004640678,0.0002684545],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9042078,"threshold_uncertainty_score":0.5048358,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2345521790","doi":"10.1016/j.ifacol.2015.06.385","title":"Production and setup policy optimization for hybrid manufacturing-remanufacturing systems","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Remanufacturing; Production (economics); Holding cost; Scheduling (production processes); Sensitivity (control systems); Raw material; Manufacturing engineering; Computer science; Mode (computer interface); Reliability engineering; Process engineering; Operations management; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.021291469712182,"gpt":0.2350466145618806,"spread":0.2137551448496985,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006165634,0.0003121433,0.0002832853,0.0005428076,0.0002515059,0.0004951289,0.0001991371,0.00006577234,0.00002575991],"category_scores_gemma":[0.0005177458,0.0002985832,0.00006259056,0.0002224479,0.00005273821,0.001272646,0.0002068556,0.0001091758,0.00003020073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002339896,"about_ca_system_score_gemma":0.00004615208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009479255,"about_ca_topic_score_gemma":0.00003720493,"domain_scores_codex":[0.9982421,0.0000153167,0.0003335314,0.0005621859,0.0003447112,0.0005021453],"domain_scores_gemma":[0.9991027,0.00003075898,0.0002463451,0.0003307238,0.0002408146,0.00004872112],"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":[0.0003136973,0.0002014097,0.00114444,0.003090956,0.0001812915,0.00004253393,0.0003527181,0.9745281,0.0001248818,0.003635822,0.002737118,0.01364705],"study_design_scores_gemma":[0.003816635,0.0001093595,0.001047904,0.000301169,0.0003504747,0.00005256831,0.009848411,0.8364039,0.001728816,0.001984718,0.1427814,0.001574632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8744761,0.0008867829,0.07286444,0.03148037,0.004568673,0.007018077,0.00005350358,0.001528112,0.007123945],"genre_scores_gemma":[0.9404026,0.00003713928,0.04228026,0.001508473,0.009886244,0.0002705009,0.0004507437,0.00014024,0.005023847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1400443,"threshold_uncertainty_score":0.9999467,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4297792233","doi":"10.1016/j.ifacol.2022.07.605","title":"GWO-Based Optimal Tuning of Controllers for Shape Memory Alloy Wire Actuators","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Shape Memory Alloy Transformations","field":"Materials Science","cited_by":26,"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; Ministry of Education and Research, Romania; Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii; Corporation for National and Community Service","keywords":"Control theory (sociology); SMA*; Controller (irrigation); Actuator; Fuzzy logic; Nonlinear system; Computer science; Shape-memory alloy; Fuzzy control system; Control engineering; Engineering; Algorithm; Control (management); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01957580449935913,"gpt":0.2578551046227437,"spread":0.2382793001233846,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008566591,0.0002604527,0.0004575987,0.0001795041,0.0005382469,0.00003773442,0.000566541,0.00006939937,0.005069362],"category_scores_gemma":[0.0001689403,0.0002611792,0.0002579563,0.0002787098,0.0001607779,0.0002721836,0.00007678019,0.0001992543,0.00003011101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367651,"about_ca_system_score_gemma":0.0003036429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003074669,"about_ca_topic_score_gemma":0.00002231288,"domain_scores_codex":[0.9978647,0.0001390142,0.000563361,0.0003919391,0.000558219,0.0004828302],"domain_scores_gemma":[0.998675,0.0004507056,0.000254926,0.000355175,0.0001244734,0.0001396583],"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":[0.0007893036,0.0003107629,0.00009072105,0.0001188542,0.00005846195,0.0000117722,0.002023172,0.1046823,0.8882484,0.0001852531,0.00006907199,0.003411904],"study_design_scores_gemma":[0.009570089,0.00108858,0.0002773842,0.00006178704,0.0002353062,0.00002770797,0.008050284,0.8476008,0.1286394,0.00003260778,0.003593307,0.000822842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900489,0.00008781868,0.00482469,0.001799734,0.000600408,0.0009279283,0.001044636,0.0001889623,0.0004769244],"genre_scores_gemma":[0.8458511,0.000002444221,0.1523357,0.0009020257,0.0001067064,0.0002868394,0.0001910543,0.00004905738,0.0002750903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.759609,"threshold_uncertainty_score":0.999984,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2884324793","doi":"10.1016/j.ifacol.2018.06.382","title":"Benchmarking of Industrial Stick-Slip Mitigation Controllers","year":2018,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":26,"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":"","keywords":"Drill string; Control theory (sociology); Slip (aerodynamics); Drill; Engineering; Amplitude; Controller (irrigation); Coulomb; Computer science; Mechanical engineering; Physics; Control (management); Aerospace engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01098035921138455,"gpt":0.1992387964543208,"spread":0.1882584372429363,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001640261,0.0001722475,0.0002514401,0.0001089874,0.00004753771,0.00001795584,0.0001171793,0.0001406838,0.0001359983],"category_scores_gemma":[0.00007790529,0.0001752974,0.00007664362,0.0002075164,0.00006655606,0.00009015922,0.00001456821,0.0001811399,0.00002911739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004743949,"about_ca_system_score_gemma":0.00002036774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002085164,"about_ca_topic_score_gemma":0.00001389889,"domain_scores_codex":[0.9990867,0.00001322987,0.0002965881,0.0001532055,0.0001804997,0.0002698159],"domain_scores_gemma":[0.9995487,0.00008671398,0.00004552853,0.0001725812,0.00006095575,0.00008553208],"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":[0.0001331722,0.00009503123,0.003697789,0.0002240413,0.000527931,0.00001705557,0.002118244,0.6560194,0.1783611,0.0006444702,0.0003498878,0.1578119],"study_design_scores_gemma":[0.001838156,0.0001654877,0.0005159652,0.0002348912,0.00006179717,0.000005619377,0.0001322392,0.9695614,0.02477422,0.00004517191,0.002304543,0.0003605169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9579904,0.0003057077,0.03054091,0.0001118389,0.002719277,0.0002388857,0.00005386062,0.0005058009,0.007533313],"genre_scores_gemma":[0.9683459,0.00002915826,0.02963181,0.00002595801,0.001809894,0.000005248236,0.0000347227,0.00003937729,0.00007787939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.313542,"threshold_uncertainty_score":0.7148421,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3153015002","doi":"10.1016/j.ifacol.2020.12.1549","title":"Fast Trajectory Planning in Cartesian rather than Frenet Frame: A Precise Solution for Autonomous Driving in Complex Urban Scenarios","year":2020,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada","keywords":"Frenet–Serret formulas; Trajectory; Cartesian coordinate system; Computer science; Control theory (sociology); Frame (networking); Mathematical optimization; Constraint (computer-aided design); Motion planning; Curvature; Simulation; Mathematics; Robot; Control (management); Artificial intelligence; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.04216438017253147,"gpt":0.273681377512884,"spread":0.2315169973403526,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003783234,0.0003470228,0.000499562,0.0002351286,0.0001284335,0.0001352812,0.0008781031,0.000188343,0.00001171844],"category_scores_gemma":[0.0001866385,0.0003674061,0.0001133368,0.0006153837,0.00005903511,0.0003924606,0.000161453,0.0004648882,0.00001792638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002187277,"about_ca_system_score_gemma":0.0001990083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001599995,"about_ca_topic_score_gemma":0.0002040367,"domain_scores_codex":[0.9974139,0.000141926,0.0005337547,0.0008450084,0.0003157344,0.0007497059],"domain_scores_gemma":[0.9989057,0.0002308371,0.0001733429,0.0004098492,0.0000447402,0.0002355506],"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":[0.0002032034,0.0009697239,0.2317518,0.0003086622,0.000133467,0.0007916843,0.1557166,0.453839,0.06220103,0.0003441681,0.0007137877,0.09302685],"study_design_scores_gemma":[0.001358758,0.0002297431,0.06645257,0.0001742824,0.000008072917,0.00001336599,0.0003108899,0.9306003,0.0001218505,0.00002991207,0.0003054025,0.0003948915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1792463,0.000555903,0.8135391,0.004402271,0.0004202453,0.001080803,0.000054745,0.0004641856,0.0002364449],"genre_scores_gemma":[0.3349215,0.000002435195,0.6640619,0.0005158717,0.0002804077,0.0000608183,0.00006147285,0.00003459588,0.00006094221],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4767613,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2514725691","doi":"10.1016/j.ifacol.2016.08.002","title":"Estimating tailpipe NOx concentration using a dynamic NOx/ammonia cross sensitivity model coupled to a three state control oriented SCR model","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":24,"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":"","keywords":"NOx; Selective catalytic reduction; Diesel engine; Diesel fuel; Slip (aerodynamics); Sensitivity (control systems); Ammonia; Environmental science; Automotive engineering; Catalysis; Chemistry; Engineering; Combustion","retraction":null,"screen_n_in":null,"score":{"opus":0.01644730756060145,"gpt":0.2977771639018822,"spread":0.2813298563412808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001732214,0.000505137,0.0006585533,0.00009668526,0.000499196,0.0004076279,0.0005224942,0.0001432699,0.0000682157],"category_scores_gemma":[0.001274922,0.0003954006,0.00009877522,0.0003950587,0.00052291,0.001271371,0.0002874362,0.0001369731,0.00017153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005989305,"about_ca_system_score_gemma":0.0006681486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000311535,"about_ca_topic_score_gemma":0.0007892502,"domain_scores_codex":[0.9958122,0.00009134167,0.0008409367,0.001199929,0.0009348311,0.001120705],"domain_scores_gemma":[0.997504,0.0002656867,0.0004756005,0.0007514935,0.0006222669,0.0003809602],"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":[0.000223916,0.00005389283,0.0001328705,0.00003498045,0.00000631104,0.00001652176,0.0002508924,0.4018485,0.5969414,0.0000391218,4.343993e-7,0.0004511417],"study_design_scores_gemma":[0.001968506,0.00006494956,0.0001243445,0.000215168,0.00004226155,0.00004511873,0.00001956458,0.9059216,0.09041179,0.000672551,9.29164e-7,0.0005131877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5087355,0.00001154842,0.4892225,0.0003493581,0.0003905179,0.0004574728,0.0006528044,0.0001708567,0.000009381268],"genre_scores_gemma":[0.6013892,0.000001645648,0.3980204,0.0003167221,0.00007446925,0.00002716916,0.00001440012,0.00003940948,0.0001166096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5065296,"threshold_uncertainty_score":0.9998498,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2744953493","doi":"10.1016/j.ifacol.2017.08.061","title":"Three examples of the stability properties of the invariant extended Kalman filter","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Extended Kalman filter; Invariant extended Kalman filter; Control theory (sociology); Kalman filter; Multiplicative function; Alpha beta filter; Convergence (economics); Computer science; Unscented transform; Mathematics; Artificial intelligence; Moving horizon estimation; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.06367141838380903,"gpt":0.2462683893208179,"spread":0.1825969709370088,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004864428,0.0001662967,0.0002530966,0.00001929018,0.0005309903,0.0001072497,0.003412911,0.00008209753,0.00005494875],"category_scores_gemma":[0.0004131353,0.00007972394,0.0001688546,0.0001162914,0.0005546794,0.0002883533,0.001352457,0.0002363492,0.000003770353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001564797,"about_ca_system_score_gemma":0.00009235893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006060825,"about_ca_topic_score_gemma":0.0009941398,"domain_scores_codex":[0.9984489,0.0001176957,0.0003732608,0.0003634086,0.0004471491,0.0002495934],"domain_scores_gemma":[0.9960432,0.00009930933,0.000419129,0.003245463,0.0001453131,0.00004757468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000335848,0.002151842,0.1923333,0.0007356243,0.0003828732,0.00001827567,0.01561137,0.0009317159,0.5769156,0.06654619,0.0009387405,0.1430986],"study_design_scores_gemma":[0.001004941,0.0001215794,0.7999896,0.0005599348,0.00005201362,0.00002260378,0.0002638088,0.04147895,0.1506136,0.003644166,0.001799192,0.0004495799],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845092,0.0003258243,0.007183551,0.005425913,0.001190741,0.0004239413,0.00009876458,0.00006144603,0.0007805978],"genre_scores_gemma":[0.9488544,0.00001694805,0.05073144,0.0001691704,0.0001069874,0.000006485235,0.000001827732,0.000009406017,0.0001032949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6076563,"threshold_uncertainty_score":0.6342094,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2988613083","doi":"10.1016/j.ifacol.2019.10.056","title":"A Review of Developments in the Fields of the Design of Smart Cutting Tools, Wear Monitoring, and Sensor Innovation","year":2019,"lang":"en","type":"review","venue":"IFAC-PapersOnLine","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Manufacturing engineering; Engineering; Work (physics); Systems engineering; Data science; Mechanical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.0789060811662014,"gpt":0.327274887217883,"spread":0.2483688060516816,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004127687,0.0001810396,0.0006720313,0.00008200799,0.00001837753,0.000005658759,0.0002001334,0.0001190797,0.000003094232],"category_scores_gemma":[0.0003166795,0.0001098145,0.0000619277,0.0006628379,0.00001974029,0.00006806992,0.00003901497,0.0002421934,3.913069e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002298774,"about_ca_system_score_gemma":0.00007209958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000422675,"about_ca_topic_score_gemma":5.436295e-7,"domain_scores_codex":[0.9988698,0.00006835174,0.0006829193,0.0001235317,0.0001512494,0.0001041281],"domain_scores_gemma":[0.999101,0.0002222805,0.0004016175,0.0001796128,0.00008816229,0.000007289272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000003415796,0.00002052893,0.00005763431,0.2025255,0.00006953897,4.749458e-7,0.0004652684,0.006222817,0.00003289695,0.00004803365,0.000003062039,0.7905508],"study_design_scores_gemma":[0.00092717,0.0002093509,0.0002251046,0.8307297,0.001196792,0.00005837587,0.0005243289,0.006560872,0.0006591188,0.00003620758,0.1577768,0.001096275],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006256007,0.9945875,0.004396262,0.00001553902,0.0001229649,0.0006650127,0.00001829597,0.00001119865,0.0001206626],"genre_scores_gemma":[0.00009454232,0.9156528,0.08412266,0.00002161709,0.00002653832,0.00001814668,0.00001852635,0.00002218051,0.00002306331],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7894545,"threshold_uncertainty_score":0.4478104,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2522617141","doi":"10.1016/j.ifacol.2016.07.319","title":"A Multi-Scale Model of the Whole Human Body based on Dynamic Parsimonious Flux Balance Analysis","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Flux balance analysis; Computer science; Toolbox; Set (abstract data type); Scale (ratio); MATLAB; Systems biology; Population; Convergence (economics); Metabolic network; Machine learning; Mathematical optimization; Bioinformatics; Biology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.006644408579191945,"gpt":0.2344749924075528,"spread":0.2278305838283609,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096453,0.0001479732,0.0001837118,0.00005402108,0.00006206641,0.000005515891,0.0001995008,0.000105636,0.0000121332],"category_scores_gemma":[0.00003939501,0.00008792379,0.0002021589,0.0001852264,0.00007109989,0.0000023991,0.00003049058,0.00006205174,0.000004431978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000149824,"about_ca_system_score_gemma":0.00002513097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001727581,"about_ca_topic_score_gemma":0.00009273695,"domain_scores_codex":[0.9991764,0.00003206559,0.0001749961,0.0003295717,0.0001107729,0.0001762387],"domain_scores_gemma":[0.9992697,0.000003298328,0.00008428941,0.0005450294,0.00005666259,0.00004099964],"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":[0.00002337113,0.0001138667,0.0009972479,0.000008935477,0.00008610136,1.514615e-7,0.00001223308,0.01894858,0.9792401,0.000001478521,0.00001313972,0.0005548298],"study_design_scores_gemma":[0.0008642336,0.0001139301,0.006880929,0.00003500507,0.0002208731,0.000001045157,0.00001054048,0.1670256,0.8240071,0.000002905692,0.0006242425,0.0002136346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762818,0.0001262949,0.02244004,0.000617534,0.0001029616,0.0001189612,0.0002450578,0.000018821,0.0000485654],"genre_scores_gemma":[0.9749355,0.00002154462,0.02136541,0.0001226629,0.00009235067,0.000007191645,0.0001050329,0.00001670281,0.003333587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.155233,"threshold_uncertainty_score":0.3585428,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3211942258","doi":"10.1016/j.ifacol.2021.08.124","title":"LIVE Digital Twin for Smart Maintenance in Structural Systems","year":2021,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prognostics; Pipeline (software); Predictive maintenance; Architecture; Systems engineering; Computer science; Service (business); Engineering; Pipeline transport; Reliability engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.007900122052016659,"gpt":0.2560186921123698,"spread":0.2481185700603531,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008416527,0.0002339339,0.000323391,0.00007620113,0.00003010227,0.0001076451,0.0001746551,0.0001144167,0.00004781823],"category_scores_gemma":[0.0002084226,0.0002264338,0.0001031713,0.0001833351,0.0000251572,0.0002232889,0.00004419485,0.0002055856,0.00002196206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001471857,"about_ca_system_score_gemma":0.00002703378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007441625,"about_ca_topic_score_gemma":0.0002584564,"domain_scores_codex":[0.9988452,0.00001588712,0.00031928,0.0002865599,0.0001429382,0.000390139],"domain_scores_gemma":[0.9993906,0.0001501233,0.00003368879,0.0002687673,0.00007785141,0.00007894263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004926281,0.001369251,0.4674825,0.009937059,0.001622584,0.00329764,0.01178887,0.126639,0.1107181,0.02199486,0.0134484,0.2312091],"study_design_scores_gemma":[0.003014708,0.0002299533,0.03159524,0.001070185,0.00005240218,0.0002442826,0.001515057,0.9202786,0.0119886,0.0008438435,0.027416,0.001751103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890357,0.001665871,0.002922826,0.0004637883,0.0007738697,0.0007252659,0.0007392277,0.0008777182,0.002795702],"genre_scores_gemma":[0.9461563,0.00007704634,0.05230484,0.000107649,0.0002460464,0.0001719807,0.0002716821,0.00007003183,0.000594478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7936397,"threshold_uncertainty_score":0.9233702,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1867625458","doi":"10.1016/j.ifacol.2015.06.127","title":"Production Planning and Opportunistic Preventive Maintenance for Unreliable One-Machine Two-Products Manufacturing Systems","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Preventive maintenance; Robustness (evolution); Reliability engineering; Economic shortage; Synchronization (alternating current); Computer science; Production planning; Discrete event simulation; Production (economics); Control (management); Operations research; Industrial engineering; Variance (accounting); Production control; Proactive maintenance; Engineering; Risk analysis (engineering); Simulation; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.0386810661580436,"gpt":0.2529649696475627,"spread":0.2142839034895191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005326884,0.0002418412,0.0003074624,0.00008185712,0.000104646,0.00006675223,0.0001049514,0.00008280883,0.000003434237],"category_scores_gemma":[0.0004578891,0.0002303135,0.00003658707,0.0001065021,0.00005836115,0.0003397558,0.00003192469,0.0001723039,0.000005724847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001651407,"about_ca_system_score_gemma":0.00004279514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000592305,"about_ca_topic_score_gemma":0.00001185918,"domain_scores_codex":[0.9986517,0.00002918344,0.0003245968,0.0004295948,0.000178891,0.0003859785],"domain_scores_gemma":[0.99924,0.00005423185,0.0000910829,0.0002816768,0.000180167,0.0001528416],"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":[0.0001401589,0.00007745934,0.0001893309,0.001010615,0.00009515413,0.000007670779,0.0006761608,0.9887033,0.00501819,0.0005531432,0.0004181525,0.003110709],"study_design_scores_gemma":[0.002146294,0.0002600404,0.0003320469,0.0009118835,0.0001436636,0.00007831998,0.001286435,0.9761133,0.008930678,0.0006241601,0.008432679,0.0007405022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4879375,0.009794693,0.4744204,0.003284434,0.01094334,0.006444021,0.0004741251,0.002052671,0.004648839],"genre_scores_gemma":[0.8040203,0.0003575171,0.1898596,0.00005159991,0.000794922,0.0002004077,0.0003771383,0.0001041332,0.004234416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3160828,"threshold_uncertainty_score":0.939191,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1458772023","doi":"10.1016/j.ifacol.2015.06.120","title":"Proposal Sustainability Assessment of Resource Sharing in Intermodal Freight Transport with Agent-based Simulation","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Outsourcing and Supply Chain Management","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Sustainability; Resource (disambiguation); Sharing economy; Transport engineering; Business; Shared resource; Environmental economics; Computer science; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.02099432883290166,"gpt":0.2713060370712398,"spread":0.2503117082383382,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009833555,0.0002456068,0.0003367052,0.0003482401,0.00006485379,0.00007072244,0.0002848596,0.00007277085,0.00006087045],"category_scores_gemma":[0.00007717046,0.0002038783,0.00008165737,0.0005192647,0.00008131772,0.0004126496,0.00008819601,0.0002065513,0.000004429147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002539122,"about_ca_system_score_gemma":0.000134617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008115136,"about_ca_topic_score_gemma":0.0008368624,"domain_scores_codex":[0.9981868,0.00002660016,0.0004504309,0.0004604103,0.0005258096,0.0003499142],"domain_scores_gemma":[0.9990642,0.00004292818,0.0002195515,0.0003810909,0.0002591332,0.00003308068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002511027,0.0003623022,0.5331501,0.00047605,0.0000252995,0.00005644141,0.0003116906,0.4629455,0.00003611436,0.0009945869,0.000006675584,0.001384163],"study_design_scores_gemma":[0.002814741,0.00009677428,0.1003754,0.0001683693,0.00007746421,4.394394e-7,0.002945528,0.8903378,0.00002166059,0.0003921581,0.002431615,0.0003380348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9612707,0.00001571202,0.02762471,0.003336176,0.00009240815,0.0008280688,0.000006276639,0.0001421042,0.006683819],"genre_scores_gemma":[0.9848058,1.781637e-7,0.01402833,0.0004012587,0.0002444495,0.00002618231,0.0001624635,0.00003530991,0.0002959789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4327747,"threshold_uncertainty_score":0.8313918,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897473460","doi":"10.1016/j.ifacol.2018.09.133","title":"Using Decoupling Methods to Reduce Polynomial NARX Models","year":2018,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":20,"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":"","keywords":"Nonlinear autoregressive exogenous model; Polynomial; Decoupling (probability); Polynomial matrix; Nonlinear system; Control theory (sociology); Applied mathematics; Matrix polynomial; Mathematics; Computer science; Benchmark (surveying); Autoregressive model; Algorithm; Mathematical optimization; Control engineering; Control (management); Artificial intelligence; Engineering; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.1033372304670336,"gpt":0.4124253959466641,"spread":0.3090881654796305,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002251455,0.0002339641,0.0002645458,0.00008520243,0.000280586,0.00006381261,0.0002021845,0.0000698299,0.0007854023],"category_scores_gemma":[0.000007449522,0.000220786,0.0001396373,0.0002718359,0.00006841304,0.0002005054,0.00009469367,0.0002151369,0.00006842897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004224643,"about_ca_system_score_gemma":0.00006683221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002031406,"about_ca_topic_score_gemma":0.000005585332,"domain_scores_codex":[0.998625,0.00006104003,0.0002874597,0.0004414124,0.0001481781,0.0004369193],"domain_scores_gemma":[0.9992136,0.0000447982,0.00008433418,0.0003007751,0.0001020195,0.0002544923],"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":[0.0003117661,0.0002636213,0.0003370209,0.00001148799,0.0001896443,0.000003280488,0.001774281,0.1084473,0.5049858,0.003283507,0.0005288977,0.3798633],"study_design_scores_gemma":[0.0005240719,0.0001056168,0.0000220235,0.00004285786,0.00004837326,0.000007278406,0.0004030999,0.9421964,0.05156077,0.0008646425,0.003791407,0.0004334887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5193979,0.00004899058,0.4742177,0.000655673,0.0009288404,0.0001926284,0.00002104444,0.00006587123,0.004471316],"genre_scores_gemma":[0.4263968,0.000001655786,0.5687406,0.0003062029,0.003590868,0.000007463177,0.00001263315,0.00003090712,0.0009128803],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8337491,"threshold_uncertainty_score":0.9003391,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2411414308","doi":"10.1016/j.ifacol.2015.09.711","title":"Correlation and Dependency in Multivariate Process Risk Assessment","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Copula (linguistics); Univariate; Multivariate statistics; Correlation; Computer science; Econometrics; Random variable; Dependency (UML); Statistics; Data mining; Risk analysis (engineering); Mathematics; Machine learning; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01124478628951955,"gpt":0.2660532574443239,"spread":0.2548084711548044,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002300887,0.0001208162,0.0001548243,0.00007916619,0.00002891925,0.00003052326,0.00005045387,0.00008820798,0.00001411907],"category_scores_gemma":[0.00006045257,0.0001124764,0.00001983896,0.0001374587,0.000009762156,0.0001663274,0.000008486319,0.000211617,0.00002323604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008986461,"about_ca_system_score_gemma":0.00002431129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670388,"about_ca_topic_score_gemma":0.0005291453,"domain_scores_codex":[0.9992889,0.00004262701,0.0002038322,0.000151358,0.0001586607,0.0001546038],"domain_scores_gemma":[0.9997015,0.00002947538,0.00003876554,0.00009478667,0.00003858997,0.0000968958],"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":[0.0001548754,0.0002382875,0.2211182,0.000258556,0.0001680629,0.00006170808,0.008183748,0.6291329,0.009056618,0.0002361228,0.00001930633,0.1313716],"study_design_scores_gemma":[0.001605833,0.00004244113,0.0298782,0.00002860147,0.00001155223,0.00001084436,0.0008027837,0.9670996,0.00004986878,0.0001068711,0.0002166449,0.000146734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824148,0.0004427344,0.0114673,0.0001068288,0.0006524468,0.000310454,0.0000180761,0.000269672,0.004317652],"genre_scores_gemma":[0.9940214,0.00002803679,0.00563246,0.00001811242,0.00009291423,0.00003196224,0.000009821711,0.00001907407,0.0001461859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3379667,"threshold_uncertainty_score":0.4586653,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2244784720","doi":"10.1016/j.ifacol.2015.10.271","title":"Linear Parameter Varying Adaptive Control of an Unmanned Surface Vehicle","year":2015,"lang":"ko","type":"article","venue":"IFAC-PapersOnLine","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Adaptive control; Computer science; Controller (irrigation); Scheduling (production processes); Gain scheduling; Variation (astronomy); Estimation theory; Control engineering; Control (management); Engineering; Mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.03549644638589464,"gpt":0.2596095572568766,"spread":0.2241131108709819,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001178983,0.0009854406,0.00180475,0.0002120276,0.0001194271,0.00007729162,0.000788016,0.0006334302,0.0001141327],"category_scores_gemma":[0.0006417756,0.001000068,0.0004410975,0.0005584788,0.0002711033,0.0007908195,0.0001296144,0.0009091481,0.0004225276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004031633,"about_ca_system_score_gemma":0.0003216901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005239322,"about_ca_topic_score_gemma":0.0001231599,"domain_scores_codex":[0.9947944,0.0005675861,0.001474161,0.0009419954,0.001034288,0.001187534],"domain_scores_gemma":[0.9957037,0.0007804466,0.0005537657,0.001130707,0.0008791723,0.0009521893],"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":[0.004369862,0.00150925,0.005572638,0.0004846044,0.002904449,0.0005454667,0.006494647,0.8790784,0.08895787,0.00029448,0.00004057075,0.00974779],"study_design_scores_gemma":[0.009583763,0.001854537,0.0009863224,0.0003606764,0.0004127876,0.00003556022,0.00159864,0.9803206,0.003145663,0.00005417816,0.0006023878,0.001044908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9410301,0.005800628,0.04557558,0.0008300737,0.002009695,0.001638693,0.001416839,0.0005313973,0.00116699],"genre_scores_gemma":[0.8243565,0.00003759155,0.173154,0.0002073544,0.001371159,0.00001604492,0.00009639101,0.0002445491,0.0005163942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1275784,"threshold_uncertainty_score":0.999245,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2765099665","doi":"10.1016/j.ifacol.2017.08.2586","title":"Comparison of Two Basic Statistics for Fault Detection and Process Monitoring","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":18,"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":"Statistic; Statistics; Fault detection and isolation; Constant false alarm rate; False alarm; Fault (geology); Scan statistic; Computer science; Mathematics; Data mining; Pattern recognition (psychology); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02657885239887017,"gpt":0.3392886313855916,"spread":0.3127097789867215,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008794739,0.0001226528,0.0002462423,0.00004328338,0.0001863143,0.00005914637,0.000101237,0.00006057455,0.000003777625],"category_scores_gemma":[0.00008246108,0.0001215792,0.00003257137,0.00002849407,0.00003324332,0.0001126645,0.00000951905,0.00009828033,0.00000257108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002646016,"about_ca_system_score_gemma":0.000006992125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006000577,"about_ca_topic_score_gemma":0.0001980701,"domain_scores_codex":[0.9993588,0.000008088581,0.0002300597,0.0001321289,0.0001162854,0.0001545804],"domain_scores_gemma":[0.9995276,0.00005076537,0.0001049675,0.0001827966,0.00007695116,0.00005695385],"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":[0.0001699578,0.00009425794,0.02853632,0.001556588,0.0002220232,0.00000299948,0.002042914,0.02599904,0.4802907,0.00009686162,0.00000875861,0.4609796],"study_design_scores_gemma":[0.001629789,0.0001326722,0.006119235,0.00008142663,0.0000476014,0.000005015042,0.000689408,0.9121999,0.07837922,0.0000619038,0.0004520752,0.0002018166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498566,0.0003187894,0.0479902,0.00002813488,0.001015875,0.0003105469,0.000103968,0.0001317671,0.000244102],"genre_scores_gemma":[0.9860575,0.00001577024,0.01345524,0.000002636917,0.000306026,0.00004344284,0.000004327836,0.00002518159,0.00008989292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8862008,"threshold_uncertainty_score":0.4957857,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4289878074","doi":"10.1016/j.ifacol.2022.07.466","title":"LSTM-based model predictive control with discrete actuators for irrigation scheduling","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":17,"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":"","keywords":"Irrigation scheduling; Computer science; Model predictive control; Actuator; Scheduling (production processes); Irrigation; Homogeneous; Mathematical optimization; Low-flow irrigation systems; Agricultural engineering; Water conservation; Control (management); Engineering; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01548531763665134,"gpt":0.2248587102590748,"spread":0.2093733926224234,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002900813,0.0001437051,0.0001438086,0.00001595916,0.0005848014,0.00006290226,0.0001762317,0.00003147887,0.0002200256],"category_scores_gemma":[0.00002449086,0.00005752757,0.00008085215,0.0001759644,0.00003300019,0.0002188979,0.00003998062,0.0001291176,0.000003568797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006370974,"about_ca_system_score_gemma":0.0000205429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005997037,"about_ca_topic_score_gemma":0.0001170897,"domain_scores_codex":[0.9988962,0.00006031714,0.0001743039,0.0003137293,0.0003153933,0.0002400842],"domain_scores_gemma":[0.9994802,0.0001496976,0.0001694064,0.00005784645,0.00007143359,0.00007136349],"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":[0.002521141,0.0004105684,0.002312622,0.00003786523,0.0001917113,0.000007310162,0.0005500474,0.9393866,0.02307326,0.004074687,0.00002941462,0.02740474],"study_design_scores_gemma":[0.001225166,0.001011054,0.001266963,0.00001039656,0.00008963606,0.000001191394,0.001298297,0.9911252,0.000343753,0.0008313598,0.002572793,0.0002241356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8852084,0.00004291761,0.08411454,0.02645002,0.0001766584,0.001699759,0.001196014,0.0002022635,0.0009094793],"genre_scores_gemma":[0.9557156,0.000001396689,0.04114317,0.001717117,0.0001344427,0.0002974213,0.0006131678,0.000002676141,0.0003750041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07050725,"threshold_uncertainty_score":0.4497878,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2188495923","doi":"10.1016/j.ifacol.2015.09.580","title":"Multiple oscillations detection in control loops by using the DFT and Raleigh distribution ★ ★This work was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada; the National Natural Science Foundation of China [61174161, 61304141, 61375077]; the specialized Research Fund for the Doctoral Program of Higher Education of China [20130121130004]; and the Fundamental Research Funds for the Central Universities in China [201212G005].","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Control Systems and Identification","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"","keywords":"Work (physics); Distribution (mathematics); Engineering research; Computer science; SIGNAL (programming language); Oscillation (cell signaling); Fast Fourier transform; Engineering; Algorithm; Telecommunications; Mathematics; Mathematical analysis; Mechanical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.08353592221469229,"gpt":0.343687302684646,"spread":0.2601513804699537,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01308766,0.000146067,0.0002164695,0.0001400468,0.001401193,0.0002185615,0.0005044975,0.00006077544,0.000005426124],"category_scores_gemma":[0.001231526,0.00006611407,0.00004954835,0.00144718,0.002639704,0.0003504972,0.00009535821,0.0004453579,3.523931e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001013763,"about_ca_system_score_gemma":0.001455736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07276137,"about_ca_topic_score_gemma":0.05059777,"domain_scores_codex":[0.9966251,0.0004682853,0.000447716,0.0002462162,0.001744983,0.0004676624],"domain_scores_gemma":[0.9953564,0.002927556,0.0001743323,0.0002384612,0.001257952,0.00004526012],"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":[0.01295199,0.00126312,0.05434297,0.001601068,0.00130685,8.161505e-7,0.1174928,0.07678207,0.6092496,0.05079068,0.009713962,0.06450411],"study_design_scores_gemma":[0.002843086,0.0001363708,0.3177894,0.0001097755,0.00004736292,0.000005580168,0.01389686,0.659879,0.001063818,0.0002119436,0.003885307,0.0001314227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859659,0.004697077,0.0001508754,0.005414587,0.0004493206,0.003047101,0.0002191171,0.000007944832,0.0000480928],"genre_scores_gemma":[0.9992465,0.00009665608,0.00008985921,0.000006372014,0.0001465592,0.0001595483,0.00003476532,0.00001125875,0.0002084263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6081858,"threshold_uncertainty_score":0.9998989,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2477285746","doi":"10.1016/j.ifacol.2015.09.120","title":"Establishing Multivariate Specification Regions for Raw Materials using SMB-PLS","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Alcoa (Canada); Université Laval","funders":"","keywords":"Raw material; Multivariate statistics; Process (computing); Process engineering; Computer science; Block (permutation group theory); Raw data; Quality (philosophy); Multivariate analysis; Product (mathematics); Final product; Reliability engineering; Mathematics; Engineering; Machine learning; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.1269965263534115,"gpt":0.3060360324684559,"spread":0.1790395061150444,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003770668,0.0002100746,0.0002529351,0.0001120413,0.0001362939,0.0002011129,0.0001685568,0.000124801,0.00002768672],"category_scores_gemma":[0.0002453131,0.0002034757,0.00005228899,0.0001916642,0.00002553637,0.0004364804,0.00002531567,0.0001192222,0.0000214673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368113,"about_ca_system_score_gemma":0.00003667427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001198201,"about_ca_topic_score_gemma":0.00002253248,"domain_scores_codex":[0.9988834,0.00002544076,0.0003245102,0.0002519887,0.0001595424,0.0003550719],"domain_scores_gemma":[0.9993525,0.0000810503,0.00008285826,0.0002284149,0.0001050217,0.0001501716],"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":[0.00005403097,0.00004789171,0.00005164232,0.0001853726,0.0000558585,0.000006358535,0.002147973,0.08130619,0.9116628,0.001378299,0.0004068628,0.002696783],"study_design_scores_gemma":[0.004826334,0.0001427149,0.0005554612,0.0007829098,0.000238726,0.00009188645,0.002710239,0.8119097,0.1585942,0.003402874,0.01482092,0.001924031],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.845583,0.0004286183,0.1495145,0.0003670012,0.001788631,0.0004311978,0.0001480045,0.0006613646,0.001077708],"genre_scores_gemma":[0.6791971,0.00001740073,0.3182341,0.00006564993,0.00145884,0.00002357595,0.0002477683,0.00008965422,0.0006659695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7530685,"threshold_uncertainty_score":0.8297496,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2765222065","doi":"10.1016/j.ifacol.2017.08.065","title":"A low-cost non-invasive slag detection system for continuous casting","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"St. Thomas University","keywords":"Tundish; Ladle; Continuous casting; Outflow; Casting; Slag (welding); Process (computing); Computer science; Unit operation; Engineering; Microcontroller; Mechanical engineering; Process engineering; Materials science; Nozzle; Metallurgy; Computer hardware","retraction":null,"screen_n_in":null,"score":{"opus":0.01204061730903144,"gpt":0.2295979771145014,"spread":0.21755735980547,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001494549,0.0002310212,0.0003366059,0.00004215372,0.0003673939,0.0001419366,0.0002688881,0.0001394732,0.00001519895],"category_scores_gemma":[0.0001865022,0.0002055457,0.0001412028,0.00004687976,0.00003734527,0.0001720315,0.00003836178,0.0001657711,0.00004470984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009654847,"about_ca_system_score_gemma":0.00001825944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004637286,"about_ca_topic_score_gemma":0.0002889612,"domain_scores_codex":[0.9990057,0.000007699338,0.0002570564,0.0002478193,0.0001276686,0.0003540665],"domain_scores_gemma":[0.9991986,0.0001045363,0.0001260774,0.0003595664,0.00009758188,0.0001136462],"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":[0.0002964256,0.000167304,0.0001644874,0.007842089,0.0006313769,0.0002499568,0.001085225,0.05926531,0.6914439,0.0005932925,0.000006479845,0.2382542],"study_design_scores_gemma":[0.00108141,0.00006393655,0.000247894,0.0002803603,0.00006705754,0.00004661565,0.0003196244,0.9807069,0.01645055,0.00003049732,0.0003652604,0.0003399041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6971729,0.0001218296,0.2953107,0.00005208901,0.001162254,0.000678916,0.0001068904,0.0003596348,0.005034826],"genre_scores_gemma":[0.9860371,0.000026533,0.01298585,0.00001766901,0.0005141606,0.00008139189,0.00002476247,0.00006425501,0.0002483263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9214416,"threshold_uncertainty_score":0.838191,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2611125885","doi":"10.1016/j.ifacol.2017.08.774","title":"Interval Observer Approach to Output Stabilization of Linear Impulsive Systems","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Control theory (sociology); Observer (physics); Fault detection and isolation; Linear system; Interval (graph theory); Computer science; Linear matrix inequality; Dwell time; Mathematics; Control (management); Mathematical optimization; Actuator; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02448449845626277,"gpt":0.249637080100147,"spread":0.2251525816438842,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001823573,0.0001922527,0.0003681678,0.0000803465,0.0001202628,0.00007954604,0.0003287636,0.0001201355,0.00001212931],"category_scores_gemma":[0.0001187693,0.0001756375,0.0001117756,0.00008256646,0.00003156517,0.0001741768,0.00004824507,0.0001283806,0.00005641078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007612808,"about_ca_system_score_gemma":0.00001419448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002984784,"about_ca_topic_score_gemma":0.00006934457,"domain_scores_codex":[0.998902,0.00003508335,0.0003839565,0.0002262328,0.0002251573,0.0002276347],"domain_scores_gemma":[0.9990484,0.00002178766,0.0001181647,0.000566466,0.0001212797,0.0001239339],"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":[0.0003517757,0.000536032,0.01190272,0.003006578,0.0009434795,0.00001957119,0.009042418,0.7733278,0.1634789,0.001145507,0.0003453307,0.03589984],"study_design_scores_gemma":[0.0009807224,0.0001076587,0.005589277,0.0001376543,0.00003398637,0.00001181691,0.001357446,0.9855807,0.001715846,0.000002754735,0.004164992,0.0003170812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.955048,0.0004434913,0.0307897,0.0001400035,0.002619714,0.000916903,0.0001469287,0.0003737907,0.009521444],"genre_scores_gemma":[0.9920406,0.00001130639,0.006420961,0.00002629216,0.0004032219,0.00004740871,0.00002544731,0.00004401748,0.0009807321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.212253,"threshold_uncertainty_score":0.7162291,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2542338965","doi":"10.1016/j.ifacol.2016.07.920","title":"Identifiability of dynamic networks with part of the nodes noise-free","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Control Systems and Identification","field":"Engineering","cited_by":16,"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":"","keywords":"Identifiability; Node (physics); Noise (video); Identification (biology); Process (computing); Computer science; SIGNAL (programming language); Network topology; Rank (graph theory); Topology (electrical circuits); Control theory (sociology); Mathematics; Artificial intelligence; Machine learning; Engineering; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.003596081775230191,"gpt":0.1722804678513561,"spread":0.1686843860761259,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002034923,0.0001123383,0.0002124403,0.00002666442,0.00002865356,0.000009154072,0.0002708301,0.00005819146,0.00006049022],"category_scores_gemma":[0.0000615364,0.0000593206,0.00008763233,0.0001430838,0.00008994011,0.00008655173,0.00003390036,0.00005945713,0.000005218447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004338816,"about_ca_system_score_gemma":0.00001349756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009445101,"about_ca_topic_score_gemma":0.000879572,"domain_scores_codex":[0.9991674,0.0000321531,0.0003276654,0.0001462295,0.000180986,0.0001455943],"domain_scores_gemma":[0.9990001,0.00007278137,0.0001086962,0.0006966979,0.00009064317,0.00003103226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001198348,0.0001831965,0.03801281,0.0005369894,0.0003447043,0.000001386349,0.000563757,0.02108885,0.8856241,0.0002857826,0.0001794312,0.05305918],"study_design_scores_gemma":[0.004566892,0.0001342748,0.6915796,0.001563044,0.0002946969,0.00001431238,0.0005187463,0.2836923,0.0149008,0.0003684095,0.001609634,0.0007572549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914807,0.000407055,0.006533815,0.0003693676,0.0004401775,0.0002634992,0.0001244968,0.00006494553,0.0003159242],"genre_scores_gemma":[0.9977198,0.00003569444,0.001317681,0.000005241293,0.00007394087,0.00001423184,0.000005274291,0.0000194719,0.0008087017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8707232,"threshold_uncertainty_score":0.2419024,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1659849417","doi":"10.1016/j.ifacol.2015.06.124","title":"Quality, Reliability, Maintenance Issues in Closed-Loop Supply Chains: A Review","year":2015,"lang":"en","type":"review","venue":"IFAC-PapersOnLine","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Remanufacturing; Warranty; Reliability (semiconductor); Quality (philosophy); Supply chain; Variety (cybernetics); Risk analysis (engineering); Computer science; Reverse logistics; Closed loop; Preventive maintenance; Reliability engineering; Work (physics); Business; Process management; Operations management; Manufacturing engineering; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.06002811476704775,"gpt":0.3633985135383215,"spread":0.3033703987712738,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.007415866,0.001661742,0.005346175,0.001198828,0.0001639124,0.0004512916,0.002255255,0.0005817425,0.001041728],"category_scores_gemma":[0.003193487,0.001395462,0.001132745,0.003400221,0.0002424088,0.001235025,0.00194234,0.001283335,0.001877689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176007,"about_ca_system_score_gemma":0.0004377495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002825245,"about_ca_topic_score_gemma":0.0008275135,"domain_scores_codex":[0.9914858,0.0003908828,0.00289015,0.002030495,0.00152873,0.001673907],"domain_scores_gemma":[0.9947548,0.0002909583,0.001723823,0.00230449,0.0008281358,0.00009779283],"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":[0.00002007275,0.0003635114,0.0001314873,0.2732822,0.0001252495,0.0003319045,0.00003877691,0.000008623372,6.630972e-8,0.004019903,0.01665638,0.7050218],"study_design_scores_gemma":[0.0007642463,0.00002437248,0.00002761603,0.06455567,0.0007135093,0.00001011739,0.0004193836,0.0001423544,1.527258e-8,0.0009350103,0.9309608,0.001446862],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000008995223,0.9733595,0.00002348581,0.01011654,0.001059545,0.005787927,0.00009304158,0.0004397641,0.009111215],"genre_scores_gemma":[0.000001163376,0.9583344,0.005596161,0.006757644,0.002759689,0.0009179736,0.001609148,0.0002958004,0.02372802],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9143045,"threshold_uncertainty_score":0.9998714,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2182630508","doi":"10.1016/j.ifacol.2015.09.009","title":"Monitoring Safety of Process Operations Using Industrial Workflows","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":16,"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":"","keywords":"Workflow; Computer science; Process (computing); Process mining; Event (particle physics); Workflow technology; Workflow management system; Work in process; Software engineering; Reliability engineering; Systems engineering; Business process; Engineering; Database; Business process management; Operations management; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.124902049996885,"gpt":0.3031483248072538,"spread":0.1782462748103688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003677719,0.0002333123,0.000382188,0.0002835912,0.0002163588,0.0001774202,0.0002916572,0.0001461748,0.00005752714],"category_scores_gemma":[0.0003333579,0.0002101344,0.0001066953,0.001242161,0.00005888825,0.001172976,0.00009858159,0.000217464,0.00002847073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004790673,"about_ca_system_score_gemma":0.0001559317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001031786,"about_ca_topic_score_gemma":0.00006683798,"domain_scores_codex":[0.9984152,0.00001076924,0.000499129,0.000326955,0.0004515948,0.0002962935],"domain_scores_gemma":[0.998717,0.00001753246,0.0002029803,0.0002385664,0.00078787,0.00003602858],"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":[0.0003738127,0.0005517028,0.1032401,0.0003714357,0.0002606705,0.00001776277,0.0007111186,0.8407063,0.003845207,0.0004993631,0.0000210203,0.0494015],"study_design_scores_gemma":[0.002789752,0.00001762027,0.0005225029,0.0006844641,0.0005446466,0.000004561421,0.003566125,0.9887983,0.0007942739,0.0004268185,0.001124753,0.0007261566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918186,0.0003164707,0.004864164,0.0008844809,0.0006537894,0.0001714119,0.000009414473,0.0001422687,0.001139404],"genre_scores_gemma":[0.97326,0.00001393969,0.0221702,0.0001423894,0.004155494,0.000009152252,0.00004946483,0.00003969764,0.0001596339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.148092,"threshold_uncertainty_score":0.8569034,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897747592","doi":"10.1016/j.ifacol.2018.09.399","title":"Three-Phases Dynamic Modelling of Column Flotation Process","year":2018,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":15,"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":"","keywords":"Discretization; Nonlinear system; Partial differential equation; Discrete system; Applied mathematics; Mathematics; Transformation (genetics); Hyperbolic partial differential equation; Continuous modelling; Discrete modelling; Mathematical analysis; Algorithm; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02553239702314134,"gpt":0.2990261788845435,"spread":0.2734937818614022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001295458,0.0001129088,0.0001351247,0.00004164831,0.0001002614,0.00001579984,0.0001428934,0.00005743511,0.00272823],"category_scores_gemma":[0.0000267947,0.0001060897,0.00004095223,0.0002428266,0.000188976,0.0002273006,0.00002434561,0.00005730779,0.0001396394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004557662,"about_ca_system_score_gemma":0.00001420102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002480707,"about_ca_topic_score_gemma":0.001431319,"domain_scores_codex":[0.9990579,0.00001652634,0.0002672972,0.0002334012,0.0002746715,0.0001502101],"domain_scores_gemma":[0.9995869,0.00002466706,0.0001256829,0.0001559463,0.00005016087,0.00005662315],"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":[0.0003022138,0.0009392058,0.01216849,0.0001060847,0.00005671088,0.000007104581,0.008527947,0.05477589,0.852083,0.000809842,0.0006546648,0.06956884],"study_design_scores_gemma":[0.0003195456,0.0002310669,0.00144622,0.00002334226,0.00001359564,0.000003179221,0.0001529181,0.9468079,0.04897069,0.001433711,0.0004107706,0.0001870144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8474556,0.00002372881,0.1474741,0.0002423889,0.00005703726,0.0002386769,0.0000198567,0.0001134471,0.00437521],"genre_scores_gemma":[0.8445865,0.00001621851,0.1542687,0.0002281341,0.0000465526,0.00001933966,0.00004674364,0.00001318693,0.0007746118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8920321,"threshold_uncertainty_score":0.9981834,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2776786319","doi":"10.1016/j.ifacol.2017.08.771","title":"Conditions for handling confounding variables in dynamic networks","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Control Systems and Identification","field":"Engineering","cited_by":15,"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":"","keywords":"Confounding; Identification (biology); Computer science; Transfer function; Focus (optics); Function (biology); Variable (mathematics); Econometrics; Mathematics; Statistics; Engineering; Biology; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.01164361818885412,"gpt":0.2767457518290785,"spread":0.2651021336402243,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002273532,0.0001148142,0.0001947091,0.00006917775,0.0002840747,0.00020197,0.0001661327,0.000088145,0.00002851919],"category_scores_gemma":[0.00009806469,0.0001223531,0.00005950997,0.00003845627,0.0000246477,0.0002208322,0.0000140232,0.0001019374,0.000009941253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008566395,"about_ca_system_score_gemma":0.00001170818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001387739,"about_ca_topic_score_gemma":0.001501011,"domain_scores_codex":[0.9992971,0.00000896364,0.0002410154,0.0001569393,0.00006300393,0.0002329467],"domain_scores_gemma":[0.999465,0.00008646456,0.00007193229,0.000294764,0.00003822467,0.00004356645],"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":[0.00008261505,0.0001598608,0.01143786,0.000692677,0.0004189341,0.00002304931,0.001504834,0.6135558,0.3269439,0.01057231,0.0001806601,0.03442753],"study_design_scores_gemma":[0.0008542798,0.000009366813,0.01498653,0.0001283008,0.00002067498,0.000002774463,0.0001034072,0.982487,0.00004859079,0.0001810178,0.001025027,0.0001530544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7997718,0.001397469,0.1894393,0.000661489,0.00380317,0.00119523,0.0002129421,0.0003635293,0.003155089],"genre_scores_gemma":[0.9928133,0.00006129684,0.005979287,0.000015123,0.0002811919,0.00009252234,0.0001409247,0.00002731103,0.0005890434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3689312,"threshold_uncertainty_score":0.4989414,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2525405294","doi":"10.1016/j.ifacol.2016.07.278","title":"Energy management of a microgrid via parametric programming","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Photovoltaic system; Computer science; Mathematical optimization; Renewable energy; Energy management; Integer programming; Wind power; Energy management system; Parametric statistics; Energy storage; Distributed generation; Turbine; Grid; Energy (signal processing); Engineering; Power (physics); Algorithm; Mathematics; Electrical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.003966519761118728,"gpt":0.1762846352977404,"spread":0.1723181155366217,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007100091,0.0001664631,0.00020014,0.0001442358,0.00002542321,0.00001381278,0.0001457677,0.00006767605,0.00009035991],"category_scores_gemma":[0.00000427782,0.000122184,0.00009132063,0.0003738108,0.00003087683,0.00008590375,0.00003060951,0.00004208133,0.00002159594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004679916,"about_ca_system_score_gemma":0.000004822181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001395905,"about_ca_topic_score_gemma":0.00001025205,"domain_scores_codex":[0.9991191,0.0000121986,0.0002650161,0.0001813944,0.0001383457,0.0002839659],"domain_scores_gemma":[0.9996009,0.00003137944,0.00005040037,0.0002093732,0.00004137439,0.00006653598],"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":[0.00001649219,0.00005569281,0.0001964107,0.00008315538,0.0001487901,0.00001144319,0.00002619769,0.001963847,0.02135582,0.0001143941,0.00001213202,0.9760156],"study_design_scores_gemma":[0.01650843,0.0009098004,0.006057502,0.001688637,0.0009851636,0.0001314251,0.0004247974,0.5010558,0.1539615,0.0004627881,0.3141519,0.003662282],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1611895,0.02606369,0.8058147,0.0009395546,0.001218953,0.000882453,0.0001094825,0.001422654,0.002359018],"genre_scores_gemma":[0.4774615,0.004908401,0.5167005,0.00006073717,0.0001894946,0.00006005798,0.00003661995,0.00006569003,0.0005170109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9723533,"threshold_uncertainty_score":0.4982519,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3203993587","doi":"10.1016/j.ifacol.2021.11.207","title":"Input-output Data-driven Modeling and MIMO Predictive Control of an RCCI Engine Combustion","year":2021,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":15,"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":"","keywords":"Model predictive control; Combustion; Computer science; Controller (irrigation); Control theory (sociology); State-space representation; Automotive engineering; Control (management); Engineering; Algorithm; Chemistry; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.0240641195560804,"gpt":0.2605688454654045,"spread":0.2365047259093241,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001168134,0.0002617158,0.0004337638,0.0001106492,0.00005439418,0.00001568197,0.0003712532,0.0002007376,0.00002860637],"category_scores_gemma":[0.0006492888,0.0002677096,0.00004864742,0.0002746432,0.00008126639,0.0004383574,0.0002553367,0.0004238161,0.000003520339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005930817,"about_ca_system_score_gemma":0.00004095571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001261787,"about_ca_topic_score_gemma":0.000008370751,"domain_scores_codex":[0.9984913,0.0000303801,0.0003936359,0.000534175,0.0002485291,0.0003019563],"domain_scores_gemma":[0.9986162,0.0001396276,0.00009940617,0.0008216099,0.0002111099,0.0001120728],"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":[0.00004930351,0.0001033365,0.00006664982,0.00006878197,0.00008993655,0.00002303838,0.000106421,0.9348797,0.05390442,0.0003871752,0.000001505756,0.01031968],"study_design_scores_gemma":[0.001446279,0.00008809366,0.00005996369,0.00009241737,0.00009283017,0.00002959693,0.0005242149,0.9864311,0.01074666,0.0001770364,0.00006279191,0.0002490153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2606553,0.0007062508,0.7368526,0.000457856,0.00009822772,0.0001492592,0.0004267238,0.0005898185,0.00006396131],"genre_scores_gemma":[0.7279597,0.0001202961,0.2711844,0.00004935454,0.00009713805,0.000009846708,0.0004820656,0.00003665641,0.00006058042],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4673044,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2548873026","doi":"10.1016/j.ifacol.2016.10.364","title":"Remote-state estimation with packet drop","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Estimator; Markov process; Network packet; Computer science; Markov chain; Transmitter; Transmission (telecommunications); State (computer science); Markov model; Channel (broadcasting); Estimation; Real-time computing; Algorithm; Mathematics; Telecommunications; Computer network; Statistics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005326008142910765,"gpt":0.1844100145725955,"spread":0.1790840064296847,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001427195,0.0001852126,0.0002214467,0.00004840327,0.00004533335,0.0000262811,0.0001199825,0.00006381498,0.00008631745],"category_scores_gemma":[0.00005621634,0.0001141032,0.00005169642,0.0001225358,0.00005157171,0.0001813642,0.00000961349,0.00008026782,0.0001621399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009863533,"about_ca_system_score_gemma":0.00002186355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000560658,"about_ca_topic_score_gemma":0.0001782017,"domain_scores_codex":[0.9990613,0.00002619772,0.0002199478,0.0002031792,0.0002084548,0.0002809427],"domain_scores_gemma":[0.9993849,0.0001267886,0.000037489,0.0003018125,0.0000531892,0.00009580483],"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":[0.0003082482,0.0000668268,0.00184475,0.0002401672,0.0002505168,0.00006067551,0.00136788,0.02837466,0.08701409,0.0001474333,0.0000840509,0.8802407],"study_design_scores_gemma":[0.005888877,0.0005234235,0.005200936,0.0008051511,0.00009451633,0.00008153565,0.0003556436,0.9693689,0.00809325,0.001535215,0.006777248,0.001275282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5941243,0.0004511294,0.3951404,0.002690824,0.0004629696,0.0004820322,0.0001090296,0.001006137,0.005533149],"genre_scores_gemma":[0.9262465,0.00003675467,0.07250249,0.00008080239,0.0001314256,0.00001006513,0.00001227103,0.00004255003,0.0009371482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9409943,"threshold_uncertainty_score":0.4652992,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312831283","doi":"10.1016/j.ifacol.2022.09.599","title":"An overview on olive oil waste valorization scenarios: Life Cycle Approach","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Olive oil; Environmental science; Life-cycle assessment; Agriculture; Mediterranean Basin; Waste management; Mediterranean climate; Production (economics); Engineering; Geography; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.0335191939584138,"gpt":0.2568315252285691,"spread":0.2233123312701553,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003312989,0.0001819492,0.0002106738,0.00002125342,0.0006384313,0.00005712977,0.0003010291,0.0000657505,0.0008851499],"category_scores_gemma":[0.00007492473,0.00008266456,0.0001257426,0.0005522659,0.00005472961,0.000156598,0.00009440113,0.0002464539,0.00001295057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001284205,"about_ca_system_score_gemma":0.00003385182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000247883,"about_ca_topic_score_gemma":0.00005143441,"domain_scores_codex":[0.9982367,0.0003054945,0.0002329001,0.0004892422,0.0004245792,0.0003110432],"domain_scores_gemma":[0.9994346,0.00005084591,0.00009414935,0.0001337765,0.00007724867,0.0002094062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006496799,0.005475916,0.001484195,0.0002686523,0.00009130861,0.00001795498,0.002716752,0.05861609,0.05659408,0.005188404,0.0001608992,0.8687361],"study_design_scores_gemma":[0.004060965,0.0150088,0.04369253,0.0001430354,0.0002189152,0.0001536129,0.6019565,0.2180629,0.001480051,0.00181363,0.1092728,0.004136357],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940218,0.0004941475,0.000003197223,0.002971674,0.0002736884,0.0001686124,0.0001157654,0.0001373861,0.001813685],"genre_scores_gemma":[0.9937223,0.0002438154,0.001583464,0.001749734,0.0007417533,0.00006370877,0.0006366293,0.000003388253,0.001255252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8645997,"threshold_uncertainty_score":0.9691771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312942651","doi":"10.1016/j.ifacol.2022.09.555","title":"Selective maintenance optimization: a condensed critical review and future research directions","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Component (thermodynamics); Computer science; Heuristic; Set (abstract data type); Field (mathematics); Operations research; Limited resources; Reliability engineering; Management science; Systems engineering; Risk analysis (engineering); Industrial engineering; Engineering; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02122800093463845,"gpt":0.2927288206122783,"spread":0.2715008196776398,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005564875,0.0001423409,0.0002361017,0.00009563052,0.0004905591,0.00003249935,0.0001199246,0.00006088785,0.0008667805],"category_scores_gemma":[0.0003467316,0.0001422064,0.00004946936,0.0008196149,0.0001388002,0.0001481338,0.00007126197,0.0006169924,0.000007660801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125968,"about_ca_system_score_gemma":0.00004983024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001285347,"about_ca_topic_score_gemma":0.000009984105,"domain_scores_codex":[0.9986699,0.0001769663,0.0002219639,0.0003016732,0.0002768264,0.0003526278],"domain_scores_gemma":[0.9991878,0.0001760275,0.00001892173,0.0002189714,0.0002968194,0.0001014623],"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":[0.0001901408,0.0006027592,0.0001382092,0.004827529,0.0002914147,0.00008623456,0.003217032,0.9235415,0.001429437,0.01680133,0.02548361,0.02339079],"study_design_scores_gemma":[0.001021076,0.0003726754,0.0002497787,0.0003558304,0.0001440796,0.0002422954,0.002509094,0.6011496,0.00009086185,0.0005599228,0.3925812,0.0007236527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.003440534,0.407978,0.0947311,0.3981145,0.005870003,0.007830204,0.001422795,0.003939027,0.0766738],"genre_scores_gemma":[0.03245948,0.30239,0.6473286,0.00839532,0.001558013,0.001920259,0.0004883328,0.0002642352,0.005195756],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5525975,"threshold_uncertainty_score":0.9490639,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}