{"meta":{"query_hash":"119117fdafa3","filters":{"venue":"Operations Research Perspectives"},"cohort_total":6,"direct_labels_cover":0,"predictions_cover":6,"exported":6,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/119117fdafa3","api":"https://metacan.xera.ac/api/v1/cohort?venue=Operations+Research+Perspectives"},"results":[{"id":"W2084126087","doi":"10.1016/j.orp.2014.06.002","title":"Power theories for multi-choice organizations and political rules: Rank-order equivalence","year":2014,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"University of Ottawa","keywords":"Equivalence (formal languages); Voting; Mathematics; Equivalence class (music); Mathematical economics; Rank (graph theory); Social choice theory; Equivalence relation; Ordinal regression; Shapley value; Ordinal data; Order (exchange); Econometrics; Game theory; Discrete mathematics; Politics; Economics; Statistics; Combinatorics; Political science","score_opus":0.07920507547477938,"score_gpt":0.37175037743919237,"score_spread":0.292545301964413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084126087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3741241,0.002197568,0.55680615,0.00739647,0.0002891685,0.0015778596,0.0005490062,0.00013734575,0.05692235],"genre_scores_gemma":[0.98665243,0.000033274584,0.007192671,0.00005251113,0.00016947892,0.00012830742,0.0000121930025,0.000026032072,0.00573308],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986335,0.0001714166,0.00027408998,0.00042677042,0.000060627324,0.00043357533],"domain_scores_gemma":[0.99822015,0.000660417,0.000024651781,0.0002893422,0.0006785325,0.00012688481],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001942402,0.000108065724,0.0002098048,0.00025060883,0.00088469544,0.0003299556,0.00019536373,0.0000761811,0.0003840407],"category_scores_gemma":[0.01064693,0.00011032552,0.000034011235,0.00039858176,0.00047392218,0.00031099687,0.000074765136,0.00019080777,0.00022049004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064580063,0.00010789447,0.0027708106,0.000018372019,0.000022030928,1.0508545e-7,0.0056471922,0.000049676375,0.00010612038,0.9911752,0.00007976874,0.000016412874],"study_design_scores_gemma":[0.0048961,0.0012125486,0.04465411,0.00016352018,0.000019425588,0.000026306843,0.07854857,0.107589334,0.0007375657,0.72229695,0.038446873,0.0014086777],"about_ca_topic_score_codex":0.00026652517,"about_ca_topic_score_gemma":0.00010462151,"teacher_disagreement_score":0.6125283,"about_ca_system_score_codex":0.00008676673,"about_ca_system_score_gemma":0.00005140516,"threshold_uncertainty_score":0.9976868},"labels":[],"label_agreement":null},{"id":"W2784086842","doi":"10.1016/j.orp.2018.01.002","title":"Configuration and evaluation of an integrated demand management process using a space-filling design and Kriging metamodeling","year":2018,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université TÉLUQ; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metamodeling; Kriging; Computer science; Operations research; Process (computing); Industrial engineering; Profit (economics); Engineering; Economics; Microeconomics","score_opus":0.13483846830798552,"score_gpt":0.3989901837834457,"score_spread":0.2641517154754602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784086842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90213466,0.00028372827,0.09393729,0.00022599172,0.00003116326,0.0010661386,8.0280813e-7,0.000035039582,0.0022851597],"genre_scores_gemma":[0.9802766,0.000054644912,0.019313343,0.000012999547,0.00021695974,0.000046670495,0.000023643994,0.000016157428,0.000039009454],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984474,0.00016544263,0.00021279565,0.0003905975,0.0005820355,0.00020168748],"domain_scores_gemma":[0.996712,0.00002371531,0.000050506336,0.0001353937,0.0030605798,0.000017774599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040353173,0.00011908228,0.00013026761,0.0006741734,0.00084183196,0.00056325865,0.00009048449,0.00004173783,0.00008028811],"category_scores_gemma":[0.00033433654,0.00010880651,0.0000108956965,0.00082367484,0.00022033017,0.002318781,0.00006033299,0.000106469655,0.000007992344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007165832,0.00074371014,0.0017700216,0.00077841006,0.0005747805,0.0000064091796,0.052564133,0.57538253,0.11451446,0.1678131,0.0002283466,0.08490751],"study_design_scores_gemma":[0.0005202381,0.000024617282,0.000486763,0.0000775431,0.000076777265,0.0000016370423,0.033447172,0.95800894,0.0043927757,0.0027752959,0.000055064025,0.00013314871],"about_ca_topic_score_codex":0.0001413487,"about_ca_topic_score_gemma":0.00009313195,"teacher_disagreement_score":0.38262644,"about_ca_system_score_codex":0.0000704259,"about_ca_system_score_gemma":0.000109409506,"threshold_uncertainty_score":0.64747757},"labels":[],"label_agreement":null},{"id":"W2807206830","doi":"10.1016/j.orp.2018.05.001","title":"On slowdown variance as a measure of fairness","year":2018,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slowdown; Measure (data warehouse); Computer science; Variance (accounting); Decoupling (probability); Metric (unit); Suite; Range (aeronautics); Econometrics; Mathematics; Economics; Data mining; Political science; Engineering; Law; Operations management; Accounting","score_opus":0.03851069793096599,"score_gpt":0.36246131448806984,"score_spread":0.32395061655710383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807206830","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040873438,0.00060176814,0.8246852,0.012702224,0.00029177402,0.0007458053,0.000006978432,0.00017648932,0.119916335],"genre_scores_gemma":[0.9915357,0.00002671839,0.0044643222,0.00006574307,0.00023339836,0.00007724692,6.104838e-7,0.0000067245237,0.0035894916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808586,0.00037286762,0.00014411176,0.000418922,0.0006848463,0.0002933686],"domain_scores_gemma":[0.99724495,0.0002336692,0.000014548216,0.0005966197,0.0018123871,0.00009782077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089917035,0.00009135976,0.00012593235,0.00021339834,0.00054197543,0.00021214838,0.0007364579,0.000052792268,0.00024593686],"category_scores_gemma":[0.0006452609,0.00007854375,0.000044386146,0.00093565317,0.00042031074,0.00038792036,0.00010936911,0.0002591309,0.00038746189],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002879249,0.00016740955,0.000005080245,0.0000018190393,0.00002269913,0.0000035559528,0.0047283745,0.0011034098,0.0008550984,0.96782273,0.001626567,0.023634456],"study_design_scores_gemma":[0.0025015492,0.004148713,0.0019934413,0.00026683035,0.000012007173,0.000036399575,0.008596081,0.93122876,0.0059656324,0.03566959,0.008905392,0.0006756056],"about_ca_topic_score_codex":0.0000919706,"about_ca_topic_score_gemma":0.00015251208,"teacher_disagreement_score":0.9506623,"about_ca_system_score_codex":0.00007646476,"about_ca_system_score_gemma":0.00040332862,"threshold_uncertainty_score":0.4980168},"labels":[],"label_agreement":null},{"id":"W4200130196","doi":"10.1016/j.orp.2021.100210","title":"A simulation–optimization framework for optimizing response strategies to epidemics","year":2021,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Closure (psychology); Social distance; Computer science; Risk analysis (engineering); Operations research; Coronavirus disease 2019 (COVID-19); Management science; Business; Economics; Engineering; Medicine","score_opus":0.5230268611592118,"score_gpt":0.600429788115829,"score_spread":0.07740292695661721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200130196","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015359142,0.0004152957,0.95825875,0.024074364,0.00005010947,0.0011635922,0.000047854996,0.00013171708,0.00049918727],"genre_scores_gemma":[0.297514,0.00010429594,0.70053643,0.00024202785,0.00018356739,0.00059935707,0.000009752288,0.000029900702,0.00078066374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99616545,0.0016701504,0.00045064674,0.0006920181,0.00045404458,0.0005676588],"domain_scores_gemma":[0.9526313,0.043669183,0.000036514415,0.00058015104,0.0029028724,0.00017998181],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0045121727,0.00018961394,0.00037794336,0.00026122347,0.0014031506,0.00038626615,0.00024809336,0.00017004092,0.00031285262],"category_scores_gemma":[0.2531369,0.00017237142,0.00013409962,0.0011719841,0.00020013031,0.00036431584,0.0002721864,0.00045543403,0.000021856275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017926561,0.00011879396,0.000017565151,0.000020828802,0.000044227934,0.0000032660682,0.0077868993,0.66596526,0.0003332269,0.32478136,0.0006627376,0.00008655468],"study_design_scores_gemma":[0.00032038533,0.00028463663,0.00020862772,0.000111654386,0.000019823658,0.0000015669597,0.074900314,0.6794131,0.00023769373,0.2419761,0.0022331367,0.00029299405],"about_ca_topic_score_codex":0.000038855098,"about_ca_topic_score_gemma":0.00015945765,"teacher_disagreement_score":0.28215483,"about_ca_system_score_codex":0.0005702352,"about_ca_system_score_gemma":0.0005853988,"threshold_uncertainty_score":0.9998969},"labels":[],"label_agreement":null},{"id":"W4378373065","doi":"10.1016/j.orp.2023.100282","title":"Measuring the performance of retailers during the COVID-19 pandemic: Embedding optimal control theory principles in a dynamic data envelopment analysis approach","year":2023,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Agencia Nacional de Investigación y Desarrollo; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Competitor analysis; Data envelopment analysis; Business; Product (mathematics); Quarter (Canadian coin); Control (management); Marketing; Industrial organization; Economics","score_opus":0.36236579805391933,"score_gpt":0.48932577308612774,"score_spread":0.1269599750322084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378373065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9816953,0.00047210077,0.014113962,0.002360812,0.000019897483,0.0006712843,0.000059880516,0.000045294128,0.00056149776],"genre_scores_gemma":[0.9967796,0.00036743341,0.0008071787,0.000025082985,0.00002460583,0.00015575739,0.000021212742,0.000012951909,0.0018061281],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99042594,0.003892394,0.000846844,0.0010681279,0.0031526089,0.0006140981],"domain_scores_gemma":[0.991326,0.005310186,0.00011925082,0.0023506996,0.00077201886,0.000121840385],"candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.051563617,0.00017386505,0.00041387253,0.0023697359,0.0023593095,0.0006357473,0.0036033664,0.00006662668,0.00013367769],"category_scores_gemma":[0.020952674,0.00009481685,0.00016420578,0.012288085,0.0012473691,0.0006308994,0.0011191647,0.00070014957,0.000041094005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006247502,0.00007609881,0.04245841,0.0000082269635,0.00028455636,0.0000030087338,0.026464406,0.92775357,0.0012901269,0.0013076267,0.00002302456,0.00026844058],"study_design_scores_gemma":[0.00026237644,0.00001677972,0.06394505,0.000008832362,0.00005088118,0.000004821027,0.09712678,0.8382518,0.000031115425,0.00005855084,0.0001434539,0.00009956174],"about_ca_topic_score_codex":0.0002779085,"about_ca_topic_score_gemma":0.0020765294,"teacher_disagreement_score":0.0895018,"about_ca_system_score_codex":0.0006146713,"about_ca_system_score_gemma":0.0007639266,"threshold_uncertainty_score":0.99893945},"labels":[],"label_agreement":null},{"id":"W4414441757","doi":"10.1016/j.orp.2025.100355","title":"Development of a robust design optimization algorithm for hierarchical time series pharmaceutical problems","year":2025,"lang":"en","type":"article","venue":"Operations Research Perspectives","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"National Research Foundation of Korea","keywords":"Quality by Design; Quality (philosophy); Optimization problem; Optimization algorithm; Hierarchical database model; Design of experiments; Optimal design; Development (topology)","score_opus":0.3568773472423729,"score_gpt":0.5492687362278529,"score_spread":0.19239138898547997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414441757","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040021472,0.00045264032,0.9914367,0.0014070935,0.000063740554,0.0019212605,0.000025962227,0.000037940197,0.004254428],"genre_scores_gemma":[0.00260394,0.000038664817,0.9849211,0.00001791074,0.000042370095,0.00080377614,0.00001140579,0.000017104569,0.011543732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99492997,0.0017333484,0.00074227777,0.00072491425,0.0014215392,0.0004479365],"domain_scores_gemma":[0.99446833,0.0023234799,0.000039090017,0.00041292806,0.002612043,0.00014411645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010093908,0.0001695597,0.00033894487,0.0009578285,0.0010012576,0.00049709243,0.0007161612,0.00010922027,0.00083618134],"category_scores_gemma":[0.0057438216,0.00013766708,0.0000958889,0.0020972057,0.00074187067,0.0006721664,0.00028487312,0.0003053237,0.000051913874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000376378,0.0011795014,0.000008518559,0.00002470192,0.00016616126,0.0000022310762,0.018583119,0.6873879,0.11619415,0.036718026,0.0034117978,0.13594751],"study_design_scores_gemma":[0.0005910881,0.00022996814,0.000027911628,0.00003765475,0.000006893058,0.0000026091327,0.009182815,0.9155997,0.06894196,0.002115457,0.0031185388,0.00014538961],"about_ca_topic_score_codex":0.000006982174,"about_ca_topic_score_gemma":0.0000057546417,"teacher_disagreement_score":0.22821182,"about_ca_system_score_codex":0.00030125552,"about_ca_system_score_gemma":0.0012311703,"threshold_uncertainty_score":0.91555995},"labels":[],"label_agreement":null}]}