{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":105,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":105,"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":"b7145a54d347","filters":{"venue":"Journal of Global Optimization"}},"results":[{"id":"W2151238122","doi":"10.1023/a:1012771025575","title":"A Taxonomy of Global Optimization Methods Based on Response Surfaces","year":2001,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":2137,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Waterloo; RAND Corporation","keywords":"Mathematics; Simple (philosophy); Mathematical optimization; Theme (computing); Management science; Algorithm; Computer science; Epistemology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02457143740247184,"gpt":0.3308629553278328,"spread":0.3062915179253609,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001571037,0.0002972907,0.0004971764,0.0001810352,0.0001287444,0.0001368847,0.000799797,0.0001642172,0.00005867444],"category_scores_gemma":[0.00127126,0.000279374,0.0002077432,0.0024049,0.00009403945,0.00144994,0.0001039644,0.0001663755,0.000003300867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009568722,"about_ca_system_score_gemma":0.0005603045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008947962,"about_ca_topic_score_gemma":0.000001887719,"domain_scores_codex":[0.9966089,0.0009376432,0.001040569,0.0003772885,0.0007199707,0.0003156265],"domain_scores_gemma":[0.9957034,0.0003464802,0.00161942,0.0004777747,0.001639762,0.000213166],"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":[0.001003325,0.0002723583,0.001779309,0.000005995883,0.00003628901,0.00002719645,0.00002154853,0.988131,0.00002861346,0.0007740325,0.0001056927,0.007814653],"study_design_scores_gemma":[0.001935537,0.0006608565,0.001863578,0.00007772101,0.00003270481,0.000133881,0.00003530484,0.9941744,0.000194876,0.0001663586,0.0004853376,0.0002395004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006317706,0.000131019,0.9960013,0.0008860551,0.0006548419,0.0003557107,0.00001867274,0.00007067596,0.001249946],"genre_scores_gemma":[0.04555365,0.00007953651,0.9539672,0.0002886528,0.00005985772,0.000007440524,0.000005165512,0.00001466712,0.00002384975],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04492188,"threshold_uncertainty_score":0.9999658,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1549791526","doi":"10.1023/a:1026583532263","title":"On Copositive Programming and Standard Quadratic Optimization Problems","year":2000,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":197,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Orthant; Positive-definite matrix; Semidefinite programming; Conic optimization; Cone (formal languages); Quadratically constrained quadratic program; Affine transformation; Scaling; Simplex; Relaxation (psychology); Combinatorics; Matrix (chemical analysis); Quadratic programming; Applied mathematics; Mathematical optimization; Convex optimization; Regular polygon; Pure mathematics; Algorithm; Convex set; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01776061782903075,"gpt":0.3325683721105566,"spread":0.3148077542815259,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000514227,0.0002053333,0.0003581433,0.0001123933,0.000174764,0.0001682376,0.0001495757,0.0001155085,0.0005223536],"category_scores_gemma":[0.000539711,0.0001788624,0.00007398469,0.0005967731,0.00009341521,0.0006484823,0.00002356752,0.0002194891,0.000004212012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003578758,"about_ca_system_score_gemma":0.0001366666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002130761,"about_ca_topic_score_gemma":0.000002098073,"domain_scores_codex":[0.9978933,0.0001697478,0.0007126672,0.0002062928,0.0007471355,0.0002708159],"domain_scores_gemma":[0.9981384,0.0002000501,0.0004900561,0.0001537564,0.0008334114,0.0001843244],"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":[0.0003222683,0.0001430642,0.00006329432,0.00003764547,0.00005467686,0.00001439428,0.000185094,0.980352,0.000001222014,0.003274034,0.000271184,0.01528115],"study_design_scores_gemma":[0.002428594,0.001430254,0.00003102061,0.0003448621,0.0001042844,0.0002204329,0.0002120939,0.983952,0.00003702317,0.01071918,0.0002420315,0.0002782111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003441901,0.0001592791,0.9932499,0.0004376343,0.00008417278,0.0005357256,0.00001743586,0.00004971533,0.00202423],"genre_scores_gemma":[0.0321202,0.0005030433,0.9669111,0.00009396052,0.00008824911,0.0000103606,0.00001302303,0.00003697937,0.0002230687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0286783,"threshold_uncertainty_score":0.7293797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994895518","doi":"10.1007/s10898-007-9234-1","title":"Nonsmooth optimization through Mesh Adaptive Direct Search and Variable Neighborhood Search","year":2007,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":185,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Air Force Office of Scientific Research","keywords":"Mathematics; Variable neighborhood search; Mathematical optimization; Metaheuristic; Convergence (economics); Local search (optimization); Variable (mathematics); Guided Local Search; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.02169005376408899,"gpt":0.2979204776592476,"spread":0.2762304238951586,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00328646,0.0002663189,0.0004570952,0.0002856858,0.000283322,0.000488432,0.0008627698,0.0001868971,0.0001395937],"category_scores_gemma":[0.0005651054,0.0002417758,0.000096293,0.002536157,0.0001329949,0.002229713,0.000353935,0.0003984001,0.000007668465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004574342,"about_ca_system_score_gemma":0.0006523264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000564047,"about_ca_topic_score_gemma":0.000002877318,"domain_scores_codex":[0.9960027,0.0004029568,0.0009508406,0.0004527295,0.001563759,0.0006269968],"domain_scores_gemma":[0.9962236,0.0003355058,0.0003701444,0.0004216572,0.002260257,0.000388872],"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":[0.0001184625,0.0001523266,0.0004820714,0.0000154017,0.00007907621,0.00004850242,0.0002121949,0.9687564,0.000009066946,0.02451492,0.0002632015,0.005348428],"study_design_scores_gemma":[0.001158692,0.0004556973,0.0004860624,0.00005698383,0.00003199924,0.0002329694,0.0001215003,0.9965358,0.0001357055,0.0004399988,0.0001162137,0.0002284162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001243343,0.000423672,0.9842018,0.0005950191,0.0004288334,0.0003350979,0.00001233884,0.00006215821,0.01381675],"genre_scores_gemma":[0.05963765,0.0006130883,0.9392055,0.0001792776,0.0001937348,0.000002022733,0.000008224722,0.00002274761,0.0001377971],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05951332,"threshold_uncertainty_score":0.985933,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2088855121","doi":"10.1007/s10898-004-2692-9","title":"Global Stability Results for the Weak Vector Variational Inequality","year":2005,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"National Natural Science Foundation of China","keywords":"Mathematics; Variational inequality; Stability (learning theory); Euclidean space; Applied mathematics; Euclidean geometry; Inequality; Solution set; Set (abstract data type); Vector optimization; Mathematical analysis; Vector space; Space (punctuation); Mathematical optimization; Pure mathematics; Optimization problem; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.02314939605882728,"gpt":0.2857274072162192,"spread":0.2625780111573919,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001961141,0.0001295672,0.00020596,0.00003462048,0.000222462,0.0002348718,0.0006649275,0.00007576338,0.00004544799],"category_scores_gemma":[0.001348666,0.00009101034,0.0002178757,0.0009510891,0.00002990464,0.001043245,0.00007664057,0.00007039268,0.00000428814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005568539,"about_ca_system_score_gemma":0.00037802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001744131,"about_ca_topic_score_gemma":0.00003945833,"domain_scores_codex":[0.9979175,0.0001975939,0.0008848284,0.0002120461,0.0006152854,0.0001727661],"domain_scores_gemma":[0.9968565,0.000396089,0.0008469599,0.0002905486,0.00150433,0.000105543],"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":[0.0001569915,0.0001228105,0.001222339,0.000002644636,0.00007481151,2.038285e-7,0.00004068982,0.8899126,9.116433e-7,0.1047362,0.00242778,0.001301986],"study_design_scores_gemma":[0.001142049,0.00008069861,0.02287241,0.000005685994,0.00005854732,0.00001687997,0.000017244,0.9704631,0.000004866311,0.001871719,0.003366821,0.00009998012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001656824,0.0000948843,0.9704823,0.02758462,0.0004438075,0.0001674996,0.0001294728,0.00002761484,0.0009041344],"genre_scores_gemma":[0.4213256,0.00003644578,0.5773873,0.0006853592,0.0005026707,0.000005075303,0.00002507986,0.00000336419,0.00002905068],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4211599,"threshold_uncertainty_score":0.3711294,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1965868850","doi":"10.1007/s10898-014-0185-z","title":"A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines","year":2014,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; AngloGold Ashanti","keywords":"Mathematical optimization; Open-pit mining; Benchmark (surveying); Linear programming; Scheduling (production processes); Descent (aeronautics); Computer science; Schedule; Variable (mathematics); Production planning; Mathematics; Production (economics); Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01375831141325796,"gpt":0.2672620278749107,"spread":0.2535037164616528,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007747988,0.00008675397,0.0001767042,0.000060109,0.00003030399,0.00007934187,0.0000936637,0.00004280923,0.000002931825],"category_scores_gemma":[0.0001976573,0.00008486573,0.00002547618,0.00009959803,0.000004763818,0.0002348591,0.00001568726,0.00006345013,1.001618e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365398,"about_ca_system_score_gemma":0.00002618533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000411909,"about_ca_topic_score_gemma":0.000002275971,"domain_scores_codex":[0.9993956,0.00002294308,0.000310329,0.0001009452,0.00005257689,0.0001176005],"domain_scores_gemma":[0.9996287,0.00003130647,0.0001341764,0.00007547045,0.00008775613,0.00004264039],"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":[0.00006861989,0.00003575897,0.00076123,0.00004507397,0.000008206292,3.863834e-7,0.00000935048,0.9866133,0.00003457806,0.0004177488,0.00009055831,0.01191519],"study_design_scores_gemma":[0.0005685918,0.0002079387,0.00006011903,0.0001588079,0.00001797301,0.00002000543,0.0000099677,0.9972028,0.0005014639,0.0004358593,0.0007306861,0.0000857583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01678563,0.00003488152,0.982353,0.0001590033,0.000219114,0.0002634073,0.000002345764,0.00002885065,0.0001537298],"genre_scores_gemma":[0.240834,0.00002131616,0.7589744,0.00003035646,0.0001151047,0.000008223794,0.000003685514,0.00001124228,0.000001721211],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2240484,"threshold_uncertainty_score":0.3460724,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021601290","doi":"10.1007/s10898-011-9732-z","title":"An experimental methodology for response surface optimization methods","year":2011,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Mathematical optimization; Gaussian process; Global optimization; Gaussian; Set (abstract data type); Function (biology); Dimension (graph theory); Test functions for optimization; Scaling; Surface (topology); Optimization problem; Algorithm; Computer science; Multi-swarm optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.09512033817134276,"gpt":0.4191384652855515,"spread":0.3240181271142088,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002792505,0.0002348596,0.0003985519,0.0001412109,0.0001647279,0.0000991649,0.0008133389,0.0001654262,0.00005661273],"category_scores_gemma":[0.0009168217,0.0002258655,0.0001557929,0.0007355941,0.00007372097,0.002492047,0.00009118057,0.0001230456,0.000001347759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00042685,"about_ca_system_score_gemma":0.0002404446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005097842,"about_ca_topic_score_gemma":4.71012e-7,"domain_scores_codex":[0.9966507,0.001618059,0.0007716289,0.0003721883,0.0002896202,0.0002978116],"domain_scores_gemma":[0.996714,0.0003687977,0.0009913543,0.0004031211,0.001300879,0.0002218631],"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":[0.001033713,0.0002733635,0.00005710042,0.000002867806,0.00003515154,0.000007744018,0.0006826948,0.990315,0.002439067,0.002560806,0.00003178855,0.002560695],"study_design_scores_gemma":[0.001510883,0.001297379,0.000127388,0.00001151506,0.00002792163,0.0001977511,0.000254233,0.9747539,0.02081162,0.0007052987,0.00006889735,0.0002332233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008555923,0.0002139572,0.9970936,0.0001369708,0.001067607,0.0003556933,0.000008274096,0.00008967541,0.0001785904],"genre_scores_gemma":[0.01253042,0.00003078274,0.9871235,0.0001805331,0.00007544477,0.000008376967,0.000005888873,0.00002420435,0.00002086824],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01837256,"threshold_uncertainty_score":0.9210529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999777494","doi":"10.1007/s10898-004-9971-3","title":"Comparative Assessment of Algorithms and Software for Global Optimization","year":2005,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":48,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Solver; Computer science; Software; Implementation; Stochastic programming; Mathematical optimization; Theoretical computer science; Algorithm; Software engineering; Programming language; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05312631796310618,"gpt":0.4253711833736167,"spread":0.3722448654105106,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005591136,0.0002127922,0.0005805862,0.00009052487,0.0001171802,0.00006496029,0.0002168874,0.000133706,0.00006345239],"category_scores_gemma":[0.0007921068,0.0001955347,0.0001174733,0.0006487365,0.0001100718,0.0007568196,0.00006917932,0.0001310468,3.554769e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006437447,"about_ca_system_score_gemma":0.0003327972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001915489,"about_ca_topic_score_gemma":0.000005378766,"domain_scores_codex":[0.9977674,0.0001165457,0.001001421,0.000206903,0.0006533833,0.0002543409],"domain_scores_gemma":[0.9956742,0.0002679861,0.001159094,0.0001684202,0.002561176,0.0001691178],"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":[0.0001020267,0.0002456477,0.00104853,0.0000554829,0.0001025732,0.000001444796,0.00006502911,0.9881387,0.000003107157,0.005121177,0.000655664,0.004460607],"study_design_scores_gemma":[0.00223608,0.0004021424,0.0004131438,0.00008380537,0.0001009124,0.0000759475,0.0001694162,0.9926581,0.00004625547,0.003442782,0.0001994395,0.0001720152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007604213,0.0002435477,0.9972191,0.0004199196,0.0001459542,0.0005504293,0.0001194551,0.00002917426,0.0005119383],"genre_scores_gemma":[0.01678337,0.0002168931,0.982685,0.00004737653,0.0001652029,0.00001079468,0.00002812118,0.00001782585,0.00004539346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01602295,"threshold_uncertainty_score":0.7973676,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2002285779","doi":"10.1007/s10898-006-9065-5","title":"Extremal problems for convex polygons","year":2006,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal; Polytechnique Montréal","funders":"","keywords":"Mathematics; Regular polygon; Polygon (computer graphics); Combinatorics; Convex polygon; Perimeter; Series (stratigraphy); Linear programming; Mathematical optimization; Discrete mathematics; Geometry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.009376869784567364,"gpt":0.2353780241406865,"spread":0.2260011543561192,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002389635,0.00007060033,0.0001142337,0.00006327617,0.00007868997,0.0001203424,0.0002124416,0.00004028674,0.000007037004],"category_scores_gemma":[0.00004379816,0.00006390447,0.00008332209,0.0003915719,0.00001132321,0.0005973676,0.00002291032,0.00003632909,0.000001663258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008766773,"about_ca_system_score_gemma":0.0001356359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000047181,"about_ca_topic_score_gemma":0.000003463202,"domain_scores_codex":[0.9991795,0.00002665923,0.0003531689,0.0001006662,0.0002266743,0.0001133202],"domain_scores_gemma":[0.9990119,0.00003926497,0.0003205753,0.00007853768,0.0005042017,0.00004548028],"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":[0.00001134111,0.00005706804,0.000277289,0.000004985019,0.000007987781,0.000001466467,0.0000090902,0.9452477,0.0001235869,0.04842179,0.002972484,0.002865253],"study_design_scores_gemma":[0.0007272386,0.0001946777,0.001660637,0.00001634659,0.00001417398,0.0001249993,0.000003755712,0.9818587,0.0002163408,0.01119796,0.003891222,0.00009399408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002375325,0.0002699571,0.994694,0.001230932,0.0005579142,0.0001205121,0.000004509212,0.00001939972,0.0007274481],"genre_scores_gemma":[0.4398016,0.000009172181,0.5595669,0.0001336999,0.0003636449,0.000002717351,0.00001059593,0.000003234631,0.0001084759],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4374263,"threshold_uncertainty_score":0.2605949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1606362855","doi":"10.1023/a:1011280023547","title":"Capacity and flow assignment of data networks by generalized Benders decomposition","year":2001,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Decomposition; Mathematical optimization; Flow network; Network topology; Benders' decomposition; Multi-commodity flow problem; Decomposition method (queueing theory); Flow (mathematics); Integer (computer science); Regular polygon; Measure (data warehouse); Function (biology); Integer programming; Quality of service; Computer science; Discrete mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.01915627088536034,"gpt":0.2574983124426431,"spread":0.2383420415572828,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003446168,0.00008428564,0.0001755556,0.00002415643,0.00005462149,0.00007227877,0.0004061345,0.00005663853,0.000009892291],"category_scores_gemma":[0.00001407385,0.00007511213,0.00003345304,0.0002127919,0.00002939813,0.000805995,0.00007621456,0.00007161966,2.040673e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006921168,"about_ca_system_score_gemma":0.00003960953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006537316,"about_ca_topic_score_gemma":0.000003720051,"domain_scores_codex":[0.9990258,0.0000974412,0.0003669001,0.000143049,0.0002482605,0.00011851],"domain_scores_gemma":[0.9991141,0.00003162646,0.0003885447,0.0002103784,0.0001620255,0.00009334158],"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":[0.00004161017,0.00005034938,0.0006815026,0.000001552512,0.00003579086,0.000003681235,0.00001171739,0.9040798,0.00001623508,0.0008412576,0.00384565,0.09039086],"study_design_scores_gemma":[0.0009077435,0.0000999723,0.0002971963,0.00002265131,0.00003155059,0.0001037542,0.000005348152,0.9979064,0.000005161632,0.000144762,0.0004076668,0.00006777129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005488836,0.0007802061,0.9921173,0.001154103,0.0002653328,0.00006509959,0.000008370043,0.00001266005,0.0001080803],"genre_scores_gemma":[0.7369061,0.0007357566,0.2620367,0.0001983391,0.00009852202,4.872562e-7,0.00001602956,0.000002806195,0.000005305678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7314172,"threshold_uncertainty_score":0.3062983,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2761472785","doi":"10.1007/s10898-017-0574-1","title":"Order-based error for managing ensembles of surrogates in mesh adaptive direct search","year":2017,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Benchmark (surveying); Surrogate model; Mathematical optimization; Global optimization; Computer science; Mathematics; Machine learning; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.03303527240385088,"gpt":0.3275313214449492,"spread":0.2944960490410983,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006174704,0.0001434636,0.000334861,0.0001741297,0.0001749907,0.0001336347,0.0007648171,0.00006517163,0.000004546671],"category_scores_gemma":[0.0006544403,0.0001352329,0.0001025326,0.0003983856,0.00008178558,0.001279526,0.0001066774,0.00009846432,5.154832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002620781,"about_ca_system_score_gemma":0.0002705762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003397886,"about_ca_topic_score_gemma":0.00003936321,"domain_scores_codex":[0.9985812,0.0000985443,0.0005118754,0.0002196456,0.0003615574,0.0002271795],"domain_scores_gemma":[0.9970368,0.0001595002,0.0009407116,0.000328015,0.001456082,0.00007895009],"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":[0.0001308616,0.0001026686,0.002376928,0.00001513586,0.00002395148,0.000008913058,0.00008626233,0.9901016,0.00002897728,0.001938518,0.0000186755,0.005167463],"study_design_scores_gemma":[0.001838876,0.0002614592,0.002765779,0.00012708,0.00001272035,0.0000103151,0.00007757825,0.9930339,0.001090885,0.0006439214,0.00001203618,0.0001253978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001063991,0.00008660783,0.9965624,0.0007123133,0.0002918235,0.0002755647,0.00001397812,0.00001719212,0.0009761573],"genre_scores_gemma":[0.3676151,0.00003360707,0.6322731,0.00002456834,0.00002624948,0.000003462722,0.000001736114,0.0000075713,0.0000145732],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3665511,"threshold_uncertainty_score":0.5514639,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052741439","doi":"10.1007/s10898-008-9395-6","title":"Towards global bilevel dynamic optimization","year":2009,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"National Science Foundation","keywords":"Bilevel optimization; Mathematical optimization; Mathematics; Optimization problem; Global optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.007580607459892368,"gpt":0.2645765146161052,"spread":0.2569959071562128,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003926555,0.0002034072,0.0003175402,0.0001303539,0.0001387225,0.0003299634,0.0007537715,0.0001274147,0.00009481274],"category_scores_gemma":[0.0001990393,0.0001805842,0.0002225894,0.0020424,0.00002240171,0.00171584,0.00006157891,0.0001027473,0.000009618542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006320207,"about_ca_system_score_gemma":0.0003809711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006929414,"about_ca_topic_score_gemma":0.000002473103,"domain_scores_codex":[0.9978532,0.0001115531,0.0007996222,0.0002548994,0.0007410596,0.0002396287],"domain_scores_gemma":[0.9975339,0.0000178409,0.0008063226,0.0002723089,0.001172341,0.0001972557],"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":[0.00002348946,0.0001407077,0.0002753218,0.000002044295,0.0000430714,0.000008896985,0.00002029603,0.9568381,0.000002769078,0.0306247,0.000523298,0.01149726],"study_design_scores_gemma":[0.0007006032,0.0002097842,0.005222973,0.00002111516,0.0000557157,0.0001384913,0.000009465789,0.9882883,0.000004672071,0.005021774,0.0001429938,0.000184148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001287276,0.0001445028,0.9870337,0.008689919,0.0004757027,0.0000938985,0.00001330482,0.00007340112,0.003346878],"genre_scores_gemma":[0.2184718,0.0001772687,0.7799528,0.001248078,0.00009040917,7.040827e-7,0.00001931483,0.000004472652,0.00003520533],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2183431,"threshold_uncertainty_score":0.736401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2396268331","doi":"10.1007/s10898-016-0438-0","title":"Robust optimization approximation for joint chance constrained optimization problem","year":2016,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Bounding overwatch; Robust optimization; Optimization problem; Mathematics; Convexity; Constrained optimization; Probabilistic logic; Constraint (computer-aided design); Continuous optimization; Computer science; Multi-swarm optimization; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.07599725735112603,"gpt":0.3229622976148248,"spread":0.2469650402636987,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003588921,0.0003644009,0.0006974011,0.0004708377,0.0002984985,0.0004403217,0.0006097201,0.0003024699,0.0003703189],"category_scores_gemma":[0.003819137,0.0002420033,0.0003598488,0.001702896,0.0001534985,0.002889344,0.00006530088,0.0001126188,0.00001329942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004777474,"about_ca_system_score_gemma":0.0004421776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003997789,"about_ca_topic_score_gemma":0.000003536866,"domain_scores_codex":[0.994365,0.0003200503,0.002657261,0.000559164,0.001650242,0.0004482842],"domain_scores_gemma":[0.9902455,0.0004113553,0.003748179,0.0004475221,0.004875483,0.0002719755],"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":[0.000310085,0.0001280177,0.0006898321,0.000009113653,0.00004367458,0.000002571006,0.00006628374,0.972838,0.00006985237,0.002287852,0.003086797,0.02046792],"study_design_scores_gemma":[0.002857965,0.0004317289,0.0001246957,0.000142264,0.00009061236,0.0001113941,0.0001268284,0.9916008,0.0002166739,0.00311168,0.0008577072,0.0003277238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003972564,0.000151447,0.991796,0.003645258,0.001008225,0.0009642072,0.00009760429,0.00006787724,0.00187215],"genre_scores_gemma":[0.06012144,0.001017811,0.937682,0.0001996397,0.0004834395,0.00003471872,0.00006540439,0.0000413327,0.0003541666],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05972418,"threshold_uncertainty_score":0.986861,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3033072407","doi":"10.1007/s10898-020-00949-1","title":"Advances in verification of ReLU neural networks","year":2020,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"MNIST database; Artificial neural network; Solver; Computer science; Deep neural networks; Artificial intelligence; Set (abstract data type); Integer programming; Theoretical computer science; Machine learning; Algorithm; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.008913140916029237,"gpt":0.2572706877657535,"spread":0.2483575468497242,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002061863,0.00006245042,0.0001554531,0.00003261893,0.00002120097,0.00002721518,0.0003958046,0.00004199857,0.000004461172],"category_scores_gemma":[0.0002838814,0.000058498,0.00004381062,0.0006771223,0.00001797995,0.001154005,0.00005640049,0.0001469021,3.307223e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006567222,"about_ca_system_score_gemma":0.00003947336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002379224,"about_ca_topic_score_gemma":8.686982e-7,"domain_scores_codex":[0.9990857,0.00009434023,0.0004151773,0.00009886918,0.0002176677,0.00008825189],"domain_scores_gemma":[0.9990797,0.00003308167,0.0005874507,0.00008850495,0.0001592056,0.0000520546],"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":[0.00004199199,0.00001362561,0.006269638,0.000004622392,0.000002337236,0.000005711693,0.00007903449,0.9738975,0.000006161949,0.002884942,0.00002139475,0.01677304],"study_design_scores_gemma":[0.0003553361,0.000113489,0.002615381,0.00002052977,0.000004370511,0.00001118592,0.00002077995,0.9966025,0.000007676261,0.0001180209,0.00008313691,0.0000475944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00217987,0.0005017165,0.9950491,0.001561592,0.0003031524,0.00004323424,2.636733e-7,0.000012149,0.000348903],"genre_scores_gemma":[0.8189388,0.0001656356,0.180678,0.0001194782,0.00009412353,2.238127e-7,7.209358e-7,0.000002614634,4.212771e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8167589,"threshold_uncertainty_score":0.2385479,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2944554922","doi":"10.1007/s10898-019-00782-1","title":"Preference-based evolutionary multi-objective optimization for portfolio selection: a new credibilistic model under investor preferences","year":2019,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Ministerio de Economía y Competitividad; Concordia University","keywords":"Selection (genetic algorithm); Preference; Mathematics; Portfolio; Mathematical optimization; Multi-objective optimization; Portfolio optimization; Econometrics; Machine learning; Computer science; Statistics; Business; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.04571095833041305,"gpt":0.2849508484444216,"spread":0.2392398901140086,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003254329,0.0003655432,0.0004785713,0.000304404,0.0001951618,0.0002006369,0.000706983,0.0002334515,0.00009270479],"category_scores_gemma":[0.0006317623,0.0003488804,0.0002145181,0.001336199,0.0000647502,0.002040876,0.00009171273,0.0002350585,0.000006043527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238397,"about_ca_system_score_gemma":0.002493115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001777457,"about_ca_topic_score_gemma":0.000008690998,"domain_scores_codex":[0.9972521,0.0001388733,0.0009226186,0.0005984903,0.0006948336,0.0003930521],"domain_scores_gemma":[0.9952457,0.0002121208,0.001305302,0.0003475057,0.002584541,0.0003048224],"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":[0.0001877303,0.0002385427,0.0009391078,0.00002128138,0.00006293065,0.000001041333,0.0000825839,0.9936068,0.00003087291,0.003673813,0.0004464077,0.0007088959],"study_design_scores_gemma":[0.003383405,0.00060501,0.001009733,0.00009066122,0.00006293608,0.00005165192,0.00005808036,0.9908485,0.00006846532,0.003430931,0.00002874481,0.0003618505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007295808,0.0001708433,0.9964554,0.0003296896,0.0008442341,0.0009987913,0.0000308042,0.0001149953,0.0003256043],"genre_scores_gemma":[0.0892136,0.0000395397,0.9099233,0.000301286,0.0001570561,0.00001794006,0.00003131207,0.00002801156,0.0002879517],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08848402,"threshold_uncertainty_score":0.9998963,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1965468942","doi":"10.1007/s10898-008-9371-1","title":"A new Lagrangean approach to the pooling problem","year":2008,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Heuristics; Mathematical optimization; Benchmark (surveying); Pooling; Relaxation (psychology); Nonlinear system; Upper and lower bounds; Set (abstract data type); Bilinear interpolation; Function (biology); Nonlinear programming; Applied mathematics; Computer science; Statistics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.05188978761513707,"gpt":0.332848798223235,"spread":0.280959010608098,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000464948,0.0001321029,0.0002307363,0.00008300699,0.0001955368,0.00005352538,0.0003859231,0.00006566456,0.00004571495],"category_scores_gemma":[0.0006246684,0.00008951301,0.0001013956,0.0009457144,0.00002851688,0.0003308959,0.0000662593,0.0002023579,0.00001018482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002418716,"about_ca_system_score_gemma":0.0002688756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008360797,"about_ca_topic_score_gemma":0.00000302746,"domain_scores_codex":[0.9982873,0.00009856102,0.0005320116,0.0001317133,0.0007128288,0.000237611],"domain_scores_gemma":[0.9984589,0.00008409513,0.0003739749,0.0002012941,0.0006565715,0.0002251386],"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":[0.00005797917,0.00008660834,0.0001205763,0.000009861842,0.00003226848,0.000007920647,0.0003676108,0.9757482,0.000002696487,0.003691655,0.01811683,0.001757781],"study_design_scores_gemma":[0.003523803,0.0005445738,0.0004602924,0.0001668922,0.0001415322,0.003119016,0.0007539309,0.9613593,0.00008647882,0.01746498,0.01179912,0.0005801475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003583007,0.0001279248,0.9904181,0.001488346,0.0001104692,0.000350651,0.000003853494,0.00002968088,0.007112698],"genre_scores_gemma":[0.007320197,0.0001062005,0.9914454,0.0001834562,0.0003438792,0.000003694885,0.000002505696,0.0000210393,0.000573578],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01438897,"threshold_uncertainty_score":0.3650235,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2087914194","doi":"10.1007/s10898-005-3839-z","title":"Lower Semicontinuous Regularization for Vector-Valued Mappings","year":2006,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"Conseil Régional du Limousin","keywords":"Mathematics; Regularization (linguistics); Scalar (mathematics); Limit (mathematics); Pure mathematics; Lattice (music); Vector space; Upper and lower bounds; Mathematical analysis; Geometry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.005521688878268117,"gpt":0.2223214039018633,"spread":0.2167997150235952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003653832,0.000121572,0.000216739,0.0001199987,0.0001267753,0.0002145325,0.0003662182,0.00008771919,0.00002485294],"category_scores_gemma":[0.0001365059,0.0001119213,0.000186776,0.0008592805,0.00002357986,0.0009251776,0.0000356521,0.00005235696,0.000002964522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000198576,"about_ca_system_score_gemma":0.0001356954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001017102,"about_ca_topic_score_gemma":0.000002550941,"domain_scores_codex":[0.9986271,0.00005356838,0.0006082081,0.0001734578,0.0003784595,0.0001591889],"domain_scores_gemma":[0.9977833,0.00003426283,0.0007417147,0.0001606543,0.001217581,0.00006247523],"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":[0.00002544825,0.00008467105,0.0002936825,0.000004488415,0.00003137966,0.000001914856,0.0000155138,0.824668,0.0000759305,0.1709114,0.003618781,0.0002687237],"study_design_scores_gemma":[0.0008571064,0.0001097127,0.001446443,0.00001986765,0.00005442023,0.00003623857,0.000007024312,0.9887062,0.00007990486,0.006913331,0.001633463,0.0001362966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003746603,0.00007878839,0.9951711,0.00253876,0.0006022094,0.0001306437,0.000007115661,0.00004156019,0.001055222],"genre_scores_gemma":[0.1919239,0.00001583741,0.8067144,0.0003576061,0.0003924569,0.000003709788,0.00003892653,0.000009673505,0.0005435371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1915492,"threshold_uncertainty_score":0.4564018,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1901524206","doi":"10.1007/s10898-015-0373-5","title":"On Slater’s condition and finite convergence of the Douglas–Rachford algorithm for solving convex feasibility problems in Euclidean spaces","year":2015,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Mathematics; Convergence (economics); Euclidean geometry; Context (archaeology); Projection (relational algebra); Constraint (computer-aided design); Regular polygon; Mathematical optimization; Applied mathematics; Euclidean space; Algorithm; Convex optimization; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.02642004899376784,"gpt":0.2788745590008693,"spread":0.2524545100071015,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007663554,0.00009283222,0.0002065712,0.00007914358,0.0000575464,0.0000906401,0.0002649391,0.00005650573,0.00000704843],"category_scores_gemma":[0.0003879797,0.00006729158,0.00007848578,0.0005210682,0.00004325295,0.0006436966,0.00005826841,0.00007185358,4.609148e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001401807,"about_ca_system_score_gemma":0.0001540087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002217953,"about_ca_topic_score_gemma":0.00001465393,"domain_scores_codex":[0.9988141,0.00009367245,0.0005087167,0.0001453318,0.000333051,0.0001051143],"domain_scores_gemma":[0.9982491,0.0001239096,0.0006983544,0.00013699,0.0007187323,0.00007298867],"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":[0.00002077389,0.00007551655,0.01497157,0.00001046643,0.00001989423,4.463722e-7,0.0002154509,0.9762071,0.000004765933,0.007504723,0.0001552982,0.0008139932],"study_design_scores_gemma":[0.001091187,0.0001876894,0.004656393,0.00005815316,0.00002104582,0.00000910553,0.00004963264,0.9867103,0.00004317478,0.007054619,0.00004725551,0.00007143908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008978668,0.00006537278,0.9890353,0.001197424,0.0004068623,0.0002119276,0.00001630174,0.000006966612,0.00008117582],"genre_scores_gemma":[0.7877489,0.0000423719,0.2119285,0.0002021982,0.00003969338,0.000002906475,0.000006551817,0.000003794567,0.0000251844],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7787701,"threshold_uncertainty_score":0.2744071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2079646161","doi":"10.1007/s10898-007-9270-x","title":"An inexact proximal point method for solving generalized fractional programs","year":2008,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Mathematics; Mathematical optimization; Regularization (linguistics); Rate of convergence; Parametric statistics; Convergence (economics); Applied mathematics; Regular polygon; Term (time); Computer science; Key (lock)","retraction":null,"screen_n_in":null,"score":{"opus":0.02341616659943074,"gpt":0.3095328237218821,"spread":0.2861166571224514,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006055246,0.0001323732,0.0002488598,0.0001192731,0.0002378256,0.0001728951,0.0004065667,0.00007815122,0.00004231677],"category_scores_gemma":[0.0001482158,0.0001135684,0.0002064909,0.0006772949,0.00001825283,0.001956514,0.00003240617,0.00008497088,0.000001570495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001911987,"about_ca_system_score_gemma":0.0003092823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001399967,"about_ca_topic_score_gemma":0.000002523741,"domain_scores_codex":[0.9984364,0.0001052076,0.0005890392,0.0002069566,0.0004853052,0.0001771205],"domain_scores_gemma":[0.9976349,0.00005124633,0.0006855362,0.0001662619,0.001308293,0.0001537888],"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":[0.00006221611,0.0002501747,0.001315669,0.000003746211,0.00007232754,0.00000497626,0.0000748912,0.974984,0.00004575258,0.0200803,0.0004413887,0.002664547],"study_design_scores_gemma":[0.0009548783,0.0002940065,0.001049513,0.000009058302,0.00003887266,0.0002951099,0.00001237509,0.9953681,0.0000426465,0.00139295,0.0004130158,0.0001294634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006374249,0.00004527589,0.9968643,0.001806628,0.0002733381,0.0001783846,0.000004844409,0.00004531889,0.0001444736],"genre_scores_gemma":[0.06506451,0.00003479667,0.9341482,0.0004072505,0.0002654012,0.000008079323,0.0000318748,0.000007459546,0.00003245065],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06442709,"threshold_uncertainty_score":0.4631185,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2082247794","doi":"10.1007/s10898-012-9946-8","title":"Optimization methodology assessment for the inlet velocity profile of a hydraulic turbine draft tube: part I—computer optimization techniques","year":2012,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Polytechnique Montréal","keywords":"Draft tube; Inlet; Computational fluid dynamics; Tube (container); Turbine; Flow (mathematics); Fluent; Range (aeronautics); Hull; Mechanical engineering; Mechanics; Engineering; Simulation; Marine engineering; Aerospace engineering; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02558329019184007,"gpt":0.3012648757875383,"spread":0.2756815855956982,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001419638,0.000222095,0.0004014288,0.0001348504,0.00009478789,0.00005289817,0.0002484845,0.0001705339,0.0001279541],"category_scores_gemma":[0.000208246,0.0001803341,0.0001550183,0.0005434769,0.00006088035,0.0007791611,0.00004735263,0.000178617,7.895605e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004440138,"about_ca_system_score_gemma":0.00008793204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003407754,"about_ca_topic_score_gemma":7.799402e-7,"domain_scores_codex":[0.998064,0.0001938211,0.0009688495,0.0001286727,0.0003536222,0.0002910273],"domain_scores_gemma":[0.9979482,0.0003333614,0.0006613614,0.0002125792,0.0007409049,0.0001036307],"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":[0.00005399537,0.00008064503,0.0003854307,0.00006173849,0.0001381533,3.197194e-7,0.0001592708,0.9908,0.00005130377,0.000463698,0.003182352,0.004623082],"study_design_scores_gemma":[0.0006097998,0.0002080114,0.0004900674,0.00005194028,0.0001640156,0.0000426055,0.0000563215,0.9962454,0.0006918567,0.000087341,0.00117948,0.0001732043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006409613,0.0003975236,0.995796,0.0004248263,0.001567735,0.0006786067,0.00004312671,0.00009132601,0.0003598544],"genre_scores_gemma":[0.04364925,0.0002629519,0.9551148,0.0001333418,0.0006696319,0.00004075754,0.00007780773,0.00003853997,0.00001289126],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04300829,"threshold_uncertainty_score":0.7353813,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2007576447","doi":"10.1007/s10898-005-3835-3","title":"Variational Methods in Convex Analysis","year":2006,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Subderivative; Mathematics; Convex analysis; Proper convex function; Parallels; Variational analysis; Regular polygon; Convex set; Convex conjugate; Convex combination; Convex optimization; Mathematical optimization; Applied mathematics; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.008219625034438783,"gpt":0.3067541756659409,"spread":0.2985345506315021,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008868584,0.0001007704,0.0003014012,0.0004465968,0.00005022976,0.0001495523,0.0003791091,0.00007003867,0.0001308782],"category_scores_gemma":[0.00009789326,0.00009150404,0.0002191494,0.00437513,0.00001406816,0.0008344694,0.00004406698,0.00007968814,0.000003207985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000240337,"about_ca_system_score_gemma":0.0001607337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000691993,"about_ca_topic_score_gemma":0.00002693676,"domain_scores_codex":[0.998287,0.0002371522,0.0007653728,0.0001598618,0.0004201386,0.0001304816],"domain_scores_gemma":[0.998419,0.00009877286,0.0006441909,0.0001500366,0.0006303077,0.00005764115],"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":[0.000006569666,0.00009016,0.02028077,8.72846e-7,0.0001207156,0.000004072637,0.00001260736,0.865949,0.000005311109,0.112869,0.0001759342,0.0004849938],"study_design_scores_gemma":[0.0004231429,0.00002072569,0.05356712,0.000003402035,0.0001354255,0.00001837921,0.000005187452,0.9400091,0.00000918395,0.005566478,0.0001542706,0.00008756365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001835049,0.00008632988,0.9954146,0.00181169,0.0001739885,0.00003841377,0.00000339105,0.00001600409,0.002272106],"genre_scores_gemma":[0.1092428,0.00001589062,0.8904071,0.0001929562,0.00006681727,9.629186e-7,0.0000156167,0.000002594706,0.00005526736],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1090593,"threshold_uncertainty_score":0.3731427,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2002055553","doi":"10.1007/s10898-004-8318-4","title":"Optimality Conditions for D.C. Vector Optimization Problems Under Reverse Convex Constraints","year":2005,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Mathematics; Mathematical optimization; Regular polygon; Convex optimization; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01720371333025808,"gpt":0.2794169235117329,"spread":0.2622132101814748,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005943018,0.000194564,0.0003412126,0.0001509793,0.0002265639,0.0002561419,0.0004765559,0.0001331709,0.0003624615],"category_scores_gemma":[0.000238861,0.0001843312,0.0002479234,0.0008391667,0.00008777075,0.001847209,0.00005326558,0.000109227,0.00001034769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004065582,"about_ca_system_score_gemma":0.0003659686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004574387,"about_ca_topic_score_gemma":0.000004262524,"domain_scores_codex":[0.9979882,0.0001181347,0.0009053366,0.0002706152,0.0004738665,0.0002438626],"domain_scores_gemma":[0.9967311,0.0001099112,0.0009731443,0.0002381385,0.001753352,0.0001943652],"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":[0.00002040679,0.0001628516,0.0001195773,0.000009415449,0.0001018038,9.354972e-7,0.00004429663,0.9118053,0.00001556209,0.08529589,0.002062685,0.0003613106],"study_design_scores_gemma":[0.001420649,0.0001199712,0.0004058034,0.0000322636,0.000101967,0.00007109196,0.00003506188,0.9957389,0.00002568935,0.001057668,0.0007926697,0.0001982826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000949565,0.00006688747,0.9864968,0.01167415,0.0003716989,0.0003123934,0.00006683251,0.00006032826,0.0008559272],"genre_scores_gemma":[0.1884938,0.00007922309,0.8097472,0.001254287,0.0002281075,0.00001116406,0.0000794048,0.00001086696,0.00009591591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1883989,"threshold_uncertainty_score":0.751681,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043131887","doi":"10.1007/s10898-014-0222-y","title":"The robust crew pairing problem: model and solution methodology","year":2014,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Crew; Mathematical optimization; Nonlinear system; Mathematics; Pairing; Interval (graph theory); Relaxation (psychology); Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03915311288015694,"gpt":0.2788324183795673,"spread":0.2396793054994104,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002176892,0.0001124344,0.0001878614,0.00004051278,0.0001543017,0.0000798316,0.0001320311,0.00009687433,0.000003050858],"category_scores_gemma":[0.000498585,0.00008739976,0.00004952214,0.0002092624,0.00004342032,0.0002599466,0.000030603,0.0001543278,6.41168e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343724,"about_ca_system_score_gemma":0.00002897545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002116791,"about_ca_topic_score_gemma":0.000004391474,"domain_scores_codex":[0.9988083,0.0002962289,0.0004527746,0.00008479875,0.0001724036,0.0001855506],"domain_scores_gemma":[0.9991553,0.0002123909,0.0002230068,0.0001060271,0.0002262932,0.00007694287],"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":[0.0000146179,0.000004932435,0.000297931,0.00001445002,0.0000238198,3.297856e-7,0.00003917687,0.9851326,0.00009995711,0.002232383,0.000269684,0.0118701],"study_design_scores_gemma":[0.000316113,0.00004330332,0.0002538765,0.0000275905,0.00003822656,0.00007213365,0.00001709689,0.997479,0.00004297044,0.001453016,0.0001697554,0.00008694203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00285294,0.0003688258,0.9944589,0.0004645526,0.0002575041,0.00007540132,9.866228e-7,0.00006426494,0.001456667],"genre_scores_gemma":[0.09169588,0.0003803298,0.9077361,0.00004477818,0.000103855,0.000001527852,9.764207e-7,0.00001653516,0.00002000027],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08884294,"threshold_uncertainty_score":0.3564059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2294719872","doi":"10.1007/s10898-015-0394-0","title":"Local search algorithm for universal facility location problem with linear penalties","year":2015,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Facility location problem; 1-center problem; Mathematical optimization; Mathematics; Set (abstract data type); Location model; Total cost; Computer science; Algorithm; Operations research","retraction":null,"screen_n_in":null,"score":{"opus":0.03017387370649793,"gpt":0.2533858792778074,"spread":0.2232120055713094,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006942213,0.0001177193,0.0001596628,0.0001024076,0.00009050159,0.0001007945,0.000165124,0.00004653927,0.00004240332],"category_scores_gemma":[0.00005937029,0.00009673395,0.00005219492,0.0005729055,0.00005979735,0.001357516,0.00004382184,0.00007027893,0.00002157934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002682813,"about_ca_system_score_gemma":0.000167644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000350345,"about_ca_topic_score_gemma":0.0001036319,"domain_scores_codex":[0.9988652,0.00001696308,0.000360768,0.0001356981,0.0004557612,0.0001656222],"domain_scores_gemma":[0.9972622,0.000006614138,0.0001852236,0.0001027235,0.002407072,0.00003616308],"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":[0.0002173785,0.00009960338,0.0008793208,0.000080265,0.00003727966,0.00000183548,0.00003821972,0.9790648,3.391947e-7,0.001607933,0.002844543,0.01512845],"study_design_scores_gemma":[0.001401367,0.0001275787,0.0004279615,0.00003102919,0.00007036656,0.000004693479,0.001487476,0.9842525,0.000004146771,0.0002136161,0.01185385,0.0001254832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003001699,0.00004111564,0.9937351,0.001355103,0.0002353811,0.0003197329,0.0000111238,0.00002959048,0.001271199],"genre_scores_gemma":[0.7879528,0.00002485869,0.2102474,0.0005842999,0.0006228237,0.00001089691,0.0001926676,0.00001666604,0.0003475243],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7849512,"threshold_uncertainty_score":0.3944696,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105046377","doi":"10.1023/a:1024847308982","title":"Cyclic Just-In-Time Sequences Are Optimal","year":2003,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Sequence (biology); Concatenation (mathematics); Product (mathematics); Integer (computer science); Production (economics); Discrete mathematics; Computer science; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.006722708713548566,"gpt":0.2266807671283111,"spread":0.2199580584147625,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003355654,0.0001620255,0.0002896838,0.0001141979,0.00003451549,0.00006587804,0.0001729059,0.0001203239,0.00007219978],"category_scores_gemma":[0.0002160531,0.0001599895,0.00007489696,0.000599469,0.00001946639,0.0005319693,0.000009742296,0.0001526052,0.00001655595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004286495,"about_ca_system_score_gemma":0.00006765309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002199254,"about_ca_topic_score_gemma":0.000003977004,"domain_scores_codex":[0.9987045,0.00006603196,0.0005760367,0.0001040289,0.0003226533,0.0002267844],"domain_scores_gemma":[0.9993131,0.00002773524,0.0002737896,0.000109779,0.000182522,0.00009308116],"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":[0.00001224596,0.00003162556,0.01207514,0.00001327567,0.00001968819,0.0000263844,0.00002923994,0.9868906,0.0001255898,0.0001181375,0.0005782093,0.00007984837],"study_design_scores_gemma":[0.001068117,0.00009058259,0.005437273,0.0001650609,0.00004834456,0.0002802865,0.0001385043,0.9913583,0.0005783737,0.00008133797,0.0004659143,0.0002878457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3182175,0.0008080644,0.6723541,0.0001609428,0.0009309594,0.0001974015,0.000009749713,0.0001377889,0.007183566],"genre_scores_gemma":[0.8627129,0.0002169933,0.1368485,0.00004736895,0.0001110539,0.000001718614,0.000005261543,0.00002549602,0.00003075346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5444954,"threshold_uncertainty_score":0.6524183,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3036119246","doi":"10.1007/s10898-020-00915-x","title":"Generalized risk parity portfolio optimization: an ADMM approach","year":2020,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Portfolio optimization; Mathematics; Mathematical optimization; Portfolio; Optimization problem; Coherent risk measure; Convex optimization; Risk measure; Regular polygon; Economics; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.06904678787804504,"gpt":0.3482783259159813,"spread":0.2792315380379363,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002451957,0.0003054712,0.0007022616,0.0001878903,0.0002814934,0.0006269694,0.001010436,0.0002459539,0.0007918344],"category_scores_gemma":[0.002722393,0.0002391809,0.0003261677,0.002620542,0.00008957788,0.002396335,0.0001001377,0.0003097692,0.00002329252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001370641,"about_ca_system_score_gemma":0.0003711388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002337694,"about_ca_topic_score_gemma":0.000002688406,"domain_scores_codex":[0.9941944,0.0007954602,0.002069809,0.0005247842,0.002089428,0.0003260602],"domain_scores_gemma":[0.9936625,0.0001046329,0.002865287,0.0004707046,0.002182348,0.0007144625],"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":[0.0003274464,0.000168554,0.02484667,0.000002110189,0.00004531633,0.00001617931,0.0001752823,0.9598369,0.000002417893,0.0008416669,0.00976618,0.003971306],"study_design_scores_gemma":[0.001436412,0.0003974018,0.001894695,0.000006458023,0.0001266207,0.0001169447,0.0002593049,0.9909269,0.00001576964,0.0008594614,0.00369396,0.0002660863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0135669,0.0003786451,0.9783038,0.001043795,0.000577945,0.0002483955,0.00005860909,0.0000598338,0.005762001],"genre_scores_gemma":[0.2849697,0.00194869,0.7109031,0.001054377,0.0009321125,0.000003248306,0.00008517035,0.00002987712,0.00007373943],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2714028,"threshold_uncertainty_score":0.9753513,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2792821451","doi":"10.1007/s10898-018-0634-1","title":"A sampling-based exact algorithm for the solution of the minimax diameter clustering problem","year":2018,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal; Polytechnique Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Cluster analysis; Minimax; Heuristic; Mathematical optimization; Algorithm; Set (abstract data type); Sampling (signal processing); Computer science; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.0290985115856251,"gpt":0.3178516843701105,"spread":0.2887531727844854,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006997283,0.0001043486,0.0001558842,0.00004798481,0.0002183394,0.0000990923,0.0009510341,0.00005281977,0.000003982409],"category_scores_gemma":[0.0002102629,0.00006123064,0.0001445935,0.0005376253,0.0001270411,0.0004145746,0.000212977,0.0001121448,6.555917e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002296817,"about_ca_system_score_gemma":0.0002034083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001024817,"about_ca_topic_score_gemma":0.000008017721,"domain_scores_codex":[0.9986214,0.00008314684,0.0004334837,0.0001462613,0.0004837619,0.0002319623],"domain_scores_gemma":[0.9979709,0.0002062801,0.0005539366,0.0003238946,0.0008923546,0.00005262747],"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":[0.00004084438,0.00004353785,0.00006040855,0.00001519068,0.00002943633,5.364577e-7,0.00008030775,0.8507505,0.0001405788,0.00005466896,0.000166032,0.1486179],"study_design_scores_gemma":[0.000598244,0.0003657647,0.0004450129,0.00008317189,0.00001666396,0.00003747176,0.00001405411,0.9968691,0.00078563,0.0003356847,0.0003825476,0.00006665386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000189154,0.0000825817,0.9972866,0.001481713,0.0005658559,0.0003177238,0.000008652609,0.00001360743,0.00005407835],"genre_scores_gemma":[0.04581221,0.00001046007,0.9537922,0.0001205882,0.0002272251,0.000007956854,4.958748e-7,0.000008266016,0.00002066701],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1485513,"threshold_uncertainty_score":0.2496913,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001516627","doi":"10.1007/s10898-014-0183-1","title":"Solving the planar p-median problem by variable neighborhood and concentric searches","year":2014,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada; Royal Ottawa Mental Health Centre","funders":"Agence Nationale de la Recherche","keywords":"Mathematics; Concentric; Planar; Heuristic; Variable (mathematics); Mathematical optimization; Variable neighborhood search; Plane (geometry); Decomposition; Optimization problem; Algorithm; Metaheuristic; Geometry; Computer science; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.008999484427241255,"gpt":0.2018814808665637,"spread":0.1928819964393225,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070183,0.00008829893,0.0001171441,0.00003738775,0.0001590343,0.000217745,0.0001663069,0.00003355583,0.0001151093],"category_scores_gemma":[0.0001844722,0.00006246811,0.00002980974,0.0004048219,0.00003526668,0.0007371723,0.00004562045,0.000078792,0.00001034232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004970899,"about_ca_system_score_gemma":0.00002166238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001635855,"about_ca_topic_score_gemma":0.00002039264,"domain_scores_codex":[0.9991571,0.00002453721,0.0003027187,0.00009546387,0.0002671856,0.0001529664],"domain_scores_gemma":[0.9994451,0.0000198771,0.0001921636,0.00008559866,0.0002369664,0.00002027191],"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":[0.00009827848,0.0001817395,0.05268235,0.0002395527,0.0001279251,0.000002202541,0.0001017917,0.6824048,0.00004248674,0.1243557,0.1194657,0.02029751],"study_design_scores_gemma":[0.0009045457,0.00003598585,0.004199376,0.00005979797,0.00009138396,0.000005665244,0.0002504825,0.9150081,0.000002244304,0.004172627,0.07511671,0.0001530711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01017773,0.0006489239,0.9278541,0.02115143,0.0008628119,0.0004316347,0.000008359852,0.00005180853,0.03881316],"genre_scores_gemma":[0.9904516,0.0002022036,0.006513413,0.002197833,0.0004913804,0.000002722731,0.00002114667,0.000008474563,0.0001111818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9802739,"threshold_uncertainty_score":0.2547376,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2769009861","doi":"10.1007/s10898-017-0590-1","title":"Low-rank matrix completion using nuclear norm minimization and facial reduction","year":2017,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matrix completion; Mathematics; Mathematical optimization; Semidefinite programming; Low-rank approximation; Matrix norm; Norm (philosophy); Rank (graph theory); Embedding; Minification; Matrix (chemical analysis); Linear programming; Algorithm; Computer science; Artificial intelligence; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.01609821826002892,"gpt":0.2661418461865124,"spread":0.2500436279264835,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007860185,0.00009424454,0.0001529474,0.0000510944,0.0002086498,0.0001808659,0.00009855422,0.00008224856,0.0000132194],"category_scores_gemma":[0.00003703939,0.00009697153,0.00004213145,0.00005474037,0.00004118984,0.000577156,0.00002324049,0.00007729029,7.487803e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001347101,"about_ca_system_score_gemma":0.00001285078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001487491,"about_ca_topic_score_gemma":0.000001448656,"domain_scores_codex":[0.9994107,0.00001761728,0.0002597087,0.00006928816,0.0001504558,0.00009224867],"domain_scores_gemma":[0.9993451,0.000003436445,0.0002920013,0.0001194948,0.0001933662,0.00004662685],"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":[0.00004434239,0.00001467559,0.0003475155,0.00001023631,0.00002366543,0.000005009017,0.00004067232,0.9912003,0.004656931,0.0001568376,0.0005385283,0.002961232],"study_design_scores_gemma":[0.0004037533,0.00005757248,0.002708338,0.0001278429,0.00005340589,0.0002769775,0.00003354304,0.9945163,0.001168985,0.0002098989,0.0003212516,0.0001220935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5973136,0.0001184532,0.4008372,0.0001042222,0.0007679267,0.00009156651,0.00000545098,0.00009058712,0.000671016],"genre_scores_gemma":[0.9333299,0.0002392112,0.06616557,0.000007801186,0.0002386831,1.458082e-7,0.000002988435,0.00001335781,0.000002285541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3360164,"threshold_uncertainty_score":0.3954384,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1987434446","doi":"10.1007/s10898-012-9969-1","title":"Portfolio selection under model uncertainty: a penalized moment-based optimization approach","year":2012,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Ambiguity; Portfolio; Portfolio optimization; Moment (physics); Mathematical optimization; Flexibility (engineering); Realization (probability); Mathematics; Econometrics; Range (aeronautics); Robust optimization; Selection (genetic algorithm); Computer science; Project portfolio management; Downside risk; Artificial intelligence; Economics; Finance; Statistics; Project management","retraction":null,"screen_n_in":null,"score":{"opus":0.06337797441665845,"gpt":0.3594306067613594,"spread":0.2960526323447009,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003435737,0.0003232098,0.0005787962,0.0005237131,0.0002623379,0.0003811735,0.0005186445,0.0002667248,0.0005321922],"category_scores_gemma":[0.0006552889,0.0002537898,0.0003337131,0.002661187,0.00007461374,0.00240394,0.0000509357,0.0002270057,0.00001204164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006515683,"about_ca_system_score_gemma":0.0005797638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001963897,"about_ca_topic_score_gemma":0.00000231645,"domain_scores_codex":[0.9946687,0.0004134515,0.001791919,0.0003436579,0.002270767,0.0005115198],"domain_scores_gemma":[0.9946614,0.0001305277,0.002258939,0.0003386498,0.002190583,0.0004199271],"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":[0.0003284919,0.0003775202,0.008056637,0.000003412253,0.00004678174,9.933382e-7,0.00007101328,0.9834029,0.000009859445,0.002060673,0.003878764,0.001762936],"study_design_scores_gemma":[0.001570316,0.0001282403,0.0006134773,0.00001446374,0.0001310342,0.0001026476,0.0001952037,0.9957291,0.00002685428,0.0007875334,0.0004377614,0.0002633659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004096715,0.0003099621,0.9874015,0.0004306671,0.0006354965,0.0003048661,0.00001717366,0.00004913905,0.006754445],"genre_scores_gemma":[0.4752215,0.0002463347,0.5234007,0.0004450429,0.0003109385,0.00000770612,0.00006034748,0.00002659736,0.0002807876],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4711248,"threshold_uncertainty_score":0.9999914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2156395865","doi":"10.1023/b:jogo.0000026448.63457.51","title":"Variational Analysis of the Abscissa Mapping for Polynomials via the Gauss-Lucas Theorem","year":2004,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Differential Equations and Dynamical Systems","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Mathematics; Lemma (botany); Pure mathematics; Discrete mathematics; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.02405172828966571,"gpt":0.3041534079869698,"spread":0.280101679697304,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005630606,0.00009162803,0.0002963014,0.0000640749,0.0001465893,0.00003499361,0.0002327203,0.00006131682,0.00003213171],"category_scores_gemma":[0.0006182939,0.00004823379,0.0003690699,0.0007803746,0.00004731249,0.0001298599,0.00002787682,0.0000623727,3.236386e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125144,"about_ca_system_score_gemma":0.00009142106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001659065,"about_ca_topic_score_gemma":0.00002329587,"domain_scores_codex":[0.998652,0.00007891219,0.0007341826,0.00007786421,0.000348801,0.0001082551],"domain_scores_gemma":[0.9978659,0.0003033713,0.001165179,0.000172157,0.0004569991,0.00003641119],"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":[0.00003258433,0.00007018915,0.0003175488,0.000008688397,0.0003744768,1.31629e-7,0.0001006135,0.789296,0.000103406,0.2094154,0.00002670658,0.0002542799],"study_design_scores_gemma":[0.001213195,0.00007657374,0.006291723,0.00008155276,0.001459408,0.00002038625,0.0002432945,0.5454817,0.00007129831,0.4448802,0.00005954272,0.0001211165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02092776,0.00003941071,0.9773687,0.0008922028,0.0002733088,0.0002449502,0.0000436768,0.000005047815,0.0002049029],"genre_scores_gemma":[0.8980287,0.000005992365,0.1017489,0.00005444903,0.0001248236,0.000002909434,0.00000662499,0.00000633267,0.00002120693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.877101,"threshold_uncertainty_score":0.1966917,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1991964874","doi":"10.1007/s10898-013-0037-2","title":"Abstract convexity of topical functions","year":2013,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Graduate University of Advanced Technology; Indian Council of Agricultural Research; Centre de Recherches Mathématiques","keywords":"Convexity; Mathematics; Subderivative; Characterization (materials science); Homogeneous; Set (abstract data type); Space (punctuation); Polarity (international relations); Pure mathematics; Convex function; Regular polygon; Applied mathematics; Combinatorics; Convex optimization; Geometry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01030778035003522,"gpt":0.2372538433532074,"spread":0.2269460630031722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001404351,0.00006153426,0.0001490726,0.00005906291,0.00004448205,0.00007078452,0.0002658771,0.00004877188,0.0004345646],"category_scores_gemma":[0.0001004859,0.00005034843,0.0001128624,0.0004797792,0.00002299161,0.0008522626,0.00003512279,0.00005927189,0.00001829005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007104201,"about_ca_system_score_gemma":0.00009833816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003060869,"about_ca_topic_score_gemma":0.000002046445,"domain_scores_codex":[0.9990577,0.00003257303,0.00046018,0.00007911426,0.0002938487,0.00007661702],"domain_scores_gemma":[0.9984444,0.00003257066,0.0004644373,0.0001227629,0.0008560852,0.00007977015],"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":[0.00000530762,0.0001178901,0.008614507,0.000004567128,0.00005016943,0.000001101422,0.00003308702,0.9623308,0.00005442228,0.02562734,0.001534556,0.001626324],"study_design_scores_gemma":[0.0003925779,0.00008592939,0.1287972,0.00001293822,0.00002694872,0.00002637481,0.00003650549,0.8681374,0.00005455639,0.002193547,0.0001562412,0.0000797734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00587014,0.00002481616,0.9884441,0.001924927,0.0002458243,0.00004528707,0.000002247211,0.00001157814,0.003431044],"genre_scores_gemma":[0.7877443,0.00001772566,0.2119755,0.0001339089,0.00005762658,7.899746e-7,0.000002614047,0.000001714321,0.00006584635],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7818741,"threshold_uncertainty_score":0.4758178,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3162664130","doi":"10.1007/s10898-021-01019-w","title":"Integrating $$\\varepsilon $$-dominance and RBF surrogate optimization for solving computationally expensive many-objective optimization problems","year":2021,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"National Research Foundation Singapore","keywords":"Mathematical optimization; Surrogate model; Optimization problem; Mathematics; Function (biology); Multi-objective optimization; Evolutionary algorithm; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01190640232656003,"gpt":0.2696545108687438,"spread":0.2577481085421838,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006120827,0.0003972849,0.0005935911,0.000211551,0.0004379061,0.000511449,0.0004256757,0.0001875482,0.00002373007],"category_scores_gemma":[0.001591371,0.0004123635,0.0001825285,0.00129013,0.00009408558,0.003216649,0.0002161479,0.00023983,0.000001154873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006736686,"about_ca_system_score_gemma":0.0005731715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005619048,"about_ca_topic_score_gemma":0.000007650618,"domain_scores_codex":[0.9968737,0.0002109316,0.001209293,0.000679165,0.0006173216,0.0004095409],"domain_scores_gemma":[0.9911081,0.0003771115,0.001814033,0.0003002629,0.006199358,0.0002011101],"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":[0.00007527634,0.0001347402,0.000246421,0.00004263201,0.00008225209,0.00002701714,0.0006090081,0.9894968,0.00006219588,0.005604344,0.00006436047,0.003554913],"study_design_scores_gemma":[0.002638848,0.0002849164,0.0002196545,0.0002723129,0.00005909283,0.0004884865,0.0004539255,0.993799,0.0004110954,0.0009502833,0.00003051228,0.0003918647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004062575,0.0006812835,0.9961787,0.0007924197,0.0008536095,0.000694045,0.00002887331,0.0000928857,0.0002719444],"genre_scores_gemma":[0.03051037,0.0004443193,0.9683933,0.0002945165,0.0001558051,0.00003171381,0.00008656644,0.00003998321,0.00004344206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03010411,"threshold_uncertainty_score":0.9998328,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052697378","doi":"10.1007/s10898-014-0189-8","title":"Exact solution approach for a class of nonlinear bilevel knapsack problems","year":2014,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Air Force Office of Scientific Research; National Science Foundation; Division of Civil, Mechanical and Manufacturing Innovation; U.S. Air Force; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"Knapsack problem; Mathematics; Continuous knapsack problem; Mathematical optimization; Constraint (computer-aided design); Nonlinear system; Class (philosophy); Binary number; Function (biology); Integer (computer science); Change-making problem; Quadratic equation; Computer science; Artificial intelligence; Arithmetic","retraction":null,"screen_n_in":null,"score":{"opus":0.01597327206172961,"gpt":0.2325935639447818,"spread":0.2166202918830522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004348592,0.0001321729,0.0002692651,0.00008393372,0.00003893631,0.00003473371,0.0001350987,0.0001237342,0.00001523366],"category_scores_gemma":[0.0001041742,0.0001202887,0.0001232909,0.0003085792,0.00002576416,0.0002627601,0.00001091076,0.00009151571,9.904708e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143918,"about_ca_system_score_gemma":0.00004171985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002127107,"about_ca_topic_score_gemma":0.000001154016,"domain_scores_codex":[0.9988914,0.00003675546,0.000599859,0.00009102491,0.000215583,0.0001653682],"domain_scores_gemma":[0.9989862,0.00003194885,0.0003544334,0.0001112945,0.0004401654,0.00007590629],"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":[0.00003027165,0.00006642113,0.0002381905,0.0001667202,0.00004577835,7.952785e-8,0.00005337359,0.9959371,0.0001469147,0.0004530694,0.0009828861,0.001879158],"study_design_scores_gemma":[0.000975306,0.00019361,0.00008079893,0.00006869784,0.00004565384,0.00002019129,0.00001406222,0.9964446,0.0001664288,0.0001309229,0.001740278,0.0001194629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007022067,0.0001225225,0.9953811,0.00007220801,0.0003315795,0.0002317982,0.00002430463,0.00004481767,0.003089427],"genre_scores_gemma":[0.3418711,0.0001190433,0.6577025,0.00003025738,0.0001764676,0.000004946496,0.00004651651,0.00002469984,0.00002451922],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3411689,"threshold_uncertainty_score":0.490523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980552542","doi":"10.1007/s10898-014-0175-1","title":"New heuristic for harmonic means clustering","year":2014,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"Agence Nationale de la Recherche","keywords":"Degeneracy (biology); Heuristic; Cluster analysis; Heuristics; Degenerate energy levels; Mathematics; Consistent heuristic; Mathematical optimization; Harmonic; Algorithm; Computer science; Incremental heuristic search; Search algorithm; Beam search; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.01794351272686285,"gpt":0.2395191110732201,"spread":0.2215755983463572,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003721013,0.00008801057,0.0001353076,0.00007067964,0.0000772893,0.0001333356,0.0001611655,0.000029962,0.0001689917],"category_scores_gemma":[0.0002754599,0.00008153807,0.00009108767,0.0002429785,0.000007484186,0.0006467033,0.00003869872,0.00003749097,0.00002338096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007288298,"about_ca_system_score_gemma":0.00002314922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000886387,"about_ca_topic_score_gemma":0.00008338768,"domain_scores_codex":[0.9992006,0.000006956406,0.0003784665,0.00009148193,0.0001936157,0.0001289111],"domain_scores_gemma":[0.9993574,0.000009415562,0.0002156105,0.00009091637,0.0003070653,0.00001961462],"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":[0.00005708582,0.0000249622,0.00041541,0.00007267523,0.0000213064,3.24265e-7,0.000007242163,0.9562699,0.000003727976,0.00944906,0.02373615,0.009942208],"study_design_scores_gemma":[0.0007414556,0.0000279531,0.001380396,0.00002974074,0.00007808383,0.000001843433,0.00003554005,0.919012,0.000001696856,0.001447004,0.0771485,0.00009580202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009988928,0.00003415395,0.9902114,0.003195796,0.001049672,0.0001309607,0.000001109912,0.00002448218,0.004353505],"genre_scores_gemma":[0.8990286,0.00003774561,0.09599654,0.00221132,0.002216158,0.000003766253,0.0000233041,0.00001836979,0.0004641884],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8980297,"threshold_uncertainty_score":0.3325026,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2791867344","doi":"10.1007/s10898-018-0612-7","title":"Global optimization of MIQCPs with dynamic piecewise relaxations","year":2018,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Fundação para a Ciência e a Tecnologia; Ontario Research Foundation","keywords":"Mathematics; Mathematical optimization; Global optimization; Piecewise; Bilinear interpolation; Benchmark (surveying); Relaxation (psychology); Integer programming; Integer (computer science); Optimization problem; Branch and price; Nonlinear programming; Branch and bound; Nonlinear system; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.0186278142045024,"gpt":0.3480092862410984,"spread":0.329381472036596,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005016804,0.0002416233,0.0004661293,0.0002184168,0.0001692026,0.00006760434,0.0003905674,0.000170257,0.000216689],"category_scores_gemma":[0.001517745,0.0002114071,0.0001274351,0.002448971,0.0003045449,0.0008826137,0.00007697145,0.0001560549,0.000004949955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009742414,"about_ca_system_score_gemma":0.0007023318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009431851,"about_ca_topic_score_gemma":0.00002857069,"domain_scores_codex":[0.9971437,0.0001642229,0.001091901,0.0002432141,0.001027738,0.0003291926],"domain_scores_gemma":[0.9937586,0.0001233285,0.001686286,0.0003635288,0.003862187,0.0002060488],"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":[0.000343279,0.0002673266,0.001548348,0.00003421049,0.0001108169,0.000009529264,0.00006597035,0.9904975,0.000007293272,0.005406951,0.0005417099,0.001167103],"study_design_scores_gemma":[0.002216273,0.0008913461,0.0007325193,0.0002076129,0.0001432615,0.0002863301,0.0001864978,0.9876943,0.00004256039,0.007245777,0.0001016728,0.0002518072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002967236,0.00009892778,0.9926077,0.000798248,0.0002178275,0.0003364564,0.00006265956,0.00005034907,0.002860646],"genre_scores_gemma":[0.119136,0.0002140462,0.8802685,0.00005519748,0.0001627908,0.000004503521,0.0000225334,0.00003278364,0.0001036706],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1161688,"threshold_uncertainty_score":0.8620932,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2032696538","doi":"10.1023/b:jogo.0000006719.64826.55","title":"Portfolio Selection Theory with Different Interest Rates for Borrowing and Leading","year":2003,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Portfolio; Selection (genetic algorithm); Interest rate; Efficient frontier; Mathematics; Modern portfolio theory; Frontier; Econometrics; Economics; Financial economics; Monetary economics; Computer science; Artificial intelligence; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.020246209681051,"gpt":0.2501269094010178,"spread":0.2298806997199668,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002106701,0.00006867084,0.0001751272,0.00005270887,0.00008107542,0.00005036836,0.00004270358,0.00003697189,0.0000127776],"category_scores_gemma":[0.0001509314,0.00006049206,0.00003464752,0.0001503155,0.0000177896,0.0001851553,0.000004759126,0.00004537878,7.912631e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008260288,"about_ca_system_score_gemma":0.00002068162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002073532,"about_ca_topic_score_gemma":0.00000438153,"domain_scores_codex":[0.9994801,0.000003388354,0.0003102733,0.00009693679,0.00001787703,0.00009148312],"domain_scores_gemma":[0.9993947,0.0000304615,0.000405357,0.00003511613,0.00009481086,0.00003954707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005776798,0.00003651913,0.01183383,0.00001132942,0.00002559187,2.693258e-7,0.000023157,0.01052857,0.000007499436,0.9769751,0.00003464327,0.0004657722],"study_design_scores_gemma":[0.002702503,0.0009391785,0.0180312,0.0001502584,0.0001039751,0.000288826,0.0003220112,0.04865815,0.0003889581,0.9253645,0.002592241,0.0004581909],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02974865,0.000635242,0.9683749,0.0001058274,0.00009726893,0.0001011052,0.00001118197,0.000005014589,0.0009207854],"genre_scores_gemma":[0.9701949,0.00006373525,0.02960706,0.00004431121,0.00005331506,0.000007249329,0.000002098703,0.000007115554,0.00002025865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9404462,"threshold_uncertainty_score":0.2466795,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2010355238","doi":"10.1023/b:jogo.0000042114.11969.bb","title":"Improving Interval Analysis Bounds by Translations","year":2004,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Mathematics; Univariate; Interval (graph theory); Interval arithmetic; Simple (philosophy); Polynomial; Translation (biology); Multivariate statistics; Global optimization; Applied mathematics; Variable (mathematics); Branch and bound; Mathematical optimization; Statistics; Combinatorics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.007847256506081365,"gpt":0.2730848919841986,"spread":0.2652376354781172,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002789529,0.00007571196,0.0001895304,0.0000776293,0.00007100588,0.0001782938,0.0003406524,0.00003887658,0.000009576534],"category_scores_gemma":[0.0000569797,0.00006282721,0.0001926211,0.001419652,0.00001939712,0.000735238,0.00002708232,0.00008515556,0.000001027357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001480192,"about_ca_system_score_gemma":0.00008016139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003266967,"about_ca_topic_score_gemma":0.000002540634,"domain_scores_codex":[0.9990864,0.00005359628,0.0003701974,0.0001123711,0.0002550074,0.0001223889],"domain_scores_gemma":[0.9992636,0.00002128974,0.000308345,0.0001174245,0.0001895311,0.00009985118],"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":[0.000005865827,0.00008168219,0.0003558902,0.000001894539,0.000123786,0.000006138824,0.00005911117,0.9359652,0.0001220711,0.003223931,0.000050018,0.06000435],"study_design_scores_gemma":[0.0006549509,0.0002393789,0.0007789405,0.00001380647,0.0001993678,0.00004555449,0.00001883984,0.9926267,0.0001643466,0.004858814,0.0002673043,0.0001320533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009319535,0.0001843753,0.9967213,0.001670074,0.0002578011,0.00002860941,0.000004483657,0.0000183194,0.0001831315],"genre_scores_gemma":[0.1419377,0.00001676247,0.857857,0.0001288087,0.00004890553,3.534616e-7,0.000001453301,0.000002305236,0.000006628974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1410058,"threshold_uncertainty_score":0.2562019,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975120567","doi":"10.1007/s10898-012-0011-4","title":"Optimization methodology assessment for the inlet velocity profile of a hydraulic turbine draft tube: part II—performance evaluation of draft tube model","year":2012,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Polytechnique Montréal","keywords":"Draft tube; Computational fluid dynamics; Inlet; Hull; Grid; Computer science; Tube (container); Turbine; Simulation; Mathematical optimization; Mechanical engineering; Marine engineering; Mathematics; Engineering; Aerospace engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.05462665995559051,"gpt":0.3286806632136798,"spread":0.2740540032580893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003383738,0.0001857374,0.000391953,0.0001163168,0.00009924766,0.00001798821,0.0002169924,0.000133669,0.00009190519],"category_scores_gemma":[0.0004357719,0.00015305,0.0001292673,0.0004757236,0.00006029353,0.0008127513,0.00004466673,0.0001533431,5.346008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005464179,"about_ca_system_score_gemma":0.0002233401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003066288,"about_ca_topic_score_gemma":0.000001497039,"domain_scores_codex":[0.9976924,0.0002059311,0.001038672,0.000110643,0.0007025072,0.0002498656],"domain_scores_gemma":[0.9972564,0.0002120661,0.0007634506,0.0002165488,0.001471063,0.00008049857],"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":[0.00008318443,0.0001004652,0.0006244375,0.00007902698,0.0001483921,4.279452e-8,0.0004139701,0.9935969,0.0002526326,0.0003596851,0.0007684379,0.003572827],"study_design_scores_gemma":[0.001297422,0.0002025249,0.001795841,0.00005730985,0.0003778218,0.00001383794,0.00008966999,0.9944767,0.001284484,0.0001808011,0.00009015844,0.0001334754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1014312,0.0005487922,0.8956747,0.0002259124,0.000897696,0.0006833529,0.00005220852,0.0000235542,0.0004625929],"genre_scores_gemma":[0.6250717,0.0001468141,0.3744998,0.00003321541,0.0001416318,0.00003281435,0.00004353702,0.00001979921,0.00001070758],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5236405,"threshold_uncertainty_score":0.62412,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2037658347","doi":"10.1007/s10898-013-0068-8","title":"Carbon tax based on the emission factor: a bilevel programming approach","year":2013,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Bilevel optimization; Mathematics; Factor (programming language); Carbon tax; Mathematical optimization; Econometrics; Mathematical economics; Optimization problem; Greenhouse gas; Computer science; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.0663816637887262,"gpt":0.2388060456485127,"spread":0.1724243818597865,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003291274,0.0001190567,0.0002395972,0.00008521201,0.00007970163,0.0001435097,0.0001926739,0.00009198762,0.0002367051],"category_scores_gemma":[0.0001745239,0.00009139151,0.0001178809,0.000198422,0.00002538785,0.0002101667,0.00002217539,0.0001279181,0.00002638604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002899186,"about_ca_system_score_gemma":0.00002665263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001370944,"about_ca_topic_score_gemma":0.000002093213,"domain_scores_codex":[0.9990301,0.0000190631,0.0005747493,0.0001355857,0.00004744062,0.0001930512],"domain_scores_gemma":[0.9988682,0.00004137097,0.0007721255,0.0001608449,0.00006989789,0.00008751769],"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":[0.0001182288,0.0006406785,0.105888,0.00007125542,0.0001114159,0.000002743566,0.0005609462,0.8604347,0.00001647661,0.02100605,0.004836091,0.006313423],"study_design_scores_gemma":[0.0005149159,0.0001465941,0.004883169,0.00003252955,0.000007132108,0.00001106791,0.0001265243,0.9895821,0.00001718086,0.002294958,0.002219197,0.0001645894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6599829,0.0008875618,0.2379156,0.01560163,0.001675504,0.001420668,0.0003162933,0.00006391028,0.08213589],"genre_scores_gemma":[0.9844222,0.00007966581,0.01461387,0.0005858738,0.0002025134,0.00001272405,0.00000838273,0.00001446232,0.00006028201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3244393,"threshold_uncertainty_score":0.3726838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2024983730","doi":"10.1007/s10898-006-9038-8","title":"Exact Penalty Functions for Constrained Minimization Problems via Regularized Gap Function for Variational Inequalities","year":2006,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Penalty method; Differentiable function; Variational inequality; Minification; Stationary point; Function (biology); Convex function; Mathematical optimization; Order (exchange); Applied mathematics; Space (punctuation); Regular polygon; Mathematical analysis; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01804859287744212,"gpt":0.2471798043196314,"spread":0.2291312114421892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009353841,0.0002051542,0.0003412668,0.0002346755,0.0003422661,0.0003010844,0.0002852892,0.0001448146,0.00007542269],"category_scores_gemma":[0.0003541598,0.0001921355,0.0003195609,0.0008842042,0.00003609234,0.001441818,0.00002896166,0.00007039237,0.000002210504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002888257,"about_ca_system_score_gemma":0.000383564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002452353,"about_ca_topic_score_gemma":0.00001568752,"domain_scores_codex":[0.9977074,0.0001428749,0.001113821,0.0002841008,0.0005137158,0.0002380671],"domain_scores_gemma":[0.9954205,0.000288775,0.001293731,0.000182185,0.00272086,0.00009393266],"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":[0.000145593,0.0001700997,0.0003444556,0.00002489678,0.0001084128,2.301687e-7,0.00002438377,0.8306722,0.00006910894,0.1652896,0.002624071,0.0005268933],"study_design_scores_gemma":[0.002474936,0.0003087451,0.0009522286,0.00002290798,0.0001934434,0.0000304576,0.0000251038,0.9622378,0.00001439039,0.03195052,0.001590313,0.0001991146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007523224,0.0000591306,0.9950981,0.002825447,0.000774248,0.000552021,0.0001022788,0.00006584797,0.0004477689],"genre_scores_gemma":[0.1183076,0.00001443663,0.8792491,0.0003378024,0.0006657072,0.00006843125,0.0007495575,0.00001789297,0.0005894677],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1333391,"threshold_uncertainty_score":0.7835057,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115983461","doi":"10.1007/s10898-011-9785-z","title":"On some convexity properties of the Least Squares Method for pairwise comparisons matrices without the reciprocity condition","year":2011,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Laurentian University","funders":"","keywords":"Mathematics; Pairwise comparison; Convexity; Reciprocity (cultural anthropology); Mathematical optimization; Relaxation (psychology); Least-squares function approximation; Extreme point; Applied mathematics; Regular polygon; Non-linear least squares; Optimization problem; Explained sum of squares; Combinatorics; Statistics; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.1733473187034887,"gpt":0.410255208144609,"spread":0.2369078894411203,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009324867,0.0001143372,0.0003096582,0.00002057029,0.0001521759,0.000017759,0.0002148832,0.00006239591,0.00001538628],"category_scores_gemma":[0.001773062,0.00005577885,0.0001402949,0.0001179289,0.000122613,0.0002043824,0.00002943355,0.0001332304,2.705435e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007538855,"about_ca_system_score_gemma":0.00006767384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000115726,"about_ca_topic_score_gemma":0.000006045309,"domain_scores_codex":[0.9986131,0.0003561004,0.0005322704,0.00009453291,0.0002818007,0.000122168],"domain_scores_gemma":[0.9978808,0.0004293213,0.000981915,0.0001580248,0.0005046868,0.00004525841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001746837,0.0005894986,0.0007357455,0.0002868152,0.0001776541,8.943168e-7,0.0008675246,0.1173134,0.0002544583,0.872193,0.002311965,0.003522192],"study_design_scores_gemma":[0.0009706154,0.0005426781,0.0006405087,0.0003073784,0.0003159284,0.00002233286,0.0004786624,0.2007055,0.003330851,0.7924899,0.00006369495,0.0001319761],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009532046,0.000101753,0.9890876,0.0003365447,0.0002058479,0.0004319932,0.00006679877,0.000009534027,0.0002278538],"genre_scores_gemma":[0.3312593,0.00001709251,0.6685673,0.00009084537,0.00003528286,0.000008053976,6.111689e-7,0.000007431313,0.00001408476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3217273,"threshold_uncertainty_score":0.2274595,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2790720375","doi":"10.1007/s10898-017-0601-2","title":"Corrections to: Differentiable McCormick relaxations","year":2018,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Differentiable function; Mathematics; Regular polygon; Watson; Applied mathematics; Mathematical economics; Pure mathematics; Combinatorics; Geometry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03579917435867024,"gpt":0.3849292774845069,"spread":0.3491301031258367,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002906558,0.0001278375,0.0002272975,0.0001633177,0.0002305381,0.00007936961,0.0002392464,0.00008253074,0.0006470748],"category_scores_gemma":[0.001990797,0.0001154085,0.00009006615,0.001163321,0.00006666846,0.0004601446,0.00006482911,0.0001543635,0.00005953439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004187118,"about_ca_system_score_gemma":0.0001600383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004660271,"about_ca_topic_score_gemma":0.00001739565,"domain_scores_codex":[0.9984508,0.00007933558,0.0005968786,0.0001406381,0.0004959549,0.0002363717],"domain_scores_gemma":[0.9970381,0.0001182854,0.0004680081,0.0002137243,0.001948604,0.0002133366],"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":[0.0001642043,0.0004139791,0.002506347,0.00001590712,0.0001053946,0.000007771067,0.0002583736,0.9311091,0.0000842121,0.01662547,0.04605381,0.002655372],"study_design_scores_gemma":[0.003308185,0.002167965,0.002951739,0.0003327103,0.0002639737,0.0005028282,0.0007964128,0.9166441,0.0009917457,0.05624364,0.01501164,0.0007850524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005446178,0.00001889933,0.9876654,0.0006569939,0.000706956,0.0002124383,0.00001412699,0.00004757312,0.005231422],"genre_scores_gemma":[0.06279916,0.00004682302,0.9348181,0.0001521582,0.0004787437,0.000005995998,0.000005326992,0.00002623837,0.001667478],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05735299,"threshold_uncertainty_score":0.7085016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2798508703","doi":"10.1007/s10898-019-00744-7","title":"The Douglas–Rachford algorithm for a hyperplane and a doubleton","year":2019,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperplane; Regular polygon; Characterization (materials science); Simple (philosophy); Set (abstract data type); Focus (optics); Convex set","retraction":null,"screen_n_in":null,"score":{"opus":0.004747195214022939,"gpt":0.2293596423610671,"spread":0.2246124471470442,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003880397,0.00007487216,0.0001361873,0.00003942089,0.0001353513,0.0002722264,0.0002873917,0.00004148394,0.000009783865],"category_scores_gemma":[0.000049977,0.0000490721,0.0000790601,0.0003322894,0.00001407642,0.0005402968,0.000046588,0.0000498259,0.000003252715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006090038,"about_ca_system_score_gemma":0.00008318665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004607781,"about_ca_topic_score_gemma":0.000001863672,"domain_scores_codex":[0.9991893,0.00003379675,0.000313921,0.000107485,0.0002431705,0.0001123481],"domain_scores_gemma":[0.9989032,0.0001083917,0.0003523654,0.0001243041,0.0004501942,0.00006156156],"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":[0.00005183656,0.00005459586,0.001251976,0.000006092946,0.0001082971,0.000001388235,0.00005977291,0.8785232,0.000005714545,0.06025388,0.001318494,0.05836478],"study_design_scores_gemma":[0.0007831914,0.000132023,0.0004229761,0.00000811257,0.00002473686,0.00006410588,0.00001941345,0.9895945,0.000004116854,0.001019849,0.007864469,0.00006253671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00038084,0.0002172889,0.9953105,0.002948105,0.000508202,0.0001269605,0.000004825164,0.00001113189,0.0004921282],"genre_scores_gemma":[0.01590515,0.0003343362,0.9827884,0.0004172446,0.0001704889,0.000003123817,0.000006675752,0.000005040697,0.0003695683],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1110713,"threshold_uncertainty_score":0.2625086,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2100485099","doi":"10.1007/s10898-010-9571-3","title":"Evaluating a branch-and-bound RLT-based algorithm for minimum sum-of-squares clustering","year":2010,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Mathematics; Convex hull; Combinatorics; Centroid; Cluster analysis; Least-squares function approximation; Triangle inequality; Set (abstract data type); Explained sum of squares; Data point; Algorithm; Regular polygon; Statistics; Geometry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02564626339742952,"gpt":0.3237365574687904,"spread":0.2980902940713608,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005128926,0.00008223308,0.0001593882,0.00006370153,0.00008414069,0.0001141202,0.0002090668,0.00007035468,0.000009504819],"category_scores_gemma":[0.0001632118,0.00007089291,0.00007684431,0.0001709083,0.00002575904,0.0005262004,0.00004201829,0.0000871774,5.405203e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002573515,"about_ca_system_score_gemma":0.0001178861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006580335,"about_ca_topic_score_gemma":0.000006328875,"domain_scores_codex":[0.9990734,0.00004000428,0.0003821788,0.0001164323,0.0002680147,0.0001199277],"domain_scores_gemma":[0.998783,0.0001038565,0.0004501221,0.000106385,0.0004873357,0.00006930964],"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":[0.00008779019,0.0001068174,0.0004503176,0.00005914167,0.00002843912,0.000002876654,0.0001456967,0.2850116,0.01072164,0.0001910136,0.0003426605,0.702852],"study_design_scores_gemma":[0.001062948,0.0003008075,0.0002687588,0.0001012132,0.00001944791,0.00003379973,0.00001730549,0.9948809,0.002567136,0.0006088261,0.00006203132,0.00007685606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05785542,0.00008500455,0.9408269,0.0003944313,0.0006530585,0.0001181826,0.000007332971,0.00001237472,0.0000473163],"genre_scores_gemma":[0.1818557,0.00001120915,0.8179165,0.0001059457,0.00009647794,0.000002869546,0.000002824164,0.000004225236,0.000004245211],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7098693,"threshold_uncertainty_score":0.2890929,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2149760726","doi":"10.1007/s10898-010-9585-x","title":"Controlled predatory pricing in a multiperiod Stackelberg game: an MPEC approach","year":2010,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Stackelberg competition; Oligopoly; Predatory pricing; Order (exchange); Competitor analysis; Microeconomics; Production (economics); Economics; Incentive; Linearization; Mathematical optimization; Mathematical economics; Cournot competition; Mathematics; Monopoly; Nonlinear system","retraction":null,"screen_n_in":null,"score":{"opus":0.03387750278639193,"gpt":0.364519891842761,"spread":0.330642389056369,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003485382,0.0001191303,0.0003985616,0.0001647968,0.0000784978,0.0002328222,0.0006019152,0.0001153341,0.0001791957],"category_scores_gemma":[0.002272946,0.00008518602,0.0001194436,0.0008311374,0.00008181967,0.0009160598,0.00004110631,0.0002947738,0.00001193768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007513544,"about_ca_system_score_gemma":0.0001795107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006956046,"about_ca_topic_score_gemma":0.00003718862,"domain_scores_codex":[0.9975165,0.0002911091,0.001055708,0.0002173028,0.0007473552,0.0001720688],"domain_scores_gemma":[0.9977248,0.0002452141,0.0008721282,0.0003445567,0.0006528679,0.0001604021],"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":[0.0006796499,0.0005484709,0.01271885,0.000002403351,0.00001822343,0.00000544422,0.0005859318,0.9685546,0.001433427,0.009837913,0.0001828665,0.005432292],"study_design_scores_gemma":[0.008781761,0.0002574585,0.03017679,0.00002088907,0.00004404731,0.0001843561,0.001968698,0.9450397,0.0001157032,0.0114819,0.001666934,0.0002617053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7162489,0.00003740075,0.2796845,0.0002199655,0.0002522629,0.000267799,0.000008890984,0.0000116949,0.003268632],"genre_scores_gemma":[0.9368477,0.000006639144,0.06282807,0.00008620993,0.0001285888,0.000007264024,0.000002609516,0.000006180576,0.00008666722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2205989,"threshold_uncertainty_score":0.3473785,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105120842","doi":"10.1007/s10898-011-9691-4","title":"An efficient algorithm for maximal margin clustering","year":2011,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Air Force Office of Scientific Research; National Institutes of Health; National Science Foundation","keywords":"Margin (machine learning); Cluster analysis; Mathematics; Curse of dimensionality; Dimensionality reduction; Convergence (economics); Algorithm; Extension (predicate logic); Computational complexity theory; Computer science; Artificial intelligence; Machine learning; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02734527043313598,"gpt":0.3021882505185445,"spread":0.2748429800854085,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004898872,0.0001165369,0.0001744378,0.00009015699,0.00009814673,0.0001151939,0.0007955206,0.00005860815,0.0000115932],"category_scores_gemma":[0.00005174061,0.0001062762,0.00008397487,0.0003604007,0.00002931127,0.0007619506,0.0001363932,0.0001020709,0.000002353076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002594272,"about_ca_system_score_gemma":0.0001047194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006231558,"about_ca_topic_score_gemma":0.000001031921,"domain_scores_codex":[0.9986767,0.00005669664,0.0003874643,0.0001952741,0.0003938799,0.000290026],"domain_scores_gemma":[0.9986984,0.00002424841,0.0002886969,0.0002537444,0.0005546594,0.0001803245],"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":[0.00003964594,0.0001126364,0.00003258481,0.000006331264,0.00001321009,0.00002282734,0.000125276,0.8519605,0.00002130015,0.0004314374,0.00002337631,0.1472108],"study_design_scores_gemma":[0.0006766836,0.0005888333,0.0003954686,0.00002323936,0.000006781863,0.0002297183,0.00003531458,0.9973371,0.0001663882,0.0003589815,0.00006992841,0.0001115461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007150105,0.00005495254,0.9981276,0.00007955007,0.0005453239,0.0001626477,0.000006641048,0.00004016172,0.0002681335],"genre_scores_gemma":[0.02809805,0.00001184008,0.9716871,0.00004409233,0.0001301652,0.000004187258,0.000001305039,0.00000980187,0.00001345172],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1470993,"threshold_uncertainty_score":0.4333817,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1505732277","doi":"10.1023/a:1013838625301","title":"A note on reduction of quadratic and bilinear programs with equality constraints","year":2002,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal; University of Prince Edward Island","funders":"","keywords":"Mathematics; Bilinear interpolation; Mathematical optimization; Graph; Reduction (mathematics); Quadratic equation; Discrete mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.05982993377738271,"gpt":0.3607467880512986,"spread":0.3009168542739159,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003437753,0.0001199345,0.0002780984,0.00008042575,0.00005231102,0.0000349722,0.00008734306,0.00007349253,0.00009217844],"category_scores_gemma":[0.0005420053,0.00009079806,0.00004601478,0.0004577879,0.0002208427,0.0002887548,0.00001654094,0.0001491571,0.000001256247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001471588,"about_ca_system_score_gemma":0.00005792278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001860705,"about_ca_topic_score_gemma":0.000001696194,"domain_scores_codex":[0.9984813,0.0001242293,0.0005742431,0.0001267413,0.0005485308,0.0001449865],"domain_scores_gemma":[0.9982212,0.00008862875,0.0006972805,0.0001403036,0.0007474847,0.0001050987],"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":[0.0005091212,0.001172034,0.00066304,0.0001629183,0.000123203,0.00001949359,0.0005952192,0.9298669,0.00009516707,0.008867906,0.0002042161,0.05772085],"study_design_scores_gemma":[0.003666525,0.002832378,0.0001658749,0.000523773,0.0001212481,0.0007458676,0.0006095837,0.9861423,0.000460523,0.004389483,0.0000607361,0.0002817199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03274729,0.00005864707,0.9652557,0.0004532117,0.00007639576,0.0003589697,0.000008688764,0.00002146766,0.001019606],"genre_scores_gemma":[0.3936113,0.0001056505,0.6061625,0.0000121826,0.00004783636,0.000002071991,0.000002204727,0.00001190463,0.00004441246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.360864,"threshold_uncertainty_score":0.3702637,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2963548325","doi":"10.1007/s10898-019-00786-x","title":"A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs","year":2019,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Process Optimization and Integration","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Decomposition; Benders' decomposition; Mathematics; Nonlinear system; Decomposition method (queueing theory); Integer (computer science); Lagrangian relaxation; Global optimization; Nonlinear programming; Integer programming; Optimization problem; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.009939009430692343,"gpt":0.2805451406456261,"spread":0.2706061312149337,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042134,0.0002549358,0.0004928288,0.0001083888,0.00004723468,0.00009263954,0.0001950476,0.0002275799,0.00007458505],"category_scores_gemma":[0.0001181182,0.0002361251,0.0002548725,0.0005813458,0.00002592287,0.0008108895,0.00002115452,0.0001381249,0.000004730246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005385334,"about_ca_system_score_gemma":0.0001377705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001073717,"about_ca_topic_score_gemma":0.00001229737,"domain_scores_codex":[0.9980282,0.00006645663,0.00109395,0.0001914714,0.0003786126,0.0002413259],"domain_scores_gemma":[0.9975795,0.00003247975,0.0006752381,0.0001662062,0.001421855,0.0001247613],"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":[0.0001684806,0.000153203,0.0008793836,0.0001380764,0.0001034384,8.795908e-7,0.00004912248,0.9922267,0.0001758644,0.0005816462,0.0003605372,0.005162681],"study_design_scores_gemma":[0.001796109,0.0004524658,0.0001267727,0.0002153618,0.0001028365,0.00006624361,0.00009369346,0.9953457,0.001162315,0.0001007604,0.0003181573,0.0002195876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002386291,0.0002001168,0.994162,0.0001438057,0.001054518,0.0006465455,0.00005308521,0.00009132212,0.001262338],"genre_scores_gemma":[0.1385794,0.0001446786,0.8608066,0.000065565,0.0001342667,0.00001285558,0.0002016565,0.000031492,0.00002349829],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1361931,"threshold_uncertainty_score":0.9628904,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1575565646","doi":"10.1023/a:1008318925663","title":"An Algorithm of Global Optimization for Rational Functions with Rational Constraints","year":2000,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Mathematics; Nonlinear programming; Mathematical optimization; Nonlinear system; Reliability (semiconductor); Rational function; Algorithm; Pure mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.008889216610178687,"gpt":0.2523837593612497,"spread":0.243494542751071,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000155369,0.0001387512,0.0001907332,0.00004459369,0.0001038384,0.00004953685,0.0001108722,0.00009589612,0.0005493523],"category_scores_gemma":[0.00002181478,0.0001334808,0.00007928161,0.0003857361,0.00006591054,0.0005138366,0.000002739955,0.00006360795,0.000002646822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002355544,"about_ca_system_score_gemma":0.0002127836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002835431,"about_ca_topic_score_gemma":0.000005588784,"domain_scores_codex":[0.9988408,0.00002526471,0.0005710783,0.0001224844,0.0003084913,0.0001318872],"domain_scores_gemma":[0.9986872,0.0000288128,0.0002046113,0.0001219435,0.000844752,0.0001126668],"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":[0.00008544508,0.0001015328,0.0004098579,0.000007668741,0.00006541736,3.629533e-7,0.00001906643,0.984849,0.00001782488,0.001388308,0.0004856227,0.01256986],"study_design_scores_gemma":[0.001348067,0.0001749575,0.0007000372,0.00002414196,0.0000787582,0.00006521151,0.00004987497,0.9969201,0.00002084148,0.0002304711,0.0002602368,0.0001272966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006504724,0.00005108745,0.9912415,0.0001684781,0.0001597554,0.0002586468,0.000339501,0.00006010001,0.00121619],"genre_scores_gemma":[0.5142238,0.00002522627,0.4852482,0.00004597104,0.0001567556,0.00001235563,0.0002604027,0.00001266527,0.00001470638],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.507719,"threshold_uncertainty_score":0.6015022,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2054567731","doi":"10.1007/s10898-004-0867-z","title":"Duality in Multivalued Complementarity Theory by Using Inversions and Scalar Derivatives","year":2005,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Mathematics; Infinitesimal; Complementarity (molecular biology); Duality (order theory); Scalar (mathematics); Pure mathematics; Mathematical economics; Mathematical analysis; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.06516242544786878,"gpt":0.4082980049243089,"spread":0.3431355794764401,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008976172,0.000114793,0.0002399501,0.00008542346,0.0001049022,0.00003865384,0.0001190622,0.00006286561,0.0001276322],"category_scores_gemma":[0.0009526245,0.0001059975,0.00004083959,0.0003650915,0.0001002907,0.0006491638,0.00008194818,0.0001733604,5.1358e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005045034,"about_ca_system_score_gemma":0.0000760215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270246,"about_ca_topic_score_gemma":0.00001556814,"domain_scores_codex":[0.998426,0.0003510852,0.0005569697,0.0001237166,0.000363262,0.0001789367],"domain_scores_gemma":[0.9988654,0.0002286946,0.000386498,0.00009589869,0.000312572,0.0001109882],"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":[0.0002023123,0.0004522903,0.01422872,0.00003058544,0.00005957973,0.000006138319,0.0004543957,0.973533,0.0002234922,0.00721063,0.0007791456,0.002819693],"study_design_scores_gemma":[0.00273143,0.00007547862,0.001153842,0.00009522009,0.00003399981,0.00004665698,0.0008987034,0.9760826,0.0002634609,0.01827248,0.0001722308,0.0001738681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1152023,0.0001422653,0.8836099,0.0005633267,0.00003755148,0.0001926393,0.00002999098,0.00001100925,0.0002110268],"genre_scores_gemma":[0.2129453,0.0001039895,0.7867731,0.0001071917,0.00003727882,9.041302e-7,0.000006462815,0.00001023365,0.00001548212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09774301,"threshold_uncertainty_score":0.4322451,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}