{"meta":{"query_hash":"2d921ac3640f","filters":{"venue":"IIE Transactions"},"cohort_total":55,"direct_labels_cover":0,"predictions_cover":55,"exported":55,"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/2d921ac3640f","api":"https://metacan.xera.ac/api/v1/cohort?venue=IIE+Transactions"},"results":[{"id":"W1556152654","doi":"10.1080/0740817x.2013.802842","title":"Economic lot-sizing with remanufacturing: complexity and efficient formulations","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; McGill University","funders":"","keywords":"Remanufacturing; Shortest path problem; Mathematical optimization; Sizing; Set (abstract data type); Path (computing); Computer science; Relaxation (psychology); Mathematics; Engineering; Manufacturing engineering","score_opus":0.014991112738484564,"score_gpt":0.1998788592341183,"score_spread":0.18488774649563375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1556152654","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":[0.8233356,0.000027853159,0.15571125,0.0037618561,0.0001877506,0.0010259157,0.000003781737,0.000317975,0.015628032],"genre_scores_gemma":[0.9975431,0.0000026433438,0.0012776672,0.0003806063,0.0001432137,0.00010520783,0.000010984776,0.000028259408,0.0005083277],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991086,0.0000056547765,0.00018731788,0.0002798748,0.000111735724,0.00030677542],"domain_scores_gemma":[0.99956334,0.000039278155,0.0000788654,0.00023473776,0.00006071826,0.000023076977],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010789128,0.00016704378,0.00014109169,0.0002706774,0.00050496246,0.00038716974,0.00011227866,0.00003749711,0.0013243335],"category_scores_gemma":[0.0000042297256,0.00015135623,0.00004509991,0.00015628908,0.00009823304,0.0008851811,0.000022798298,0.00012032631,0.0003087129],"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":[0.00016218895,0.0006298988,0.009690128,0.0013007007,0.00055123825,0.000032474287,0.001328662,0.78935724,0.00024321083,0.13781816,0.0029606132,0.055925503],"study_design_scores_gemma":[0.0036140375,0.000057796613,0.28626922,0.00011999079,0.000494313,0.000022214004,0.008745168,0.5771494,0.00029742258,0.026476784,0.09522718,0.0015264677],"about_ca_topic_score_codex":0.0026147368,"about_ca_topic_score_gemma":0.00086590543,"teacher_disagreement_score":0.27657908,"about_ca_system_score_codex":0.00010182608,"about_ca_system_score_gemma":0.000015364258,"threshold_uncertainty_score":0.9995886},"labels":[],"label_agreement":null},{"id":"W1965209739","doi":"10.1080/07408170208928926","title":"Satisfying partial demand in facilities location","year":2002,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":12,"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; University of Toronto","funders":"University of Calgary","keywords":"Facility location problem; 1-center problem; Location model; Computer science; Plane (geometry); Operations research; Transport engineering; Mathematics; Engineering","score_opus":0.04514013846048277,"score_gpt":0.22275572881894792,"score_spread":0.17761559035846514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965209739","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":[0.4074854,0.00063318264,0.4970013,0.011952334,0.0022184923,0.0011092086,0.000015099559,0.00075064384,0.078834355],"genre_scores_gemma":[0.99615705,0.00004523103,0.00006657635,0.0003676165,0.000111011905,0.000066140696,0.000008564178,0.000008200672,0.0031695855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991929,0.0000090360745,0.00025810965,0.00019252545,0.00014835762,0.00019909618],"domain_scores_gemma":[0.99974304,0.000009710034,0.00002339218,0.00016039742,0.000053653508,0.000009827837],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014553474,0.00010583149,0.00009724075,0.00023741246,0.00017791471,0.000090191985,0.00008959535,0.000038354916,0.0059696515],"category_scores_gemma":[0.000018291912,0.000115296156,0.000044791297,0.0005230867,0.000035391724,0.0008823276,0.000005781037,0.000091001115,0.0012739641],"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":[0.0001074678,0.001568,0.0188565,0.0019192542,0.00016151955,0.000018104487,0.0054528634,0.5948728,0.0005368674,0.04119043,0.014755256,0.320561],"study_design_scores_gemma":[0.0012136337,0.000011745607,0.03474024,0.00006291757,0.000070589915,0.0000012172519,0.0024021086,0.6350583,0.00009104902,0.0014113999,0.32437986,0.0005569913],"about_ca_topic_score_codex":0.002544993,"about_ca_topic_score_gemma":0.0069035063,"teacher_disagreement_score":0.5886717,"about_ca_system_score_codex":0.000036935075,"about_ca_system_score_gemma":0.000004001266,"threshold_uncertainty_score":0.9995037},"labels":[],"label_agreement":null},{"id":"W1971336976","doi":"10.1080/07408170490247458","title":"Production planning for medical devices with an uncertain regulatory approval date","year":2004,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"York University; Boston Scientific Corporation","keywords":"Production (economics); Product (mathematics); Government (linguistics); Competition (biology); Business; Population; Process (computing); New product development; Risk analysis (engineering); Operations management; Engineering; Computer science; Marketing; Medicine; Economics","score_opus":0.022364420684782258,"score_gpt":0.24778448180076926,"score_spread":0.225420061115987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971336976","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":[0.5313883,0.00006127891,0.45815074,0.006552363,0.00091021665,0.0008501122,0.0000029800608,0.0005613222,0.0015226705],"genre_scores_gemma":[0.99376684,0.0000028796997,0.0043099136,0.00043707463,0.000978423,0.00011113685,0.00012893362,0.000029157402,0.0002356391],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990249,0.000004826257,0.00017735167,0.00031843464,0.000271265,0.00020320603],"domain_scores_gemma":[0.999604,0.0000075636412,0.00008282328,0.00016011595,0.00012434613,0.000021169471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031568718,0.00013073694,0.00011163524,0.00015685601,0.00041122473,0.00010867598,0.00012935858,0.00006678958,0.00008060367],"category_scores_gemma":[0.000024648467,0.00011187439,0.000029683364,0.0003560158,0.00005325573,0.0016543292,0.0000038007925,0.00010227772,0.000017596212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005182755,0.0030842228,0.012349848,0.002869803,0.00095372053,0.00007826729,0.00463631,0.62091666,0.0047380705,0.06222355,0.004791946,0.27817482],"study_design_scores_gemma":[0.031082576,0.0006976084,0.13629389,0.0029325678,0.0027879039,0.0003657786,0.014041685,0.08477365,0.024662884,0.038105752,0.65659505,0.007660661],"about_ca_topic_score_codex":0.00006722984,"about_ca_topic_score_gemma":0.00029670275,"teacher_disagreement_score":0.6518031,"about_ca_system_score_codex":0.000030377934,"about_ca_system_score_gemma":0.00011369829,"threshold_uncertainty_score":0.4562105},"labels":[],"label_agreement":null},{"id":"W1972617451","doi":"10.1080/07408170601181674","title":"The no-wait two-machine flow shop scheduling problem with convex resource-dependent processing times","year":2007,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Flow shop scheduling; Regular polygon; Scheduling (production processes); Computer science; Mathematical optimization; Job shop scheduling; Operations research; Mathematics; Schedule; Geometry; Operating system","score_opus":0.006775525593504752,"score_gpt":0.21714861713138117,"score_spread":0.21037309153787642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972617451","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014366218,0.00074784935,0.98646057,0.0002712518,0.00021248826,0.00023125076,0.00000923542,0.0008170075,0.0098137185],"genre_scores_gemma":[0.71831757,0.00007062423,0.27920607,0.000065927925,0.00020232536,0.000043705735,0.000016254317,0.00010489776,0.0019726162],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998812,0.000018963654,0.000296942,0.00021005729,0.0002673402,0.00039470062],"domain_scores_gemma":[0.9993695,0.00012263503,0.0000397327,0.00021509218,0.00012129834,0.00013174655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003895977,0.00020836618,0.0001532939,0.00009724323,0.00062143395,0.0001588944,0.000163344,0.00007985536,0.00015324018],"category_scores_gemma":[0.000009166342,0.00015403422,0.000058054786,0.00035322746,0.00007552838,0.00017223645,0.0000032637276,0.00043642963,0.00006679717],"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":[0.00004412946,0.000027919881,0.000023509137,0.000031326043,0.00006089591,0.000005821389,0.00046088875,0.9575027,0.00016817189,0.000022845226,0.000016299005,0.04163547],"study_design_scores_gemma":[0.0006983027,0.00003252601,0.00001912558,0.00007301457,0.00005954205,0.000039925875,0.00051632506,0.9928672,0.002267184,0.000024308814,0.0031530096,0.00024955987],"about_ca_topic_score_codex":0.000013887565,"about_ca_topic_score_gemma":0.0001487613,"teacher_disagreement_score":0.716881,"about_ca_system_score_codex":0.00006851092,"about_ca_system_score_gemma":0.000044732613,"threshold_uncertainty_score":0.62813336},"labels":[],"label_agreement":null},{"id":"W1974509751","doi":"10.1080/07408170108936863","title":"Application of a weighted sum of order<i>p</i>to distance estimation","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Norm (philosophy); Mathematics; Generalization; Mathematical optimization; Applied mathematics; Goodness of fit; Function (biology); Statistics; Algorithm; Mathematical analysis","score_opus":0.07808754398730662,"score_gpt":0.40373759060787906,"score_spread":0.32565004662057245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974509751","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":[0.085286036,0.00003016118,0.91277,0.00059425674,0.00017777199,0.00031520272,0.000059492333,0.000037785525,0.00072934164],"genre_scores_gemma":[0.92945766,0.00000833357,0.069994375,0.00004465041,0.000014471598,0.00004081888,0.000004561216,0.000011230483,0.00042390163],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99750036,0.00008832144,0.0009303271,0.00036732524,0.0009495701,0.00016407964],"domain_scores_gemma":[0.9972101,0.0007734399,0.00030208152,0.0007290283,0.00088746287,0.0000978882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007804432,0.0001173113,0.00029351717,0.0004433233,0.00010963502,0.000044145156,0.00047187306,0.00006763163,0.0006487025],"category_scores_gemma":[0.00049119553,0.000101326725,0.000095385905,0.0030641416,0.00008030202,0.00032083943,0.0000097288885,0.00008487782,0.00014911943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037035384,0.00047765338,0.0020602667,0.000019945039,0.000027722237,0.0000024558299,0.0015260153,0.05434115,0.057400893,0.0024136633,0.0005656553,0.8807942],"study_design_scores_gemma":[0.0012409057,0.00013971925,0.029452888,0.00009438909,0.00006545715,0.000022756964,0.0005954167,0.8682964,0.022390887,0.026387576,0.05092303,0.00039058426],"about_ca_topic_score_codex":0.00010493533,"about_ca_topic_score_gemma":0.0002880834,"teacher_disagreement_score":0.88040364,"about_ca_system_score_codex":0.000032865402,"about_ca_system_score_gemma":0.000057652265,"threshold_uncertainty_score":0.71028376},"labels":[],"label_agreement":null},{"id":"W1980858669","doi":"10.1080/07408170590516764","title":"Complex assembly variant design in agile manufacturing. Part I: System architecture and assembly modeling methodology","year":2004,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"National Science Foundation","keywords":"Assembly modelling; Agile manufacturing; Design for assembly; Component (thermodynamics); Agile software development; Computer science; Graph; Engineering; Architecture; Systems engineering; Engineering drawing; Product (mathematics); Software engineering; Theoretical computer science; Mechanical engineering","score_opus":0.06411201148702918,"score_gpt":0.25448641639122976,"score_spread":0.1903744049042006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980858669","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03609109,0.00014263253,0.96232843,0.00011691878,0.00022236907,0.0002453201,0.000011374495,0.0004046514,0.00043722003],"genre_scores_gemma":[0.8964951,0.000091778704,0.10322534,0.00002269495,0.000039562015,0.000057760888,0.000008715903,0.000039894574,0.000019124625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989644,0.00008104023,0.00029101677,0.00025537718,0.000104026025,0.0003041166],"domain_scores_gemma":[0.99960184,0.00010115267,0.00002682172,0.00016456908,0.000017778675,0.00008784421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026227234,0.0002083431,0.00026405856,0.00020749436,0.00012977059,0.000054036824,0.00009955031,0.00014542724,0.000031534208],"category_scores_gemma":[0.0000055446912,0.0002098576,0.000046465335,0.0001113961,0.00001814992,0.00014377266,0.0000043774894,0.00029775634,0.000005562495],"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":[0.000016481308,0.000018079938,5.312637e-7,0.00020245193,0.000030440817,0.000016786751,0.00048488737,0.99468386,0.00079512736,0.00011862727,0.000003667143,0.003629035],"study_design_scores_gemma":[0.00072738534,0.00003214492,0.000115809526,0.00012310267,0.00005057303,0.00013236348,0.00018177765,0.98069066,0.016741138,0.00070261915,0.00020747754,0.00029493278],"about_ca_topic_score_codex":0.00015911165,"about_ca_topic_score_gemma":0.00018295745,"teacher_disagreement_score":0.860404,"about_ca_system_score_codex":0.000116461335,"about_ca_system_score_gemma":0.000024296394,"threshold_uncertainty_score":0.8557744},"labels":[],"label_agreement":null},{"id":"W1989497202","doi":"10.1080/0740817x.2012.706734","title":"Learning and forgetting effects on maintenance outsourcing","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Forgetting; Outsourcing; Business; Computer science; Operations management; Process management; Industrial organization; Engineering; Marketing; Psychology; Cognitive psychology","score_opus":0.002355930984310226,"score_gpt":0.1722965969871512,"score_spread":0.16994066600284097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989497202","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":[0.15235645,0.0000654457,0.84067893,0.0004112324,0.00026504105,0.00028813037,8.510924e-7,0.00047746138,0.0054564574],"genre_scores_gemma":[0.99629855,0.000119914876,0.0028159933,0.000044768243,0.000029109964,0.000062841595,0.0000012999412,0.000022145838,0.0006053828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995303,0.000014950119,0.000102039136,0.00011478564,0.000051069434,0.00018681864],"domain_scores_gemma":[0.9997369,0.00010625135,0.000011851644,0.00006930659,0.000024233916,0.000051480507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058665217,0.000091971444,0.00008898337,0.00004769827,0.00013642867,0.000040120973,0.000028436361,0.000049440117,0.000048569047],"category_scores_gemma":[0.000028251954,0.00008747643,0.0000321441,0.00008651821,0.000018813098,0.00018194492,0.0000013308085,0.00021110006,0.000041549065],"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":[0.0000038369603,0.000010534662,0.00017048512,0.00013321971,0.000019646282,0.0000010481511,0.00064809935,0.8673023,0.0052945907,0.00009241888,0.00013484182,0.126189],"study_design_scores_gemma":[0.0005614707,0.00012231113,0.003601546,0.00025151126,0.00002905597,0.000011689915,0.0005110754,0.9785736,0.0112230005,0.0006809906,0.004107195,0.00032651032],"about_ca_topic_score_codex":0.000021627267,"about_ca_topic_score_gemma":0.000006345562,"teacher_disagreement_score":0.8439421,"about_ca_system_score_codex":0.000035191173,"about_ca_system_score_gemma":0.000002793897,"threshold_uncertainty_score":0.35671854},"labels":[],"label_agreement":null},{"id":"W2001297076","doi":"10.1080/07408170309342346","title":"Optimal production control problem in stochastic multiple-product multiple-machine manufacturing systems","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec; Université du Québec à Montréal","funders":"","keywords":"Parameterized complexity; Mathematical optimization; Production (economics); Optimal control; Product (mathematics); Production control; Computer science; Product type; Control variable; Control (management); Holding cost; Engineering; Mathematics; Algorithm; Economics","score_opus":0.05826688806782515,"score_gpt":0.34156316557006666,"score_spread":0.2832962775022415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001297076","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":[0.042248745,0.0003726997,0.9538223,0.00022862213,0.001816708,0.001086928,0.00007007633,0.00015220973,0.00020171954],"genre_scores_gemma":[0.9817741,0.000006276783,0.0169848,0.000009448283,0.00013461807,0.00027225024,0.000003013104,0.000039772767,0.0007757255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960011,0.00032376862,0.0010461848,0.0010417984,0.0009887132,0.00059838814],"domain_scores_gemma":[0.9965988,0.002116171,0.00022713598,0.00060056185,0.0002528315,0.0002045282],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015087451,0.00031620503,0.00048725182,0.000459222,0.0004254511,0.0001849147,0.00035909208,0.0000894779,0.00009013658],"category_scores_gemma":[0.0039785225,0.0002725115,0.00010349609,0.00070514064,0.00013849833,0.00083831046,0.0000069778794,0.000590788,0.00011491003],"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":[0.00012217298,0.00016123384,0.0008968005,0.000024504658,0.000020530346,0.0000102005915,0.0002874518,0.98694706,0.001549368,0.000109778994,0.000012258913,0.009858622],"study_design_scores_gemma":[0.011462449,0.0003881801,0.016901493,0.00045236386,0.00023892295,0.0004535513,0.004736778,0.9079357,0.036916748,0.011359907,0.006583542,0.002570416],"about_ca_topic_score_codex":0.00016023904,"about_ca_topic_score_gemma":0.00025941775,"teacher_disagreement_score":0.93952537,"about_ca_system_score_codex":0.00020812401,"about_ca_system_score_gemma":0.00008168628,"threshold_uncertainty_score":0.9999727},"labels":[],"label_agreement":null},{"id":"W2006601554","doi":"10.1080/07408170903394355","title":"Cooperative cover location problems: The planar case","year":2009,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":74,"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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cover (algebra); Aggregate (composite); Heuristic; Facility location problem; Point (geometry); Euclidean geometry; Planar; Mathematical optimization; Operations research; Computer science; Point location; Mathematics; Engineering; Geometry","score_opus":0.027418900586081936,"score_gpt":0.23386521819956319,"score_spread":0.20644631761348126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006601554","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":[0.037686843,0.0002520704,0.81480056,0.06572971,0.0012628065,0.0019050919,0.000019322779,0.0006378902,0.07770571],"genre_scores_gemma":[0.99324286,0.00001657751,0.000040850984,0.0039103976,0.00014912938,0.00004524182,0.000021303345,0.000006623337,0.0025670258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993315,0.000010716372,0.00019251803,0.0001747366,0.00013419549,0.00015635039],"domain_scores_gemma":[0.9995741,0.000010734421,0.000030018015,0.00021903875,0.00015642015,0.000009693148],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00016591395,0.00011310187,0.00007724817,0.00009145359,0.0005396891,0.00013855385,0.00011333823,0.000031464973,0.0012197584],"category_scores_gemma":[0.000012581836,0.000085004634,0.000047570105,0.00055513816,0.000036887388,0.0007086273,0.00000252702,0.00010814482,0.0010924031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013080597,0.0012013514,0.000116613664,0.00029972833,0.0002321453,0.0001126537,0.0023865863,0.7448034,0.00045839444,0.10846637,0.066660754,0.075131156],"study_design_scores_gemma":[0.0010756018,0.000051427498,0.004621471,0.0000476474,0.00029515446,0.00006768672,0.0026946766,0.15540278,0.000080687634,0.0026180157,0.8324587,0.0005861884],"about_ca_topic_score_codex":0.0010267239,"about_ca_topic_score_gemma":0.0019678753,"teacher_disagreement_score":0.95555604,"about_ca_system_score_codex":0.00002806985,"about_ca_system_score_gemma":0.000014821412,"threshold_uncertainty_score":0.9996933},"labels":[],"label_agreement":null},{"id":"W2016144758","doi":"10.1080/07408170590899643","title":"Building performance standards into data envelopment analysis structures","year":2005,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Set (abstract data type); Efficiency; Sample (material); Computer science; Operations research; Service (business); A priori and a posteriori; Engineering; Mathematical optimization; Mathematics; Economics; Statistics","score_opus":0.0843991982780189,"score_gpt":0.4185390339493429,"score_spread":0.334139835671324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016144758","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":[0.23117644,0.00016121812,0.7662402,0.0013014381,0.00016055735,0.00006562053,0.000121994766,0.00006960325,0.00070292415],"genre_scores_gemma":[0.93900114,0.000054247746,0.060181215,0.000132649,0.00007051586,0.0000046758905,0.000015788934,0.000009688942,0.0005300682],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99567646,0.00012424533,0.00076136884,0.00081572146,0.0023038662,0.00031834043],"domain_scores_gemma":[0.9971355,0.00037644018,0.00017324695,0.0018058162,0.00036753327,0.00014141407],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032152755,0.0001840806,0.00037639195,0.001139513,0.0007912361,0.00035737685,0.0017456124,0.00007536821,0.0025830567],"category_scores_gemma":[0.0002902807,0.00014421232,0.0002188942,0.0043762377,0.00015325817,0.0009875473,0.000052331874,0.00023286279,0.000097041346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022692293,0.00007422494,0.0012361933,0.0000028098332,0.00047833213,0.0000016746,0.0011364482,0.46846765,0.0006844395,0.00020823552,0.0007655412,0.52692175],"study_design_scores_gemma":[0.00035421725,0.000037060527,0.024208324,0.000010503921,0.0014073548,0.000008557476,0.00045675898,0.66747916,0.0058860336,0.0019251653,0.29773128,0.00049556553],"about_ca_topic_score_codex":0.00012563397,"about_ca_topic_score_gemma":0.0017947365,"teacher_disagreement_score":0.7078247,"about_ca_system_score_codex":0.00021244629,"about_ca_system_score_gemma":0.00024639355,"threshold_uncertainty_score":0.99832875},"labels":[],"label_agreement":null},{"id":"W2017962074","doi":"10.1080/07408170903113789","title":"Can flexibility be constraining?","year":2009,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Staffing; Flexibility (engineering); Workforce; Robustness (evolution); Operations management; Business; Industrial organization; Computer science; Economics; Operations research; Microeconomics; Engineering; Management; Economic growth; Chemistry","score_opus":0.22849023704179974,"score_gpt":0.42513271523553875,"score_spread":0.196642478193739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017962074","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":[0.24154739,0.00014393953,0.61949486,0.088338785,0.001425024,0.00030888195,0.0002574071,0.00069078495,0.047792897],"genre_scores_gemma":[0.9904636,0.0000042600645,0.0053476086,0.0010188045,0.000060901562,0.0000058240057,0.000003463574,0.000005473827,0.0030900214],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980139,0.00011415472,0.00046161198,0.0004404965,0.00062920625,0.0003405904],"domain_scores_gemma":[0.99820715,0.0006398785,0.00007699153,0.0006369815,0.0002251732,0.00021383338],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001435258,0.00012779373,0.00021795601,0.00022936672,0.00055317173,0.00017573006,0.00037215996,0.000090112364,0.0019958029],"category_scores_gemma":[0.00061377883,0.00010689384,0.00021727048,0.0010056794,0.00019663438,0.00018889408,0.0000025472243,0.00026912268,0.00021961317],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019986717,0.002025625,0.0027996253,0.000005767068,0.00021105792,0.00004256961,0.009275695,0.0527327,0.0048240563,0.049893137,0.013167544,0.8648223],"study_design_scores_gemma":[0.0029504076,0.00065495895,0.09935578,0.00004782202,0.0003390247,0.00026103348,0.0064889425,0.03701965,0.0072443453,0.7341139,0.11000536,0.0015188184],"about_ca_topic_score_codex":0.000078411285,"about_ca_topic_score_gemma":0.00022162624,"teacher_disagreement_score":0.86330354,"about_ca_system_score_codex":0.000039493232,"about_ca_system_score_gemma":0.00020799515,"threshold_uncertainty_score":0.9989165},"labels":[],"label_agreement":null},{"id":"W2020404569","doi":"10.1080/07408170701246641","title":"Integrated design of supply chain networks with three echelons, multiple commodities and technology selection","year":2007,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Waterloo","funders":"","keywords":"Mathematical optimization; Cutting-plane method; Heuristic; Supply chain; Selection (genetic algorithm); Point (geometry); Relaxation (psychology); Integer programming; Computer science; Upper and lower bounds; Linear programming relaxation; Decomposition; Mathematics","score_opus":0.02056806816116851,"score_gpt":0.20478072168054065,"score_spread":0.18421265351937213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020404569","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":[0.05561284,0.00006372369,0.9424762,0.0008503571,0.0001162468,0.00033311613,0.0000028458232,0.00019466446,0.000349992],"genre_scores_gemma":[0.99690104,0.000028847711,0.0027181956,0.000091446855,0.000038765662,0.0000315296,0.0000173099,0.000012485779,0.00016037395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993222,0.0000067255833,0.0002177655,0.00016444086,0.00009731122,0.00019157422],"domain_scores_gemma":[0.99962115,0.000032178443,0.00004881879,0.0001206012,0.00016728637,0.0000099614535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030781687,0.000121774676,0.00013218482,0.00041854795,0.00020660477,0.000031946543,0.000084394116,0.00007982936,0.00016579227],"category_scores_gemma":[0.000013549816,0.000109187575,0.000021600594,0.00096069183,0.00012398041,0.00030524045,0.0000067235846,0.00014953893,0.000008357258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012943881,0.0010168127,0.104071096,0.0005644889,0.0005754307,0.000008770955,0.0003848795,0.6600805,0.0032073837,0.020983404,0.0023558899,0.20545697],"study_design_scores_gemma":[0.0013736829,0.0000998457,0.029231269,0.00008142171,0.00019283977,0.0000058160535,0.0024366411,0.95354503,0.0010243187,0.0010224011,0.010582136,0.00040458151],"about_ca_topic_score_codex":0.001876153,"about_ca_topic_score_gemma":0.021496948,"teacher_disagreement_score":0.94128823,"about_ca_system_score_codex":0.000024213603,"about_ca_system_score_gemma":0.000013153182,"threshold_uncertainty_score":0.99635816},"labels":[],"label_agreement":null},{"id":"W2020467142","doi":"10.1080/07408170304361","title":"Output deterioration with input reduction in data envelopment analysis","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Reduction (mathematics); Context (archaeology); Productivity; Operations research; Process (computing); Computer science; Resource (disambiguation); Measure (data warehouse); Engineering; Mathematics; Mathematical optimization; Economics; Data mining; Geography","score_opus":0.1425533021162724,"score_gpt":0.37541758546269044,"score_spread":0.23286428334641804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020467142","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":[0.20335107,0.000038574883,0.79467034,0.00063245127,0.00015356512,0.0001246831,0.000025820329,0.000037096972,0.00096636795],"genre_scores_gemma":[0.99119055,0.000015622025,0.007366925,0.00003479253,0.000011344253,0.000013770002,0.000029464809,0.000008137678,0.0013294144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99708784,0.00032407514,0.00065278367,0.00074998784,0.00095711026,0.0002282348],"domain_scores_gemma":[0.9980971,0.00018081753,0.00016949678,0.0012990733,0.00017424687,0.0000792407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023704534,0.0001409579,0.00029923083,0.0014283215,0.00025750563,0.00022615855,0.0005369255,0.000067805704,0.00051590416],"category_scores_gemma":[0.00020919234,0.000108822205,0.00009638021,0.0068733115,0.00009832543,0.0007952657,0.000008374923,0.0001687666,0.00008410841],"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":[0.00017200033,0.0012443409,0.015278918,0.0000067844853,0.0010591518,0.000035168072,0.0062659425,0.83810896,0.0045486954,0.0005439531,0.0006395305,0.13209657],"study_design_scores_gemma":[0.0045855767,0.0004924047,0.27049172,0.000106347485,0.0070165955,0.00024654873,0.017334824,0.55888087,0.0152497385,0.0073339506,0.11507007,0.0031913351],"about_ca_topic_score_codex":0.0001555288,"about_ca_topic_score_gemma":0.0051115416,"teacher_disagreement_score":0.7878395,"about_ca_system_score_codex":0.00010637546,"about_ca_system_score_gemma":0.00018234679,"threshold_uncertainty_score":0.5648789},"labels":[],"label_agreement":null},{"id":"W2024245239","doi":"10.1080/0740817x.2014.929363","title":"Effects of subsystem mission time on reliability allocation","year":2014,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Konkuk University","keywords":"Failure rate; Reliability engineering; Reliability (semiconductor); Order (exchange); Factor (programming language); Engineering; Computer science; Business","score_opus":0.0025546932503882846,"score_gpt":0.17398111095123797,"score_spread":0.17142641770084968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024245239","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":[0.16839561,0.000022238799,0.82760465,0.00013920978,0.00032019155,0.000315238,0.0000034092213,0.00027697455,0.0029224814],"genre_scores_gemma":[0.9986098,0.00003378719,0.0010337827,0.000010834033,0.000019743684,0.000017230812,0.000005578507,0.000015181672,0.00025408147],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994497,0.0000477047,0.00018350985,0.000119748096,0.00009574618,0.00010360758],"domain_scores_gemma":[0.99951357,0.0001633912,0.000022515509,0.00020372077,0.000052179927,0.000044614237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015453152,0.00008641784,0.00012819238,0.000050672006,0.00004548333,0.0000062487675,0.00005572776,0.00007990717,0.000047791636],"category_scores_gemma":[0.000044815086,0.00008043666,0.00006108578,0.00013307566,0.00002446473,0.000093008195,7.1820716e-7,0.00008871707,0.000058165144],"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":[0.000022290553,0.00008241148,0.0000065413406,0.00043113087,0.000010914892,1.0001502e-7,0.00014403781,0.95439273,0.0383652,0.0001571034,0.00014716659,0.006240381],"study_design_scores_gemma":[0.00050832256,0.00014503901,0.0017662296,0.0002121808,0.000050654915,0.0000013208393,0.000012366291,0.76765835,0.22686721,0.00040875643,0.0021958249,0.00017374466],"about_ca_topic_score_codex":0.000010940309,"about_ca_topic_score_gemma":0.000002156261,"teacher_disagreement_score":0.8302142,"about_ca_system_score_codex":0.00005716487,"about_ca_system_score_gemma":0.0000072209014,"threshold_uncertainty_score":0.32801116},"labels":[],"label_agreement":null},{"id":"W2026087586","doi":"10.1080/0740817x.2013.770188","title":"Multistate degradation and supervised estimation methods for a condition-monitored device","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":35,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Correctness; Consistency (knowledge bases); Nonparametric statistics; Reliability (semiconductor); Parametric statistics; Degradation (telecommunications); Process (computing); Computer science; Stochastic process; Maximum likelihood; Estimation; Markov chain; Algorithm; Mathematics; Engineering; Statistics; Artificial intelligence; Machine learning","score_opus":0.013895474305160319,"score_gpt":0.2948348266960182,"score_spread":0.2809393523908579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026087586","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":[0.022113424,0.000051843923,0.9764406,0.0002765987,0.00019229527,0.0005909435,0.000025202125,0.00021129538,0.00009777683],"genre_scores_gemma":[0.49134883,0.00008391151,0.50793654,0.000017313645,0.000012126977,0.0004142361,0.000081160426,0.000016566857,0.00008934692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995545,0.000024399324,0.00015883455,0.000110418754,0.000034204542,0.0001175993],"domain_scores_gemma":[0.9995994,0.00015460218,0.000015959242,0.00008718361,0.00009399153,0.000048853883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008859141,0.00008619985,0.00009028814,0.000057566736,0.00011985943,0.000053674692,0.000029024726,0.00005837032,0.00006842],"category_scores_gemma":[0.000025818357,0.000089666064,0.00003259319,0.00010163061,0.000027930884,0.0005018581,6.680375e-7,0.000057295594,0.000009973008],"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":[0.000011216364,0.00003101315,0.000011780951,0.00017479828,0.000041314517,7.4470826e-8,0.00051747664,0.5840734,0.015991963,0.0001862897,0.00019098666,0.39876965],"study_design_scores_gemma":[0.00039334365,0.000018316,0.0008768506,0.000015003501,0.000035495472,0.0000022863424,0.00012138325,0.99064493,0.0054326835,0.001904038,0.00045144893,0.000104189894],"about_ca_topic_score_codex":0.00007313323,"about_ca_topic_score_gemma":0.000018541838,"teacher_disagreement_score":0.4692354,"about_ca_system_score_codex":0.000040919786,"about_ca_system_score_gemma":0.0000084219055,"threshold_uncertainty_score":0.36564758},"labels":[],"label_agreement":null},{"id":"W2031966660","doi":"10.1080/07408170500288190","title":"Location of congested capacitated facilities with distance-sensitive demand","year":2006,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Facility location problem; Mathematical optimization; Heuristic; 1-center problem; Node (physics); Limit (mathematics); Computer science; Function (biology); Mathematics; Engineering","score_opus":0.014280625275187158,"score_gpt":0.19457320895641092,"score_spread":0.18029258368122375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031966660","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":[0.32130924,0.000075631804,0.66024417,0.0009502946,0.00023179421,0.00042811615,0.000029288374,0.0002042036,0.016527293],"genre_scores_gemma":[0.9965996,0.0000052390037,0.00012125751,0.000087978,0.0000474604,0.000029153118,0.00006256949,0.000009554305,0.0030371677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99925864,0.000008553037,0.00024339088,0.00017098166,0.00017251304,0.00014590507],"domain_scores_gemma":[0.99932724,0.000013456262,0.000057002293,0.00015567233,0.0004376877,0.00000893525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008976039,0.00011973037,0.00013241192,0.00015258235,0.0001475488,0.000040528896,0.000060458082,0.00003207266,0.00032018102],"category_scores_gemma":[0.000009910028,0.00010880283,0.000035480003,0.0006480424,0.00012831074,0.0005371886,0.0000026494563,0.00005859061,0.00007297271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012576747,0.0019374045,0.009560089,0.0054022297,0.0006619677,0.000018824938,0.0022573706,0.812451,0.005752757,0.1470971,0.006018117,0.007585464],"study_design_scores_gemma":[0.011907797,0.0002949414,0.43990907,0.0012156939,0.002064323,0.00001515635,0.040261317,0.20414878,0.017561458,0.008227487,0.27038655,0.004007399],"about_ca_topic_score_codex":0.007425606,"about_ca_topic_score_gemma":0.016048927,"teacher_disagreement_score":0.6752904,"about_ca_system_score_codex":0.000026546422,"about_ca_system_score_gemma":0.000020649677,"threshold_uncertainty_score":0.999184},"labels":[],"label_agreement":null},{"id":"W2035028561","doi":"10.1080/07408170490257871","title":"Exact algorithms for the job sequencing and tool switching problem","year":2004,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada Research Chairs","keywords":"Computer science; Algorithm","score_opus":0.019647533044199077,"score_gpt":0.23742910148012267,"score_spread":0.21778156843592358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035028561","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008135054,0.0003148889,0.9899989,0.0004319248,0.00028708388,0.00026741563,0.000012246004,0.00034069552,0.00021181794],"genre_scores_gemma":[0.6572462,0.0002007012,0.3420937,0.00006747956,0.00011397639,0.00012915266,0.0000029788707,0.00004051513,0.00010532564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994902,0.000004814538,0.00014370128,0.000117091135,0.000071566385,0.00017261221],"domain_scores_gemma":[0.99970925,0.000092645474,0.000012517574,0.00011430865,0.00002895433,0.00004235105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011526063,0.0001055563,0.00008468035,0.00004643983,0.0003092152,0.000073124946,0.000064248336,0.000052603413,0.00002072726],"category_scores_gemma":[0.000006257692,0.00008529514,0.000052245727,0.00013046752,0.000017659097,0.00015555888,0.000001306782,0.00015605726,0.0000047829903],"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":[0.00000233039,0.0000047530434,0.0000025344764,0.00002351066,0.00004068756,6.007513e-7,0.00081593666,0.960956,0.0006603062,0.00014348945,0.0000051739603,0.03734472],"study_design_scores_gemma":[0.00083696103,0.000026620408,0.000100198624,0.000045542016,0.00008391601,0.00004266478,0.0007283769,0.9932231,0.0031598627,0.0009243352,0.00060186576,0.0002265988],"about_ca_topic_score_codex":0.00004695871,"about_ca_topic_score_gemma":0.000037681744,"teacher_disagreement_score":0.6491111,"about_ca_system_score_codex":0.00007492426,"about_ca_system_score_gemma":0.000030542302,"threshold_uncertainty_score":0.3478235},"labels":[],"label_agreement":null},{"id":"W2035906079","doi":"10.1080/07408170304360","title":"Approximating Performance Measures for a Network of Unreliable Machines","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Downtime; Queue; Service (business); Computer science; Center (category theory); Operations research; Reliability engineering; Engineering; Computer network; Economics","score_opus":0.01775968097802655,"score_gpt":0.22839041686639497,"score_spread":0.21063073588836842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035906079","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":[0.0292409,0.00010817976,0.96141547,0.000084577136,0.00024104664,0.00021842115,0.0000028658214,0.00010901337,0.008579521],"genre_scores_gemma":[0.9832907,0.000008627379,0.01579538,0.00012686838,0.00017142671,0.00006634553,0.0000050254826,0.000023683575,0.00051199907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925786,0.000009926119,0.00026008973,0.00015303801,0.00010326344,0.0002158344],"domain_scores_gemma":[0.9994289,0.000097273274,0.0001537552,0.00016708161,0.00014572401,0.000007255672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046801957,0.00011302494,0.00018841896,0.00008055657,0.00034603168,0.000034103105,0.000100753714,0.000035897352,0.00016526176],"category_scores_gemma":[0.000102541766,0.00010714813,0.00012587757,0.00051535974,0.00003994421,0.00056977395,0.0000027151516,0.000078910205,0.000012659254],"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":[0.000095690055,0.00010915423,0.0011594321,0.00043704145,0.00013654726,3.0137252e-7,0.000059396294,0.918763,0.0008991317,0.047881518,0.00021667121,0.030242123],"study_design_scores_gemma":[0.0017350181,0.000042239702,0.0003324862,0.00030658985,0.0010843746,0.000005372468,0.00040390823,0.72886455,0.0036143127,0.121536836,0.14126924,0.0008050976],"about_ca_topic_score_codex":0.00003371298,"about_ca_topic_score_gemma":0.00004544759,"teacher_disagreement_score":0.95404977,"about_ca_system_score_codex":0.00001374742,"about_ca_system_score_gemma":0.000012382548,"threshold_uncertainty_score":0.4369374},"labels":[],"label_agreement":null},{"id":"W2047904670","doi":"10.1080/07408170701744819","title":"Heuristics for allocation of reconfigurable resources in a serial line with reliability considerations","year":2008,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":34,"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; National Science Council; Division of Civil, Mechanical and Manufacturing Innovation; Engineering Research Centers; National Science Foundation","keywords":"Heuristics; Server; Computer science; Reliability (semiconductor); Monotone polygon; Throughput; Line (geometry); Distributed computing; Resource allocation; Heuristic; Mathematical optimization; Computer network; Operating system; Mathematics; Artificial intelligence","score_opus":0.023720848011566275,"score_gpt":0.23452686709923432,"score_spread":0.21080601908766805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047904670","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":[0.6048791,0.000017582062,0.39086473,0.0014708837,0.000113572925,0.00046902962,0.000024619632,0.00009670875,0.0020638134],"genre_scores_gemma":[0.9948641,0.000007346259,0.004562001,0.00010441261,0.000114347255,0.000065842665,0.0000193107,0.000013559529,0.00024908796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933314,0.000013401854,0.0002840609,0.00017211503,0.000080343336,0.00011693613],"domain_scores_gemma":[0.99923617,0.00020518746,0.00012873851,0.00018221834,0.00024041804,0.0000072523835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021474427,0.00008701835,0.00017317102,0.00016594215,0.00023254608,0.000019900068,0.00005100768,0.000041676234,0.00018453288],"category_scores_gemma":[0.00017671831,0.00008260538,0.000054967535,0.00036152496,0.00010852412,0.00044598067,0.0000014606698,0.00008093972,0.0000051836387],"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":[0.0009844393,0.0005680472,0.0012232943,0.00025531187,0.00008850871,0.0000061111773,0.0006843724,0.9795724,0.0034298294,0.0121282255,0.00022493451,0.0008345052],"study_design_scores_gemma":[0.016626239,0.0005911559,0.017330524,0.0006871338,0.0024335354,0.00008540552,0.0041912715,0.48785448,0.030349078,0.37360498,0.06356303,0.0026831867],"about_ca_topic_score_codex":0.00036091649,"about_ca_topic_score_gemma":0.0016904512,"teacher_disagreement_score":0.49171796,"about_ca_system_score_codex":0.000023677432,"about_ca_system_score_gemma":0.00003202743,"threshold_uncertainty_score":0.33685496},"labels":[],"label_agreement":null},{"id":"W2048144767","doi":"10.1080/07408170701275343","title":"Approximate mean waiting time in a <i>GI</i> / <i>D</i> /1 queue with autocorrelated times to failures","year":2007,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The King's University; University of Toronto; University of King's College","funders":"University of Toronto; National Science Foundation","keywords":"Queue; Autocorrelation; Renewal theory; Process (computing); Computer science; Poisson distribution; Poisson process; Server; Mathematics; Real-time computing; Mathematical optimization; Statistics; Computer network","score_opus":0.006016776113520578,"score_gpt":0.20880401747776672,"score_spread":0.20278724136424614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048144767","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":[0.25480205,0.000036975212,0.69692653,0.00312336,0.00017142305,0.001154324,0.000009712277,0.0013503967,0.042425215],"genre_scores_gemma":[0.99423033,9.1496935e-7,0.002659275,0.00100913,0.00014780033,0.000053339652,0.000016054311,0.000058628306,0.0018245035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985371,0.00001562819,0.00036250072,0.00038407635,0.00021174553,0.00048893184],"domain_scores_gemma":[0.9993642,0.00010873733,0.00012368216,0.00027013558,0.00009842859,0.00003481852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006034324,0.00024133053,0.00027277874,0.0005811242,0.0002721339,0.00012590895,0.00020537758,0.000078431156,0.0005808119],"category_scores_gemma":[0.00002789145,0.00022246475,0.00009208694,0.0017477985,0.00005815084,0.0009694949,0.000014004863,0.00027987643,0.00051912246],"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":[0.0018889117,0.0009544927,0.0013264176,0.0003012998,0.0005360445,0.00035053008,0.0023571867,0.8946834,0.022017306,0.0313146,0.0009972681,0.043272547],"study_design_scores_gemma":[0.007049834,0.00017662131,0.001906412,0.0013795178,0.0017765322,0.000087892295,0.005691949,0.81020814,0.010715862,0.021804921,0.13474962,0.004452712],"about_ca_topic_score_codex":0.0005910268,"about_ca_topic_score_gemma":0.0028802,"teacher_disagreement_score":0.7394283,"about_ca_system_score_codex":0.00006831817,"about_ca_system_score_gemma":0.000017265384,"threshold_uncertainty_score":0.90718496},"labels":[],"label_agreement":null},{"id":"W2048468995","doi":"10.1080/0740817x.2013.770185","title":"A pseudo-likelihood analysis for incomplete warranty data with a time usage rate variable and production counts","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo","keywords":"Warranty; Failure rate; Reliability (semiconductor); Reliability engineering; Computer science; Product (mathematics); Missing data; Production (economics); Variable (mathematics); Econometrics; Statistics; Engineering; Mathematics; Economics","score_opus":0.011579722917857124,"score_gpt":0.20032744114857773,"score_spread":0.18874771823072062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048468995","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052203205,0.00002213057,0.99312115,0.0002092952,0.000099537945,0.00036043712,0.0000962829,0.00011901761,0.0007518477],"genre_scores_gemma":[0.9130092,0.00023246718,0.083982445,0.000039114366,0.00006453027,0.00024846298,0.00033228713,0.000039320952,0.0020521677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957275,0.000010034454,0.00009403604,0.00016557642,0.00004177753,0.00011584344],"domain_scores_gemma":[0.99961674,0.000024222656,0.000013328328,0.00025556414,0.000056836536,0.000033287208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117318436,0.00007030227,0.000105289226,0.00006126856,0.000079700876,0.00003620365,0.00005796086,0.000032543798,0.00028421782],"category_scores_gemma":[0.000008419352,0.000060729417,0.00001787229,0.0002915893,0.000023821167,0.00035136205,0.0000019608194,0.000053089974,0.000027935446],"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":[0.00003950416,0.00007334062,0.00007240094,0.00017085118,0.0008055434,2.8853546e-7,0.00024880795,0.9784908,0.0067818277,0.00005218249,0.0049665035,0.008297931],"study_design_scores_gemma":[0.00020449588,0.000020398667,0.0005229838,0.000012237997,0.00034611044,0.0000032547007,0.000018891706,0.9943685,0.000107338,0.0004879378,0.0037960995,0.00011177089],"about_ca_topic_score_codex":0.00005761676,"about_ca_topic_score_gemma":0.000045224144,"teacher_disagreement_score":0.9091387,"about_ca_system_score_codex":0.000018695942,"about_ca_system_score_gemma":0.000013026774,"threshold_uncertainty_score":0.31119856},"labels":[],"label_agreement":null},{"id":"W2048612773","doi":"10.1080/07408170304351","title":"Managing Demand to Optimize Production Costs","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"University of Louisville","keywords":"Production (economics); Economics; Product (mathematics); Time horizon; Demand forecasting; Microeconomics; Derived demand; Aggregate demand; Demand management; Control (management); Demand patterns; Monotone polygon; Industrial organization; Econometrics; Demand curve; Operations management; Mathematics; Monetary economics","score_opus":0.019550661433248333,"score_gpt":0.22270231800828827,"score_spread":0.20315165657503995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048612773","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":[0.028022673,0.00011794378,0.6183106,0.014161968,0.0049069137,0.0014464578,0.0000025156762,0.0007043951,0.3323266],"genre_scores_gemma":[0.98812836,0.00002255588,0.0015002706,0.0026969677,0.00041319794,0.00012201062,0.000006467476,0.000034329696,0.0070758495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99902886,0.000012819729,0.00018533465,0.00031600802,0.00017883476,0.00027811233],"domain_scores_gemma":[0.99959904,0.000010080859,0.000045958197,0.00025353764,0.00006657837,0.00002481293],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00027814787,0.00015014142,0.000120438766,0.00032933298,0.0003361337,0.00018076735,0.000118785625,0.0000332509,0.0015453381],"category_scores_gemma":[0.00002956451,0.00015616752,0.000076748605,0.0005839923,0.00002448715,0.000760493,0.000007954252,0.00009805321,0.0008265488],"study_design_candidate":"not_applicable","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":[0.00044098133,0.0020391585,0.0029889967,0.0010378126,0.000717334,0.00008709358,0.0012336681,0.4007591,0.0056618326,0.17253622,0.21791174,0.19458607],"study_design_scores_gemma":[0.00072736683,0.000017254892,0.0008720993,0.00007105792,0.0001750156,0.000006462316,0.0011909548,0.004252985,0.0012605764,0.0030094653,0.9878924,0.0005243649],"about_ca_topic_score_codex":0.00012039888,"about_ca_topic_score_gemma":0.00013089488,"teacher_disagreement_score":0.96010566,"about_ca_system_score_codex":0.0000782399,"about_ca_system_score_gemma":0.0000082665665,"threshold_uncertainty_score":0.9999514},"labels":[],"label_agreement":null},{"id":"W2050122359","doi":"10.1080/07408170802322630","title":"Probability, chance and the probability of chance","year":2008,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ryerson University","keywords":"Hierarchy; Context (archaeology); Computer science; Meaning (existential); Construct (python library); Mathematical economics; Epistemology; Mathematics","score_opus":0.32897376990663646,"score_gpt":0.3929668566305833,"score_spread":0.06399308672394682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050122359","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":[0.7087616,0.0002990273,0.28532022,0.003110315,0.00040693604,0.0008635673,0.00003795614,0.000052936746,0.0011474597],"genre_scores_gemma":[0.9913047,0.000068183566,0.007675114,0.000100580444,0.000034639663,0.000087985834,2.909412e-7,0.0000090862695,0.00071941386],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99692816,0.00040141595,0.0008345317,0.0005693263,0.0010286777,0.0002378764],"domain_scores_gemma":[0.99580324,0.0023832957,0.00023149654,0.0010564057,0.00043582328,0.00008976235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003068102,0.00015536523,0.0004148449,0.00013202184,0.00047410867,0.000065554,0.000635465,0.00007601147,0.0005709873],"category_scores_gemma":[0.0013751056,0.00009275457,0.00017955693,0.00085684453,0.0013605716,0.00036414145,0.00003489822,0.00021024322,0.00004432762],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0059452713,0.003678163,0.026096893,0.00033189068,0.00031926957,0.00004767632,0.07376498,0.0139790345,0.021103824,0.045837156,0.0028569459,0.8060389],"study_design_scores_gemma":[0.007359215,0.00024142419,0.1991862,0.00013458368,0.00009249106,0.00038279712,0.0009404172,0.04114159,0.011465983,0.71934754,0.01886986,0.0008379171],"about_ca_topic_score_codex":0.000078692916,"about_ca_topic_score_gemma":0.00022140259,"teacher_disagreement_score":0.805201,"about_ca_system_score_codex":0.00002745247,"about_ca_system_score_gemma":0.00008460946,"threshold_uncertainty_score":0.62519103},"labels":[],"label_agreement":null},{"id":"W2050606123","doi":"10.1080/07408170500245570","title":"Dual-role factors in data envelopment analysis","year":2006,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Dual (grammatical number); Revenue; Set (abstract data type); Factor (programming language); Returns to scale; Operations research; Scale (ratio); Computer science; Constant (computer programming); Dual purpose; Microeconomics; Production (economics); Business; Economics; Engineering; Mathematics; Mathematical optimization; Finance","score_opus":0.10747460659434036,"score_gpt":0.3754156533676718,"score_spread":0.2679410467733314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050606123","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":[0.55621874,0.000110963934,0.43802825,0.000988901,0.00018284658,0.0001067191,0.00016252344,0.000073960386,0.004127085],"genre_scores_gemma":[0.9957456,0.0000075847515,0.00115712,0.000034975368,0.000022387696,0.0000051972465,0.00008342109,0.000007997404,0.0029357125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99673563,0.00017519452,0.0008358271,0.0007744261,0.0011662239,0.0003126957],"domain_scores_gemma":[0.9974456,0.00072027685,0.00013942012,0.0015185117,0.00010015551,0.000076072414],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001680508,0.00015896207,0.0003802269,0.0016688389,0.0002579181,0.00021549978,0.0009579544,0.00007845593,0.0018170129],"category_scores_gemma":[0.00014554417,0.00012672364,0.00023069022,0.0070819124,0.000098660326,0.0004963315,0.000028548824,0.00018259783,0.00024410847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003153779,0.0016130639,0.17830151,0.0000030238223,0.00071598915,0.00004418301,0.0024166137,0.7852681,0.0032602856,0.00062628835,0.0026216053,0.025097802],"study_design_scores_gemma":[0.000475984,0.000018855497,0.74021137,0.0000072981948,0.0010449745,0.0000039045467,0.0023554324,0.2030298,0.0022623627,0.0046759415,0.045331627,0.00058247725],"about_ca_topic_score_codex":0.0029962987,"about_ca_topic_score_gemma":0.032066587,"teacher_disagreement_score":0.5822383,"about_ca_system_score_codex":0.000080538375,"about_ca_system_score_gemma":0.00009351324,"threshold_uncertainty_score":0.99909544},"labels":[],"label_agreement":null},{"id":"W2052630034","doi":"10.1080/07408170903468589","title":"Irreversible treatment decisions under consideration of the research and development pipeline for new therapies","year":2010,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Futures studies; Pipeline (software); Risk analysis (engineering); Markov decision process; Computer science; Quality (philosophy); Downstream (manufacturing); Management science; Operations research; Economics; Markov process; Operations management; Medicine; Engineering; Artificial intelligence; Mathematics; Epistemology","score_opus":0.6727710698119985,"score_gpt":0.49466712584283495,"score_spread":0.17810394396916357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052630034","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":[0.28110173,0.0014481148,0.6141658,0.09865319,0.001179552,0.002124207,0.00023357672,0.000038300906,0.0010555596],"genre_scores_gemma":[0.96949935,0.00019434936,0.024450207,0.0006665502,0.00011942583,0.00016123561,0.000010735366,0.000018774737,0.004879366],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99824816,0.0000738609,0.0011640765,0.0002503025,0.000066982066,0.00019663846],"domain_scores_gemma":[0.9972881,0.0019149733,0.0002869016,0.00030069822,0.00011091156,0.00009839097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003216431,0.00009268362,0.00029717595,0.0001911862,0.000598621,0.000045381694,0.00010487756,0.00009296405,0.00040081196],"category_scores_gemma":[0.0003539566,0.00008416199,0.000063440944,0.00013931784,0.00012021351,0.00016713953,0.0000055911123,0.00013691312,0.00006750774],"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":[0.00051363534,0.0029587855,0.02569635,0.00047182175,0.0013564196,5.6924813e-7,0.07859026,0.0048015383,0.0031007903,0.692352,0.08567996,0.104477875],"study_design_scores_gemma":[0.0047354335,0.00028589458,0.049154896,0.000100002384,0.00003288638,0.000014007394,0.006556155,0.004830321,0.0038902552,0.19325978,0.7366349,0.0005054897],"about_ca_topic_score_codex":0.0006660375,"about_ca_topic_score_gemma":0.0058370773,"teacher_disagreement_score":0.6883976,"about_ca_system_score_codex":0.00015820746,"about_ca_system_score_gemma":0.0004934525,"threshold_uncertainty_score":0.46041688},"labels":[],"label_agreement":null},{"id":"W2055387155","doi":"10.1080/07408170490257853","title":"An improved algorithm for solving a multi-period facility location problem","year":2004,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computation; Pruning; Feature (linguistics); Computer science; Algorithm; Mathematical optimization; Facility location problem; Period (music); Mathematics; Data mining","score_opus":0.01243745283278811,"score_gpt":0.23637301878444245,"score_spread":0.22393556595165434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055387155","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027211364,0.000065295266,0.994767,0.00007342301,0.00018424411,0.00047489154,0.00011851406,0.0015663559,0.000029115947],"genre_scores_gemma":[0.85153157,0.000015094842,0.1480806,0.000011687927,0.000017273771,0.00025403762,0.00004094923,0.000019544666,0.000029230327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993687,0.000003983917,0.000187079,0.00016825474,0.00005461361,0.00021732837],"domain_scores_gemma":[0.9996406,0.000008961095,0.000015653246,0.00019798687,0.00009062369,0.00004619169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006226099,0.00012722488,0.00010949106,0.00008598731,0.00020372396,0.00004316828,0.000104879226,0.00013003631,0.000021689146],"category_scores_gemma":[0.0000059229014,0.0001353773,0.000058591966,0.00021167393,0.000041414467,0.00028428735,0.0000011419173,0.00012217293,0.000011188967],"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":[0.0000070314914,0.00015944218,0.0000069559796,0.00012430364,0.000047827805,7.2546084e-7,0.001521252,0.5463697,0.023959672,0.00011633635,0.000008814816,0.427678],"study_design_scores_gemma":[0.0012295292,0.000086442924,0.00009721819,0.000017199465,0.000033329423,0.0000067020587,0.0009123971,0.8980554,0.09830235,0.00046705105,0.0005240166,0.00026838723],"about_ca_topic_score_codex":0.000056465447,"about_ca_topic_score_gemma":0.0002178404,"teacher_disagreement_score":0.84881043,"about_ca_system_score_codex":0.00012700302,"about_ca_system_score_gemma":0.000036600053,"threshold_uncertainty_score":0.5520526},"labels":[],"label_agreement":null},{"id":"W2057433016","doi":"10.1080/07408170600899565","title":"Data mining of resilience indicators","year":2007,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Shock (circulatory); Resilience (materials science); Warning system; Psychological resilience; Fuzzy logic; Early warning system; Financial market; Financial crisis; Economics; State (computer science); Macroeconomics; Computer science; Finance; Artificial intelligence","score_opus":0.029601304543182844,"score_gpt":0.30421487429150457,"score_spread":0.27461356974832174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057433016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008526361,0.000026781794,0.9877716,0.00023034125,0.00006180574,0.00008082277,0.00001858672,0.00020173848,0.0030820104],"genre_scores_gemma":[0.8390886,0.000014032058,0.16065222,0.000037433405,0.000011429427,0.0000062083072,0.000001988968,0.0000035168432,0.0001845494],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99928004,0.000008993587,0.00021043632,0.00023941736,0.00012655494,0.0001345637],"domain_scores_gemma":[0.9988881,0.00007223387,0.000073683215,0.00087803876,0.000027304543,0.00006064223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029888534,0.00005560916,0.00006960519,0.00018643368,0.0001447579,0.000016932858,0.0009554327,0.00004229226,0.00003250383],"category_scores_gemma":[0.0000063962652,0.000056646062,0.000030090616,0.0008709037,0.00006715522,0.00034536023,0.000029932206,0.0000847024,0.000007962043],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008979916,0.00023034192,0.0004918422,0.000015459056,0.000026467327,0.0000039515025,0.0006588511,0.00013141954,0.010857407,0.021440156,0.0008274998,0.96530765],"study_design_scores_gemma":[0.0007791126,0.0003944735,0.061373103,0.00009017032,0.000094561015,0.0001509063,0.0011160714,0.05713876,0.66601217,0.004714326,0.20706719,0.0010691704],"about_ca_topic_score_codex":0.000027803204,"about_ca_topic_score_gemma":0.000051058258,"teacher_disagreement_score":0.96423846,"about_ca_system_score_codex":0.000013308562,"about_ca_system_score_gemma":0.000039529405,"threshold_uncertainty_score":0.23099594},"labels":[],"label_agreement":null},{"id":"W2062485877","doi":"10.1080/0740817x.2012.705452","title":"Solving a stochastic facility location/fleet management problem with logic-based Benders' decomposition","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Benders' decomposition; Decomposition; Facility location problem; Fleet management; Mathematical optimization; Computer science; Operations research; Engineering; Mathematics; Telecommunications","score_opus":0.013953868420819715,"score_gpt":0.2429219763353642,"score_spread":0.22896810791454447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062485877","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033230418,0.000025038094,0.99338233,0.0002632935,0.00006554443,0.00065048155,0.000017463026,0.00073165493,0.0015411539],"genre_scores_gemma":[0.731225,0.0000023812431,0.26836517,0.000041668925,0.000007924788,0.00024763195,0.00002407988,0.00001950998,0.00006658593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991096,0.000047689504,0.00022283338,0.0002117116,0.00016052848,0.00024761521],"domain_scores_gemma":[0.9995063,0.00006703375,0.00002954016,0.0001956003,0.00011428741,0.000087216795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012598275,0.00016678055,0.00012724145,0.00013605457,0.0001966848,0.000075912845,0.00009409881,0.000062690866,0.00053374167],"category_scores_gemma":[0.000002818089,0.00016613265,0.0000410266,0.00038657937,0.000038473758,0.00025464167,0.0000022180884,0.00016084945,0.00012059728],"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":[0.0000069196785,0.00005087959,0.00001627793,0.000116569296,0.000056667726,7.747391e-7,0.00013718072,0.9928017,0.00039822212,0.0000616597,0.000057239562,0.006295882],"study_design_scores_gemma":[0.00059815584,0.0000397933,0.001482663,0.00006617533,0.000082946906,0.000006218634,0.00019598087,0.9962481,0.0006926262,0.0002838406,0.000050590465,0.00025289287],"about_ca_topic_score_codex":0.000034702534,"about_ca_topic_score_gemma":0.00003184181,"teacher_disagreement_score":0.727902,"about_ca_system_score_codex":0.00014292295,"about_ca_system_score_gemma":0.000020169817,"threshold_uncertainty_score":0.6774693},"labels":[],"label_agreement":null},{"id":"W2064506786","doi":"10.1080/0740817x.2010.540637","title":"Optimal inventory and admission policies for drop-shipping retailers serving in-store and online customers","year":2011,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Revenue; Inventory management; Business; Order (exchange); Revenue management; Perpetual inventory; Heuristic; Operations research; Microeconomics; Industrial organization; Computer science; Inventory control; Marketing; Operations management; Inventory theory; Economics; Mathematics; Finance","score_opus":0.06160643368701004,"score_gpt":0.248653751416219,"score_spread":0.18704731772920896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064506786","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":[0.98714244,0.00026126415,0.0047372193,0.0011452873,0.0003906977,0.00053219515,0.000008260294,0.00013754958,0.0056450753],"genre_scores_gemma":[0.9975712,0.00008208559,0.0007181935,0.0008136076,0.00017331963,0.00004413604,0.000015864638,0.000027469458,0.0005541466],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991904,0.0000081385015,0.00020666378,0.00024519986,0.00009488038,0.00025473782],"domain_scores_gemma":[0.9997238,0.000018396366,0.00006874188,0.00012008724,0.00003650837,0.000032496915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017871546,0.00015235574,0.0001516549,0.00039724505,0.00023031647,0.0000695142,0.00009658688,0.00006061372,0.00018596381],"category_scores_gemma":[0.000015397116,0.00015433408,0.000052850002,0.00022680989,0.00007703814,0.0007519796,0.000025228728,0.00011618484,0.000004683338],"study_design_candidate":"not_applicable","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":[0.004045854,0.005839324,0.38156873,0.017714635,0.0018255339,0.00018799711,0.07803474,0.010195261,0.018040271,0.07908391,0.020806411,0.38265732],"study_design_scores_gemma":[0.007216838,0.00019952898,0.1259733,0.0010496668,0.00074912637,0.000014851542,0.05229584,0.2565636,0.00040906627,0.0024564287,0.55099124,0.0020805271],"about_ca_topic_score_codex":0.0007737488,"about_ca_topic_score_gemma":0.0006589316,"teacher_disagreement_score":0.5301848,"about_ca_system_score_codex":0.000038305345,"about_ca_system_score_gemma":0.000011785112,"threshold_uncertainty_score":0.6293561},"labels":[],"label_agreement":null},{"id":"W2067640696","doi":"10.1080/0740817x.2012.761371","title":"Selective maintenance modeling for a multistate system with multistate components under imperfect maintenance","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":116,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability engineering; Imperfect; Component (thermodynamics); Maintenance actions; Reliability (semiconductor); Function (biology); Computer science; Predictive maintenance; Engineering","score_opus":0.010196622769053712,"score_gpt":0.1972156953615536,"score_spread":0.1870190725924999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067640696","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":[0.044073474,0.000036309226,0.9528262,0.00014214752,0.00027796056,0.0014480478,0.000102760954,0.00061512156,0.00047800408],"genre_scores_gemma":[0.9714282,0.00008822228,0.02681463,0.000031492724,0.00002744153,0.0010442171,0.000030072182,0.000084045285,0.00045164235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859,0.000028695009,0.0003425719,0.0003499023,0.00013154592,0.00055729214],"domain_scores_gemma":[0.999144,0.000082615516,0.000047979094,0.0002566757,0.00034357762,0.0001251243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113019836,0.00027988225,0.00029259644,0.000118890894,0.00024920324,0.00007728033,0.00012587696,0.00009478324,0.000019256306],"category_scores_gemma":[0.000008486648,0.0002388388,0.0001136305,0.00029799048,0.00006755378,0.00048225705,0.0000027426777,0.00023169733,0.00003933395],"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":[0.00008935798,0.000038476635,0.000007931132,0.00025373258,0.0001018147,0.000001402927,0.00032273112,0.99516684,0.0025865617,0.000304441,0.00013795742,0.0009887288],"study_design_scores_gemma":[0.001451372,0.00007215074,0.00020946977,0.00023758986,0.00004441124,0.000025826615,0.00066773256,0.99607515,0.00060231495,0.00016813743,0.00012220224,0.00032364664],"about_ca_topic_score_codex":0.0006676116,"about_ca_topic_score_gemma":0.00032983327,"teacher_disagreement_score":0.92735475,"about_ca_system_score_codex":0.00041777833,"about_ca_system_score_gemma":0.000029332765,"threshold_uncertainty_score":0.97395635},"labels":[],"label_agreement":null},{"id":"W2067960619","doi":"10.1080/0740817x.2010.540638","title":"On the investment in a reliability improvement program for warranted second-hand items","year":2011,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Warranty; Reliability (semiconductor); Upgrade; Investment (military); Reliability engineering; Product (mathematics); Action (physics); Computer science; State (computer science); Return on investment; Operations research; Risk analysis (engineering); Actuarial science; Engineering; Operations management; Business; Economics; Microeconomics; Production (economics); Mathematics; Power (physics)","score_opus":0.017931730525427892,"score_gpt":0.2154855122191438,"score_spread":0.1975537816937159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067960619","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":[0.5127566,0.000033850505,0.4755437,0.00047557437,0.00062158826,0.004084034,0.00006130532,0.00038752623,0.0060358015],"genre_scores_gemma":[0.99505955,0.000019991761,0.0027472817,0.000121224344,0.0000096401745,0.0018756188,0.000006734163,0.000017741577,0.00014222499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993626,0.000016309144,0.00021240748,0.00015335865,0.00006081349,0.00019451065],"domain_scores_gemma":[0.99960214,0.00007459059,0.000016332842,0.00023261606,0.000036384616,0.00003796483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020108467,0.00010701247,0.00009956607,0.000045774905,0.00009026933,0.000019252271,0.000076551674,0.00006042484,0.0002394912],"category_scores_gemma":[0.00001872939,0.00007831647,0.00007111973,0.00014614881,0.00006051413,0.000090512214,0.0000012106859,0.0001393435,0.00000599114],"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":[0.00091083406,0.0049436023,0.00014556007,0.0011756676,0.00036499678,0.0000043702958,0.031154314,0.7815501,0.02348766,0.015749682,0.002745304,0.1377679],"study_design_scores_gemma":[0.0031536603,0.0016784568,0.0039766156,0.0001530216,0.00008864209,0.000002595439,0.0011323944,0.8554137,0.08255751,0.031742316,0.01939564,0.00070549693],"about_ca_topic_score_codex":0.000057028665,"about_ca_topic_score_gemma":0.00043553536,"teacher_disagreement_score":0.48230293,"about_ca_system_score_codex":0.00010313292,"about_ca_system_score_gemma":0.000014153148,"threshold_uncertainty_score":0.3193653},"labels":[],"label_agreement":null},{"id":"W2069089947","doi":"10.1080/0740817x.2012.689121","title":"The maximum covering problem with travel time uncertainty","year":2012,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Travel time; Transport engineering; Computer science; Operations research; Variety (cybernetics); Ranging; Engineering; Telecommunications","score_opus":0.014445973556308512,"score_gpt":0.2010443653683515,"score_spread":0.186598391812043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069089947","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":[0.099877454,0.0003517959,0.52258116,0.02167027,0.0021796962,0.002256271,0.000023541674,0.0009932384,0.3500666],"genre_scores_gemma":[0.99384373,0.000018260493,0.00017276028,0.00045152492,0.00020566092,0.000081432954,0.00001167839,0.000016223477,0.0051987316],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991914,0.000006793444,0.00016481841,0.00013048749,0.00018336029,0.00032313514],"domain_scores_gemma":[0.9996655,0.00001611805,0.00003136154,0.0002072269,0.00006132348,0.000018468438],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00026121648,0.00012196061,0.00008329648,0.00006323427,0.0005980953,0.00013157603,0.00014381841,0.000026287804,0.0011134511],"category_scores_gemma":[0.00000439531,0.00008280488,0.000055132303,0.00032380046,0.00005638827,0.0007986553,0.000007901639,0.000099832076,0.0011977324],"study_design_candidate":"not_applicable","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":[0.0012143422,0.0029325867,0.007052672,0.0014690564,0.0015791877,0.000008362307,0.0033745132,0.3838785,0.0032670968,0.12768279,0.036846675,0.43069422],"study_design_scores_gemma":[0.0008578194,0.000019864616,0.017910998,0.000037125483,0.00023728237,0.0000034095892,0.0016556535,0.031707756,0.00008755696,0.0011507659,0.94580096,0.0005307881],"about_ca_topic_score_codex":0.0009191831,"about_ca_topic_score_gemma":0.00090754085,"teacher_disagreement_score":0.9089543,"about_ca_system_score_codex":0.0000330133,"about_ca_system_score_gemma":0.000010889327,"threshold_uncertainty_score":0.99979967},"labels":[],"label_agreement":null},{"id":"W2069220392","doi":"10.1080/0740817x.2013.783251","title":"Measurement and optimization of supply chain responsiveness","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Erlang (programming language); Queue; Supply chain; Exponential distribution; Random variable; Erlang distribution; Interval (graph theory); Exponential function; Supply chain management; Queueing theory; Stage (stratigraphy); Computer science; Mathematical optimization; Mathematics; Operations research; Statistics; Computer network; Combinatorics","score_opus":0.016263684998470338,"score_gpt":0.21563752348976092,"score_spread":0.1993738384912906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069220392","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":[0.056694034,0.00008973055,0.94078296,0.0012044285,0.00008665929,0.00022704083,0.0000018870384,0.00007791671,0.00083531986],"genre_scores_gemma":[0.9977157,0.000014007267,0.0019057023,0.00014462898,0.00004905326,0.00003666511,0.000003044732,0.000012602082,0.000118570155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994468,0.000015279047,0.00016049536,0.00012960892,0.00014599129,0.00010180443],"domain_scores_gemma":[0.99947906,0.000024369601,0.000084027975,0.0001315386,0.0002725357,0.000008444929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023354964,0.00007961843,0.00011657956,0.00019811743,0.0001267239,0.000043666336,0.00006133549,0.00002952209,0.00071555737],"category_scores_gemma":[0.000042822405,0.000077915756,0.000044640434,0.0003200119,0.00005118743,0.0007499568,0.0000051726192,0.000050309198,0.00002668758],"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":[0.00010179824,0.00012160224,0.00040304614,0.00014526518,0.00010745832,0.0000011118791,0.00010320505,0.96824545,0.010468314,0.005151002,0.00007747419,0.015074295],"study_design_scores_gemma":[0.0026213992,0.00005711548,0.018103257,0.00041319695,0.0011444596,0.0000074404406,0.002291971,0.925385,0.007495788,0.033288013,0.008096719,0.0010956611],"about_ca_topic_score_codex":0.00025248865,"about_ca_topic_score_gemma":0.000059533624,"teacher_disagreement_score":0.9410217,"about_ca_system_score_codex":0.000018554563,"about_ca_system_score_gemma":0.000008704083,"threshold_uncertainty_score":0.7834851},"labels":[],"label_agreement":null},{"id":"W2074784329","doi":"10.1080/0740817x.2012.695102","title":"Spare parts provisioning for multiple<i>k</i>-out-of-<i>n</i>:G systems","year":2013,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":13,"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 Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Spare part; Component (thermodynamics); Provisioning; Computer science; Hybrid system; Reliability engineering; Operations research; Engineering; Operations management; Telecommunications","score_opus":0.024001462225105873,"score_gpt":0.23970576077062816,"score_spread":0.21570429854552228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074784329","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":[0.030328602,0.00009666589,0.9646639,0.00042941712,0.0009343529,0.0010944576,0.000018394569,0.00027338215,0.0021607871],"genre_scores_gemma":[0.9967303,0.0000034469576,0.0015101524,0.00013940762,0.00033020237,0.00039684778,0.00002255855,0.000035898065,0.0008311856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990085,0.000010758935,0.00034085588,0.00024482323,0.00014040688,0.00025466597],"domain_scores_gemma":[0.9990515,0.00019686301,0.00020578346,0.00027138036,0.0002577136,0.000016740447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017877921,0.00015573819,0.0002479465,0.00017699253,0.00030897354,0.00014142135,0.00016311284,0.000058237194,0.0002581149],"category_scores_gemma":[0.00007879814,0.0001448133,0.00017668237,0.00027862133,0.000055153498,0.0012093033,0.000008232526,0.000091996175,0.00018422153],"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":[0.00032160865,0.0008192105,0.0025128305,0.0026181373,0.0007925093,0.000006376143,0.0010509063,0.8788797,0.017872345,0.038629588,0.004991416,0.05150535],"study_design_scores_gemma":[0.0026481692,0.000055794368,0.00063361565,0.000509466,0.0011007682,0.0000034884501,0.004178173,0.72186905,0.0024942278,0.020575928,0.24472503,0.0012062796],"about_ca_topic_score_codex":0.00038290728,"about_ca_topic_score_gemma":0.00013976586,"teacher_disagreement_score":0.9664017,"about_ca_system_score_codex":0.00001926955,"about_ca_system_score_gemma":0.000011491846,"threshold_uncertainty_score":0.59053147},"labels":[],"label_agreement":null},{"id":"W2081646635","doi":"10.1080/07408170802375760","title":"Optimization of production control policies in failure-prone homogenous transfer lines","year":2009,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Parameterized complexity; Mathematical optimization; Production line; Computer science; Transfer line; Heuristic; Line (geometry); Mathematics; Algorithm; Engineering; Industrial engineering; Mechanical engineering","score_opus":0.008095758904509085,"score_gpt":0.20817028128519335,"score_spread":0.20007452238068427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081646635","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":[0.03876229,0.00018125604,0.95933086,0.0008009861,0.00023302394,0.00023095567,0.000016048944,0.0002588041,0.00018580722],"genre_scores_gemma":[0.9675353,0.00015058166,0.03211802,0.000026861,0.00006824652,0.000019601408,0.000010760209,0.000017882512,0.000052703854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934006,0.00001832366,0.0002717557,0.000118083524,0.00009682652,0.00015496125],"domain_scores_gemma":[0.9997398,0.00001505134,0.000012650214,0.00012551167,0.00006956714,0.0000373984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007218641,0.00011416143,0.00016515802,0.00022394455,0.00005131077,0.000013624093,0.000057321948,0.00008313621,0.00006310509],"category_scores_gemma":[0.000008048125,0.00012218773,0.000054683373,0.00045189992,0.000025501968,0.00016779573,2.0963684e-7,0.0001239056,0.0000029692706],"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":[0.000014884445,0.00008194754,0.000017778593,0.00001532571,0.000016721107,4.530761e-7,0.00073017867,0.9909897,0.0039129574,0.000023138158,0.0000065402246,0.004190385],"study_design_scores_gemma":[0.0010250154,0.00007878531,0.000977901,0.000041932853,0.0000579879,0.00001347142,0.00026873418,0.97294754,0.024262838,0.00004763078,0.00005809082,0.00022009511],"about_ca_topic_score_codex":0.000024402898,"about_ca_topic_score_gemma":0.00008082062,"teacher_disagreement_score":0.92877305,"about_ca_system_score_codex":0.000034178145,"about_ca_system_score_gemma":0.00001670586,"threshold_uncertainty_score":0.4982671},"labels":[],"label_agreement":null},{"id":"W2084260961","doi":"10.1080/07408170208928892","title":"On the identity of the smallest random variable","year":2002,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Random variable; Weibull distribution; Combinatorics; Binomial (polynomial); Variable (mathematics); Exponential function; Statistics; Expected value; Pareto principle; Log-normal distribution; Applied mathematics; Mathematical analysis","score_opus":0.055006889103334566,"score_gpt":0.20153568963269816,"score_spread":0.1465288005293636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084260961","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":[0.2856075,0.0007358715,0.6579282,0.0025878574,0.00084231957,0.00033471867,0.00018830488,0.000026441048,0.05174876],"genre_scores_gemma":[0.9980593,0.00013365794,0.00012979898,0.00014040468,0.00002345034,0.000015475864,3.567255e-7,0.0000070142455,0.001490589],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999413,0.000015082715,0.00028799733,0.00013272901,0.00003278497,0.0001184057],"domain_scores_gemma":[0.9994186,0.00013524778,0.000094530245,0.00031490377,0.000018590024,0.000018111588],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00030329317,0.00006551967,0.00014623361,0.00003978333,0.0002895795,0.000024104893,0.0002092795,0.000049530187,0.0027331288],"category_scores_gemma":[0.000071219394,0.000047197027,0.00014110327,0.000251161,0.000055403747,0.000102471306,0.000004434177,0.00016854749,0.00014458058],"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":[0.000037483125,0.000249459,0.0022211245,0.000016822923,0.000054646476,2.0298374e-7,0.0009774602,0.017182594,0.000047897905,0.9775939,0.0009148437,0.0007035903],"study_design_scores_gemma":[0.0024641799,0.00008923094,0.02207049,0.00007310644,0.000058916296,0.0000034637783,0.00015277958,0.2670126,0.00047235962,0.6793156,0.027873987,0.00041326566],"about_ca_topic_score_codex":0.0005486319,"about_ca_topic_score_gemma":0.00031568357,"teacher_disagreement_score":0.71245176,"about_ca_system_score_codex":0.000023634448,"about_ca_system_score_gemma":0.000006362535,"threshold_uncertainty_score":0.9981785},"labels":[],"label_agreement":null},{"id":"W2086941066","doi":"10.1080/0740817x.2012.654845","title":"Manufacturing system design by considering multiple machine replacements under discounted costs","year":2012,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematical optimization; Time horizon; Bounding overwatch; Branch and bound; Integer programming; Activity-based costing; Heuristic; Process (computing); Computer science; Routing (electronic design automation); Holding cost; Operations research; Heuristics; Reliability engineering; Industrial engineering; Engineering; Mathematics","score_opus":0.017200986873332116,"score_gpt":0.221898423754041,"score_spread":0.2046974368807089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086941066","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004794272,0.00034475862,0.99222213,0.000018114535,0.000686387,0.00025454382,0.00007264652,0.00087113224,0.00073601137],"genre_scores_gemma":[0.98262566,0.0000638996,0.016872654,0.000017062877,0.00004194043,0.000055747376,0.00004826867,0.000060258317,0.00021451878],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999079,0.000029309536,0.0002313756,0.00015639012,0.000124439,0.00037949756],"domain_scores_gemma":[0.9994731,0.00013108931,0.000034097116,0.00021385071,0.0000144099795,0.00013343745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001015585,0.00020520565,0.00015832129,0.000076635166,0.0002096214,0.000035680478,0.00006990914,0.000079590034,0.00007415819],"category_scores_gemma":[0.0000066782645,0.00021293503,0.00004434401,0.000060971557,0.000027498712,0.00033230506,0.0000037688178,0.00019800731,0.00003567579],"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":[0.00001655917,0.000031787225,0.000029178784,0.000060347942,0.00006703098,0.0000010734082,0.000100846526,0.99709314,0.0014628087,0.000033347194,0.0001751787,0.0009287292],"study_design_scores_gemma":[0.0014676235,0.00003258069,0.00033630594,0.00012721236,0.00016293286,0.000059766746,0.0007366068,0.64903784,0.34399423,0.000042701464,0.0032354132,0.0007667738],"about_ca_topic_score_codex":0.000052751453,"about_ca_topic_score_gemma":0.000017823033,"teacher_disagreement_score":0.97783136,"about_ca_system_score_codex":0.0003363483,"about_ca_system_score_gemma":0.0000057695825,"threshold_uncertainty_score":0.86832386},"labels":[],"label_agreement":null},{"id":"W2091305937","doi":"10.1080/0740817x.2010.504684","title":"An efficient dynamic optimization method for sequential identification of group-testable items","year":2010,"lang":"en","type":"article","venue":"IIE Transactions","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Saint Mary's University","funders":"","keywords":"Dynamic programming; Mathematical optimization; Group (periodic table); Computation; Identification (biology); Stochastic programming; Computer science; Group testing; Scheme (mathematics); Linear programming; Algorithm; Mathematics","score_opus":0.023724481175910323,"score_gpt":0.3486940523802195,"score_spread":0.3249695712043092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091305937","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":[0.24669921,0.00000779822,0.7520355,0.00006285243,0.00054493116,0.00040812878,0.000028792267,0.00012231147,0.00009048342],"genre_scores_gemma":[0.8574191,0.0000012517222,0.14227192,0.000044064876,0.000049647555,0.00007456956,0.00004483254,0.000023511531,0.00007110574],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991241,0.0000330135,0.00033955192,0.0002237564,0.00013672601,0.00014287079],"domain_scores_gemma":[0.9992453,0.000110590205,0.00012423533,0.00025231103,0.00021654733,0.000051039435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000391529,0.00009406476,0.00015112845,0.00019007243,0.00017092994,0.000025104315,0.00005422668,0.000100916164,0.00007801681],"category_scores_gemma":[0.00006892671,0.000097279895,0.000103332946,0.00029935184,0.000041721425,0.000116427946,0.0000010897717,0.00017215771,0.0000038974335],"study_design_candidate":"bench_or_experimental","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":[0.000067125686,0.00027654922,0.00001746165,0.000047698446,0.000024277875,3.8912916e-7,0.00015329602,0.065788895,0.92682916,0.000077334495,0.0000017952848,0.006716035],"study_design_scores_gemma":[0.00059153733,0.0000926342,0.00019325163,0.000009931369,0.00012681258,0.000036677407,0.00007231998,0.6350892,0.36355707,0.000030131589,0.00014064381,0.000059758804],"about_ca_topic_score_codex":0.00010766755,"about_ca_topic_score_gemma":0.0001313844,"teacher_disagreement_score":0.61071986,"about_ca_system_score_codex":0.00003794681,"about_ca_system_score_gemma":0.00005036422,"threshold_uncertainty_score":0.3966959},"labels":[],"label_agreement":null},{"id":"W2091804335","doi":"10.1080/0740817x.2011.593609","title":"A waste relationship model and center point tracking metric for lean manufacturing systems","year":2011,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Lean manufacturing; Metric (unit); Production (economics); Process (computing); Industrial engineering; Point (geometry); Work (physics); Value stream mapping; Pareto principle; Engineering; Computer science; Operations research; Manufacturing engineering; Operations management; Mathematics; Economics; Mechanical engineering","score_opus":0.09737552933987137,"score_gpt":0.2479545961409987,"score_spread":0.15057906680112734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091804335","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":[0.1082048,0.00006863834,0.88116807,0.0004451782,0.00036069262,0.0006729876,0.000018237659,0.00017052717,0.008890879],"genre_scores_gemma":[0.99757993,0.0000068325116,0.00096190436,0.00022356413,0.00014731627,0.00010239144,0.00001456373,0.000026243537,0.00093723007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910146,0.000007807837,0.00027666573,0.00024349609,0.00012581589,0.00024473268],"domain_scores_gemma":[0.99962246,0.000057487836,0.0000854164,0.0001689345,0.000047015084,0.000018654551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034648346,0.00014268306,0.00015149819,0.00040709623,0.00041017667,0.00018698037,0.000105177154,0.00005642048,0.00007207186],"category_scores_gemma":[0.000014351997,0.00014037176,0.00009751458,0.0001822752,0.000029845703,0.0011454939,0.000011482377,0.00012266095,0.000028359895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011154788,0.0024322546,0.014718609,0.010075773,0.0012223241,0.000036901904,0.008875709,0.3330489,0.0003050831,0.5575547,0.00546969,0.06514455],"study_design_scores_gemma":[0.0042409683,0.00005475669,0.014986135,0.00029392834,0.0009842652,0.000014369164,0.0075507965,0.9021334,0.0005081139,0.04789758,0.02002752,0.0013081661],"about_ca_topic_score_codex":0.00035124307,"about_ca_topic_score_gemma":0.00020437401,"teacher_disagreement_score":0.88937515,"about_ca_system_score_codex":0.000027011747,"about_ca_system_score_gemma":0.0000053756107,"threshold_uncertainty_score":0.57241946},"labels":[],"label_agreement":null},{"id":"W2093303877","doi":"10.1080/07408170208928902","title":"Integrating advance order information in make-to-stock production systems","year":2002,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Build to order; Computer science; Stock (firearms); Queue; Stock control; Order (exchange); Supply chain; Operations research; Production (economics); Optimal control; Information structure; Risk analysis (engineering); Mathematical optimization; Microeconomics; Business; Economics; Engineering; Mathematics; Finance","score_opus":0.020773532156555596,"score_gpt":0.2148019828782036,"score_spread":0.194028450721648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093303877","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":[0.12210006,0.0002685415,0.6641613,0.015092999,0.010661543,0.004542745,0.000012465702,0.0012169543,0.18194339],"genre_scores_gemma":[0.9952233,0.000014032624,0.00046067487,0.0009383526,0.00041213149,0.0002402423,0.000013792222,0.000015290534,0.0026822244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99908906,0.000009064195,0.0003207899,0.00017461891,0.00018527688,0.00022117312],"domain_scores_gemma":[0.99958706,0.000009308366,0.00008643133,0.00018863012,0.00011555174,0.000013034414],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017103714,0.00013288288,0.00011866652,0.00050434365,0.00017141532,0.00021431044,0.00011499425,0.000039821003,0.00052003283],"category_scores_gemma":[0.00004862606,0.00013330045,0.00003698244,0.0010055724,0.000015992535,0.0022633541,0.000008632132,0.00014221783,0.00082978536],"study_design_candidate":"not_applicable","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":[0.00012123913,0.0007877641,0.003096097,0.0014210177,0.00009480652,0.000010771891,0.0037651395,0.5067768,0.0006183163,0.019595856,0.0419186,0.4217936],"study_design_scores_gemma":[0.0005487772,0.000016765907,0.0011872834,0.0001734209,0.00003164487,0.000002781816,0.0028642777,0.19882087,0.000034034925,0.0001420842,0.795832,0.00034608482],"about_ca_topic_score_codex":0.00042167256,"about_ca_topic_score_gemma":0.00041363155,"teacher_disagreement_score":0.87312317,"about_ca_system_score_codex":0.000088875255,"about_ca_system_score_gemma":0.000004112949,"threshold_uncertainty_score":0.9999482},"labels":[],"label_agreement":null},{"id":"W2094670889","doi":"10.1080/07408170601091881","title":"Dynamic pricing for multiple class deterministic demand fulfillment","year":2007,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Profitability index; Dynamic pricing; Discounting; Microeconomics; Order (exchange); Service (business); Stock (firearms); Economics; Business; Operations research; Marketing; Mathematics","score_opus":0.019287042400009616,"score_gpt":0.2456751133157826,"score_spread":0.22638807091577298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094670889","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":[0.04593896,0.00004413761,0.94182694,0.00063453673,0.0012154788,0.0008271767,0.000008337394,0.00022928225,0.00927518],"genre_scores_gemma":[0.99555075,0.0000061352334,0.0013549605,0.0011657452,0.0002575442,0.00010064033,0.000029627488,0.000035371537,0.0014992346],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988331,0.0000038605467,0.0003109605,0.00027870006,0.00016897348,0.00040437214],"domain_scores_gemma":[0.99948317,0.00011693433,0.00009692592,0.00020970475,0.00006940096,0.000023871238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040404603,0.00017411297,0.00015578332,0.00028692238,0.00040777944,0.00013035392,0.00015727027,0.00005741709,0.00028644004],"category_scores_gemma":[0.00002704829,0.00017448157,0.0001454165,0.00025271662,0.000043506436,0.00042078027,0.000011841764,0.00009098137,0.00011473295],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029870365,0.0052006016,0.014042041,0.006664841,0.0017909348,0.00025007242,0.002378208,0.059280958,0.028001659,0.04849696,0.02569317,0.8052135],"study_design_scores_gemma":[0.0029605066,0.00006180451,0.010017983,0.000086572356,0.00039783548,0.000004907321,0.0014351256,0.36991537,0.00048070386,0.002096795,0.61185426,0.0006881553],"about_ca_topic_score_codex":0.000074967815,"about_ca_topic_score_gemma":0.00092705665,"teacher_disagreement_score":0.9496118,"about_ca_system_score_codex":0.00009571979,"about_ca_system_score_gemma":0.000010057817,"threshold_uncertainty_score":0.7115152},"labels":[],"label_agreement":null},{"id":"W2104289244","doi":"10.1080/07408170208928929","title":"The value of information used in inventory control of a make-to-order inventory-production system","year":2002,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Waterloo; Dalhousie University","funders":"","keywords":"Inventory control; Production (economics); Value (mathematics); Order (exchange); Economic order quantity; Inventory valuation; Perpetual inventory; Control (management); Operations research; Operations management; Inventory theory; Computer science; Business; Mathematics; Statistics; Engineering; Economics; Microeconomics; Marketing; Supply chain; Artificial intelligence","score_opus":0.017437376276748847,"score_gpt":0.20080886174701806,"score_spread":0.1833714854702692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104289244","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":[0.7401338,0.00052855496,0.18149926,0.011305734,0.0073047243,0.0051963283,0.000031202453,0.00049308426,0.053507324],"genre_scores_gemma":[0.9990292,0.000014403931,0.00004773712,0.00028667547,0.0001307683,0.00010724395,0.000004847825,0.000012396741,0.00036671842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987575,0.000032650878,0.0005623194,0.0001348259,0.00030865578,0.0002040485],"domain_scores_gemma":[0.99925256,0.000026517906,0.0002482185,0.00029501753,0.00016236346,0.000015334177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051027164,0.00012774869,0.00019288009,0.0004933054,0.00015229698,0.000057316174,0.00020508686,0.0000511433,0.00013603915],"category_scores_gemma":[0.000051664265,0.000110299,0.000096108844,0.000843398,0.00006832067,0.00081633084,0.000011043112,0.00010851037,0.0001014051],"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":[0.0013624863,0.0028399066,0.05673984,0.009687998,0.0013016766,0.000011904679,0.012955558,0.4176048,0.0051278803,0.34084228,0.019043019,0.13248263],"study_design_scores_gemma":[0.0065686377,0.00012278788,0.01562714,0.00076506,0.00048008637,0.0000042732277,0.016913231,0.6251835,0.000982321,0.001016287,0.33149865,0.00083800365],"about_ca_topic_score_codex":0.00063105713,"about_ca_topic_score_gemma":0.00042314632,"teacher_disagreement_score":0.339826,"about_ca_system_score_codex":0.0000917859,"about_ca_system_score_gemma":0.000012106037,"threshold_uncertainty_score":0.44978625},"labels":[],"label_agreement":null},{"id":"W2106081565","doi":"10.1080/07408170309342349","title":"Optimization-based manufacturing scheduling with multiple resources, setup requirements, and transfer lots","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Capital District Health Authority","funders":"University of Connecticut; University of California, Santa Cruz; National Science Foundation","keywords":"Subgradient method; Mathematical optimization; Schedule; Computer science; Scheduling (production processes); Job shop scheduling; Integer programming; Heuristic; Linear programming; Mathematics","score_opus":0.011414599928153503,"score_gpt":0.19975513272835876,"score_spread":0.18834053280020527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106081565","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036033053,0.00019531649,0.9621223,0.00005513319,0.00014379407,0.00017570853,0.00001786275,0.0004657355,0.000791086],"genre_scores_gemma":[0.74725664,0.000050484192,0.25246942,0.00004268327,0.00001783147,0.000029892815,0.000013196731,0.000051644492,0.0000681805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991458,0.000028408627,0.00020232999,0.00022169792,0.00015412051,0.00024761836],"domain_scores_gemma":[0.99958515,0.000067053996,0.000012311888,0.00017021954,0.000035343626,0.00012989726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000089920344,0.00019493423,0.00014517347,0.00014031999,0.0002440225,0.00007572008,0.000058953734,0.000088162284,0.0002689824],"category_scores_gemma":[0.000007117098,0.0001929035,0.000040196483,0.00019188324,0.000046656773,0.00018525112,6.224114e-7,0.00019117586,0.000005751631],"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":[0.000015339698,0.00002736503,0.0000913941,0.000036825106,0.00004730595,0.0000037292787,0.00022803895,0.9986968,0.00008147234,0.000008195324,0.0000020407745,0.0007614759],"study_design_scores_gemma":[0.0014468465,0.00002948583,0.00009666299,0.00005740967,0.000065102715,0.000012368841,0.00020309575,0.9827632,0.014320634,0.0000046041896,0.0007121014,0.00028850537],"about_ca_topic_score_codex":0.000014266786,"about_ca_topic_score_gemma":0.000041727853,"teacher_disagreement_score":0.7112236,"about_ca_system_score_codex":0.000043222964,"about_ca_system_score_gemma":0.00002361003,"threshold_uncertainty_score":0.78663766},"labels":[],"label_agreement":null},{"id":"W2143228176","doi":"10.1080/07408170590948495","title":"Empirical Bayes forecasting methods for job flow times","year":2005,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo; National Science Foundation","keywords":"Bayes' theorem; Parametric statistics; Econometrics; Mathematics; Exponential distribution; Statistics; Computer science; Bayesian probability","score_opus":0.04940613717440935,"score_gpt":0.33822777687704847,"score_spread":0.28882163970263913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143228176","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":[0.0003714517,0.0002349374,0.99606496,0.0005037921,0.0003818516,0.0001160781,0.000018973325,0.0005353974,0.0017725489],"genre_scores_gemma":[0.028822372,0.000023081306,0.97005904,0.00007204498,0.00021006798,0.00006600421,0.000006811624,0.00003617842,0.00070438883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994574,0.000017825638,0.00016910599,0.00011837759,0.000048885126,0.00018841361],"domain_scores_gemma":[0.99955714,0.00021888452,0.000010312113,0.00010080823,0.000040243685,0.000072637224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014118891,0.00010414807,0.00011509403,0.0000762125,0.00014111234,0.000033198132,0.000063139276,0.0000763367,0.00043690848],"category_scores_gemma":[0.000024798535,0.00010678896,0.000100200945,0.00015589083,0.000015365635,0.00012589467,9.639255e-7,0.000118404176,0.000024215802],"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":[0.0000030164529,0.000009994275,0.0000037960294,0.00000969442,0.000026543245,1.1387627e-7,0.00022832365,0.7399585,0.00006790898,0.000006362138,0.00029374647,0.25939196],"study_design_scores_gemma":[0.0002484364,0.000012478562,0.000020973874,0.000008107881,0.000036437967,0.000008762722,0.00004746929,0.9794825,0.0026335588,0.00008997949,0.017284622,0.0001267082],"about_ca_topic_score_codex":0.000001350129,"about_ca_topic_score_gemma":0.000010069318,"teacher_disagreement_score":0.25926524,"about_ca_system_score_codex":0.000036261816,"about_ca_system_score_gemma":0.000013662192,"threshold_uncertainty_score":0.47838417},"labels":[],"label_agreement":null},{"id":"W2143324015","doi":"10.1080/0740817x.2014.905735","title":"Maximizing throughput in zero-buffer tandem lines with dedicated and flexible servers","year":2014,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Server; Heuristics; Throughput; Computer science; Queue; Distributed computing; Tandem; Buffer (optical fiber); Zero (linguistics); Queueing theory; Computer network; Mathematical optimization; Operating system; Mathematics; Engineering; Wireless","score_opus":0.013927282822819461,"score_gpt":0.2212751497083812,"score_spread":0.20734786688556173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143324015","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":[0.3532787,0.00004707737,0.64077634,0.0016427743,0.000093146344,0.000142449,0.0000011824478,0.00029863176,0.003719739],"genre_scores_gemma":[0.9974161,0.000017106295,0.0014448641,0.0005934162,0.000115916366,0.000017725075,0.0000074571044,0.000026170272,0.0003612626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992292,0.000015484704,0.00017394141,0.0002526408,0.000115406845,0.00021335381],"domain_scores_gemma":[0.99961936,0.00006192527,0.00007512281,0.00017259015,0.000056233344,0.000014744693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022371433,0.00014571285,0.00019140531,0.00024399642,0.00021957721,0.00008952083,0.00009824904,0.0000557164,0.00014130831],"category_scores_gemma":[0.000022520646,0.00012638731,0.00004247361,0.00070581853,0.00008462872,0.00094342773,0.000008502599,0.00016013638,0.000033596178],"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":[0.0013353487,0.0011325949,0.11042487,0.0010781417,0.0010483182,0.00008500467,0.0015590234,0.6773558,0.0074014305,0.0761708,0.000714821,0.1216938],"study_design_scores_gemma":[0.013565113,0.0001782201,0.059976585,0.001225938,0.0026869113,0.000054222433,0.0031002862,0.57360566,0.0039216913,0.187096,0.15096024,0.0036291513],"about_ca_topic_score_codex":0.00035204427,"about_ca_topic_score_gemma":0.0010193055,"teacher_disagreement_score":0.6441374,"about_ca_system_score_codex":0.000023345214,"about_ca_system_score_gemma":0.000007903016,"threshold_uncertainty_score":0.5153925},"labels":[],"label_agreement":null},{"id":"W2168531676","doi":"10.1080/07408170590961166","title":"Coordination of quantity and shelf-retention timing in the video movie rental industry","year":2006,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Wilfrid Laurier University; University of New Brunswick","funders":"","keywords":"Renting; License; Business; Profit (economics); Revenue; Microeconomics; Channel coordination; Studio; Revenue sharing; Incentive; Computer science; Industrial organization; Supply chain; Economics; Marketing; Finance; Supply chain management; Telecommunications","score_opus":0.029973215013965247,"score_gpt":0.23284810242108542,"score_spread":0.20287488740712017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168531676","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":[0.9794771,0.00006243101,0.006515152,0.0015911291,0.00023402934,0.00028487502,0.0000031000454,0.00004176574,0.011790423],"genre_scores_gemma":[0.9993184,0.0000051407183,0.0000408097,0.00019820161,0.00012460395,0.000021299638,0.000018322444,0.0000068355603,0.00026635927],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999405,0.00001440339,0.0001990426,0.00012676725,0.00014511052,0.00010966429],"domain_scores_gemma":[0.9997664,0.000021164335,0.000078465186,0.00010089547,0.000029576702,0.0000034800137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028134475,0.000077301454,0.00008221289,0.00020150766,0.00013063368,0.0000776853,0.000084353036,0.00006314675,0.00021335608],"category_scores_gemma":[0.0000068732006,0.00006651394,0.00004421122,0.00034233218,0.00004905355,0.00063289126,0.0000071477557,0.00014849125,0.00001051319],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028047513,0.0035233463,0.6344898,0.0020365228,0.00021699218,0.00004362639,0.0012751777,0.012430461,0.013039409,0.24027774,0.028820068,0.0635664],"study_design_scores_gemma":[0.0024220925,0.000038133036,0.898611,0.0001922065,0.00030225434,0.000006171465,0.0051721865,0.045963027,0.0005587681,0.007818783,0.038428925,0.00048646654],"about_ca_topic_score_codex":0.003917139,"about_ca_topic_score_gemma":0.0019554193,"teacher_disagreement_score":0.2641212,"about_ca_system_score_codex":0.000021098636,"about_ca_system_score_gemma":0.0000042193683,"threshold_uncertainty_score":0.5921569},"labels":[],"label_agreement":null},{"id":"W2587016265","doi":"10.1080/07408170008967441","title":"Risk intermediation in supply chains","year":2000,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":152,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Delhi; Leonard N. Stern School of Business, New York University; York University; Office of Naval Research; University of Pennsylvania","keywords":"Newsvendor model; Inefficiency; Economic order quantity; Business; Microeconomics; Profit (economics); Risk aversion (psychology); Supply chain; Order (exchange); Intermediation; Value (mathematics); Industrial organization; Economics; Expected utility hypothesis; Marketing; Computer science; Finance; Financial economics","score_opus":0.009204501042600937,"score_gpt":0.1993123592898033,"score_spread":0.19010785824720236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587016265","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":[0.8403442,0.00007160118,0.014173596,0.0034656774,0.0011475998,0.00065192784,0.000018233955,0.0004039449,0.13972321],"genre_scores_gemma":[0.9939272,0.000109624896,0.000049154965,0.0010644214,0.0003831242,0.000063903906,0.000027692011,0.000017814871,0.00435707],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99921966,0.000011322847,0.00021181778,0.0001998397,0.0001351952,0.00022215817],"domain_scores_gemma":[0.99973845,0.000017090459,0.000046593286,0.00016695097,0.000019873949,0.0000110419],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00017208181,0.00011678584,0.000105561274,0.000306992,0.00013613181,0.000100024576,0.00013381122,0.000044641885,0.014578251],"category_scores_gemma":[0.0000076082583,0.000120836456,0.00007535103,0.00043085063,0.000033531913,0.0007977511,0.0000043691202,0.00015403559,0.00132777],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002575692,0.0011549203,0.047294036,0.00018361196,0.000117667376,0.000041639723,0.0014105276,0.022761444,0.00014714569,0.008340528,0.014918759,0.90337217],"study_design_scores_gemma":[0.002215559,0.000024333127,0.19009551,0.000069000416,0.00012100987,0.0000016779145,0.0009013561,0.085109435,0.00006755076,0.0031856366,0.71766025,0.0005486666],"about_ca_topic_score_codex":0.0011312758,"about_ca_topic_score_gemma":0.0018363489,"teacher_disagreement_score":0.9028235,"about_ca_system_score_codex":0.000049454804,"about_ca_system_score_gemma":0.0000067195033,"threshold_uncertainty_score":0.9994498},"labels":[],"label_agreement":null},{"id":"W3121407226","doi":"10.1080/07408170108936878","title":"State dependent pricing with a queue","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Queue; Microeconomics; Economics; Homogeneous; Social Welfare; State dependent; Business; Industrial organization; Computer science; Mathematical economics; Mathematics","score_opus":0.010659359734794344,"score_gpt":0.21856629903478442,"score_spread":0.20790693929999007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121407226","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":[0.1721087,0.000021063825,0.8165793,0.00058484194,0.000081270926,0.000120914796,0.0000015484464,0.0002801951,0.010222166],"genre_scores_gemma":[0.9960348,0.00001401264,0.0006179348,0.0004835711,0.00012930948,0.000023697508,0.0000042468128,0.000027506454,0.0026649223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992487,0.0000074833865,0.00014821421,0.0002126132,0.00015329178,0.00022973468],"domain_scores_gemma":[0.99959475,0.000029908391,0.0000798041,0.00020462718,0.0000780104,0.000012911454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012855891,0.00012870268,0.00013060033,0.00020905236,0.0002892531,0.000105464875,0.00011363251,0.000023625385,0.000679351],"category_scores_gemma":[0.000007781131,0.00011059792,0.00006095237,0.0006392553,0.000038503727,0.00097286934,0.000005064674,0.00013759705,0.00023716377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000831183,0.0005438582,0.004486883,0.0001381954,0.00056092016,0.00033153096,0.0005110439,0.88965917,0.0032406372,0.009367854,0.00012865514,0.09020007],"study_design_scores_gemma":[0.013013066,0.00025429888,0.017959021,0.00089134474,0.0057544596,0.0005148809,0.008083084,0.29166108,0.0072736396,0.16112979,0.48687124,0.006594081],"about_ca_topic_score_codex":0.0004618077,"about_ca_topic_score_gemma":0.0021500785,"teacher_disagreement_score":0.8239261,"about_ca_system_score_codex":0.000036672085,"about_ca_system_score_gemma":0.000011574083,"threshold_uncertainty_score":0.7438417},"labels":[],"label_agreement":null},{"id":"W4233788103","doi":"10.1080/07408170008967422","title":"A metric for agility measurement in product development","year":2000,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":23,"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":"","keywords":"Measure (data warehouse); Metric (unit); New product development; Product (mathematics); Computer science; Industrial engineering; Process (computing); Product metric; Interval (graph theory); Hierarchy; Performance measurement; Reliability engineering; Operations research; Engineering; Operations management; Mathematics; Data mining; Business; Marketing; Economics","score_opus":0.0347875581570935,"score_gpt":0.2169828240654612,"score_spread":0.1821952659083677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233788103","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":[0.64706606,0.0013089891,0.26926878,0.010743205,0.0024844224,0.0073945113,0.000010769448,0.001295541,0.0604277],"genre_scores_gemma":[0.9960469,0.0000114578,0.0019134886,0.000260301,0.00019608633,0.000296881,0.00002222315,0.000017612376,0.0012350316],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988605,0.0000063271295,0.0003031288,0.00031532758,0.00026091986,0.00025379527],"domain_scores_gemma":[0.9996165,0.000009300155,0.0000463123,0.00014881544,0.00016901818,0.000010059909],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00065303943,0.0001355282,0.00013857434,0.0003558814,0.00022551055,0.00008032517,0.00011846771,0.000033442095,0.0010071311],"category_scores_gemma":[0.000041006846,0.00013464349,0.000048733855,0.0010409411,0.000015776783,0.00065466156,0.0000030309454,0.000077383454,0.00020145635],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026733635,0.0006965327,0.0028510846,0.00028122205,0.00007336427,0.0000014511584,0.00038099883,0.0028809619,0.0005481944,0.0003407938,0.0017485996,0.98992944],"study_design_scores_gemma":[0.002132804,0.000008121299,0.11022286,0.000064630076,0.00008788586,0.0000014643796,0.00009471437,0.0019757934,0.0039416817,0.0013602173,0.879499,0.0006108133],"about_ca_topic_score_codex":0.00007909824,"about_ca_topic_score_gemma":0.0005555571,"teacher_disagreement_score":0.98931867,"about_ca_system_score_codex":0.00014627237,"about_ca_system_score_gemma":0.00008600115,"threshold_uncertainty_score":0.99990606},"labels":[],"label_agreement":null},{"id":"W4233914278","doi":"10.1080/07408170008967470","title":"Gamma distribution parameter estimation for field reliability data with missing failure times","year":2000,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"U.S. Air Force; Simon Fraser University","keywords":"Missing data; Censoring (clinical trials); Estimator; Reliability (semiconductor); Maximum likelihood; Computer science; Gamma distribution; Data mining; Field (mathematics); Data collection; Reliability engineering; Statistics; Mathematics; Engineering; Machine learning","score_opus":0.05949752733788802,"score_gpt":0.3583400301840189,"score_spread":0.2988425028461309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233914278","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017729601,0.0000044074714,0.9871372,0.0065055704,0.000023649756,0.0005964,0.003361612,0.00020349854,0.00039469055],"genre_scores_gemma":[0.66599256,0.0000037245234,0.3301321,0.00010579918,0.000027866854,0.0002322008,0.002771385,0.000018093853,0.00071627623],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989506,0.00003588476,0.00031444608,0.00033866733,0.0001606344,0.00019976057],"domain_scores_gemma":[0.99768806,0.0013877262,0.00006438618,0.0006422085,0.00011708095,0.00010054347],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017095495,0.00014166645,0.00016138126,0.000021089014,0.00038266776,0.00007573649,0.00018024874,0.00009148821,0.0030538552],"category_scores_gemma":[0.00041616673,0.00012371648,0.00005385159,0.00020658321,0.00008208766,0.00031178156,0.0000033775877,0.00013448589,0.00005676009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005841155,0.0015368764,0.000034933288,0.00043378072,0.00017032975,0.0000022646793,0.00029290697,0.0076442403,0.00012892598,0.21422467,0.07270661,0.70224035],"study_design_scores_gemma":[0.0011154097,0.00014846452,0.00078446785,0.000086475186,0.00040141563,0.00002588876,0.000068685826,0.7360792,0.0013299104,0.21920782,0.040345795,0.00040645717],"about_ca_topic_score_codex":0.000019523886,"about_ca_topic_score_gemma":0.000035123103,"teacher_disagreement_score":0.728435,"about_ca_system_score_codex":0.000042487252,"about_ca_system_score_gemma":0.000055102544,"threshold_uncertainty_score":0.9978575},"labels":[],"label_agreement":null},{"id":"W4240263563","doi":"10.1023/a:1019674531563","title":"The inverted beta loss function : properties and applications","year":2002,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Ranging; Mathematics; Transformation (genetics); BETA (programming language); Probability density function; Class (philosophy); Applied mathematics; Statistics; Pure mathematics; Computer science; Artificial intelligence; Telecommunications","score_opus":0.12463852771619609,"score_gpt":0.2912623500089965,"score_spread":0.16662382229280037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240263563","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":[0.009243867,0.003174436,0.95220727,0.027244272,0.00021198142,0.00037008,0.0000198136,0.000119129225,0.0074091526],"genre_scores_gemma":[0.9863044,0.0018128162,0.00007740912,0.00011899938,0.000045136792,0.00009581561,7.496883e-7,0.0000055593946,0.011539133],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988198,0.00009117458,0.0003030583,0.00024409851,0.00039891197,0.00014293671],"domain_scores_gemma":[0.9989702,0.00033129475,0.000059280024,0.0004202574,0.00014396975,0.000075016644],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00041517493,0.00008112082,0.0001128687,0.00010325918,0.0013808237,0.00022110705,0.00023657785,0.00004694903,0.0006139768],"category_scores_gemma":[0.0000346126,0.000045581357,0.0001019499,0.0007978239,0.00024374491,0.0002695832,0.0000054953057,0.00012486748,0.00046964688],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002008534,0.000060112387,0.00034546753,0.0000015105669,0.00006694618,3.650722e-7,0.0004931816,0.0009090539,0.000192529,0.0012310274,0.0016998257,0.9949799],"study_design_scores_gemma":[0.00039019863,0.000060149552,0.009682251,0.000005652212,0.0002471146,0.000019425794,0.002062381,0.05832385,0.00034013725,0.040224455,0.88840044,0.00024392628],"about_ca_topic_score_codex":0.000052621686,"about_ca_topic_score_gemma":0.00062193314,"teacher_disagreement_score":0.99473596,"about_ca_system_score_codex":0.000012729645,"about_ca_system_score_gemma":0.000010604066,"threshold_uncertainty_score":0.99991924},"labels":[],"label_agreement":null},{"id":"W4240874259","doi":"10.1080/07408170108936848","title":"Scheduling of the optimal tool replacement times in a flexible manufacturing system","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Flexible manufacturing system; Flexibility (engineering); Scheduling (production processes); Machining; Time horizon; Schedule; Reliability (semiconductor); Job shop scheduling; Mathematical optimization; Computer science; Dynamic programming; Failure rate; Reliability engineering; Engineering; Algorithm; Mechanical engineering; Mathematics","score_opus":0.01682069972086447,"score_gpt":0.2125245421632751,"score_spread":0.19570384244241062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240874259","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":[0.90463793,0.00006387729,0.038074754,0.0012407599,0.0009119673,0.00069725,0.0000025689658,0.00020772888,0.05416315],"genre_scores_gemma":[0.99699104,0.000007698149,0.0003037901,0.00021952839,0.00014501112,0.0000536444,0.0000024310295,0.000016670076,0.0022601855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990329,0.000011840049,0.00031866014,0.00019830513,0.00021031371,0.00022797326],"domain_scores_gemma":[0.9995487,0.000017057171,0.00010791507,0.00029180333,0.000027454265,0.000007110817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027474985,0.00012706191,0.00014600747,0.00021937082,0.00018169728,0.00007608484,0.00021539515,0.000038624967,0.00078615174],"category_scores_gemma":[0.0000057503826,0.00010305972,0.000114943985,0.00034868214,0.000036050234,0.00046290318,0.000027362154,0.00012271163,0.000069283495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083868834,0.0012231321,0.022282714,0.0027578492,0.00044677628,0.000055897595,0.00092928024,0.89222753,0.0024326718,0.044770952,0.002283597,0.0297509],"study_design_scores_gemma":[0.008324002,0.00009544733,0.04836892,0.0023739352,0.00073547085,0.00004174693,0.022208914,0.43806103,0.028338475,0.0012282137,0.44835413,0.0018697338],"about_ca_topic_score_codex":0.00047179044,"about_ca_topic_score_gemma":0.00010518218,"teacher_disagreement_score":0.45416653,"about_ca_system_score_codex":0.00008682601,"about_ca_system_score_gemma":0.000012464954,"threshold_uncertainty_score":0.860781},"labels":[],"label_agreement":null},{"id":"W4247636315","doi":"10.1080/07408170108936860","title":"Location of facilities on a network with groups of demand points","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tabu search; Simulated annealing; Metaheuristic; Mathematical optimization; Facility location problem; Set (abstract data type); Computer science; Operations research; Mathematics","score_opus":0.02142236927326423,"score_gpt":0.21222963723791638,"score_spread":0.19080726796465214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247636315","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":[0.54812235,0.0000996429,0.42678234,0.0020497413,0.0003624015,0.00047516226,0.0000063033553,0.00011684789,0.021985222],"genre_scores_gemma":[0.99849796,0.000032168275,0.00014308907,0.00016281364,0.00006742816,0.000022014532,0.000010388792,0.0000074869513,0.0010566709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992937,0.0000077152245,0.00024646285,0.00013609149,0.00018302738,0.00013303054],"domain_scores_gemma":[0.9995269,0.000014147144,0.00006313794,0.00019057226,0.00019735804,0.000007885696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014595372,0.0000960385,0.00013169496,0.00013584406,0.000095065276,0.000015390524,0.000086564025,0.000028001807,0.00071585446],"category_scores_gemma":[0.000008738502,0.00008491048,0.000042658878,0.00068843283,0.000062202904,0.00033885258,0.0000038796984,0.00005282106,0.00006645436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009948852,0.0010704075,0.010665766,0.002237557,0.0003069196,0.0000030100848,0.0008500977,0.9035186,0.00015913213,0.06460121,0.0022882924,0.013304094],"study_design_scores_gemma":[0.010211474,0.0009409284,0.45112607,0.0024162063,0.001588481,0.000012224861,0.017218612,0.15680781,0.0016501653,0.025076982,0.3302315,0.002719561],"about_ca_topic_score_codex":0.001059993,"about_ca_topic_score_gemma":0.002061861,"teacher_disagreement_score":0.74671084,"about_ca_system_score_codex":0.000012777869,"about_ca_system_score_gemma":0.000013939787,"threshold_uncertainty_score":0.78381044},"labels":[],"label_agreement":null},{"id":"W4251718306","doi":"10.1080/07408170108936831","title":"One-piece flow manufacturing on U-shaped production lines: a tutorial","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Flow (mathematics); Flow line; Production (economics); Production line; Manufacturing engineering; Material flow; Industrial engineering; Computer science; Engineering drawing; Product (mathematics); Engineering; Mechanical engineering; Mathematics; Economics","score_opus":0.01410454936694193,"score_gpt":0.21655905849756196,"score_spread":0.20245450913062002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251718306","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":[0.16799718,0.000029783907,0.8229786,0.0005350408,0.004486744,0.00036542406,0.000011474834,0.0016354572,0.0019602953],"genre_scores_gemma":[0.99135375,0.00013422008,0.0062853545,0.000028113649,0.0014445813,0.000058099555,0.000025509966,0.000064949905,0.0006054104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909246,0.000016710233,0.0002283729,0.00023420036,0.00018132076,0.00024691774],"domain_scores_gemma":[0.9995819,0.000031752807,0.000024297693,0.00025211117,0.000040014864,0.000069973845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006915283,0.00017315782,0.00015274766,0.00015133008,0.00015908935,0.000038710703,0.00008167995,0.00011017729,0.00016134694],"category_scores_gemma":[0.000016528447,0.00020455389,0.000071586495,0.00021763431,0.000014071426,0.0002713069,0.0000015308584,0.00025222558,0.00014214055],"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":[0.00004461273,0.00007280469,0.000009952917,0.000026761212,0.00004158074,0.0000023965545,0.00020459757,0.98063034,0.0064363102,0.000005783318,0.00015411439,0.012370735],"study_design_scores_gemma":[0.0012847027,0.00012689714,0.0025426217,0.00016324426,0.0001614307,0.000046886853,0.00008756021,0.87410957,0.09552594,0.00012417798,0.025048582,0.00077835587],"about_ca_topic_score_codex":0.0000151228,"about_ca_topic_score_gemma":0.00009227484,"teacher_disagreement_score":0.82335657,"about_ca_system_score_codex":0.00014250759,"about_ca_system_score_gemma":0.000017931581,"threshold_uncertainty_score":0.83414656},"labels":[],"label_agreement":null},{"id":"W4252524180","doi":"10.1080/07408170108936887","title":"The plant location and technology acquisition problem","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Science Council","keywords":"Set (abstract data type); Mathematical optimization; Computer science; Product (mathematics); Selection (genetic algorithm); Piecewise linear function; Piecewise; Industrial engineering; Operations research; Engineering; Mathematics; Artificial intelligence","score_opus":0.016221553272079716,"score_gpt":0.2074896994078609,"score_spread":0.1912681461357812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252524180","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":[0.17749934,0.00093017396,0.6049164,0.16997522,0.0016504484,0.0018189594,0.000011171586,0.0014704817,0.041727822],"genre_scores_gemma":[0.99782574,0.0002601059,0.000072568146,0.00035743896,0.00008331225,0.00008066043,0.00001584661,0.0000066037414,0.0012977275],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994761,0.0000039201645,0.0001461195,0.0001405655,0.000091022775,0.00014228724],"domain_scores_gemma":[0.99971324,0.000008567181,0.000025359654,0.0001474115,0.00009902029,0.000006397664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014254548,0.00007419276,0.000050865347,0.00014961904,0.0005653021,0.00010871787,0.00008818422,0.000038601316,0.00018496574],"category_scores_gemma":[0.0000061540964,0.000058706977,0.000017061237,0.0006319948,0.000066148576,0.00039118613,0.000008014451,0.000069824084,0.00020734806],"study_design_candidate":"not_applicable","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":[0.00019633507,0.0004885546,0.0042661177,0.00041051686,0.00018724916,0.000009019457,0.0002846921,0.010733347,0.001151026,0.41667956,0.012490273,0.5531033],"study_design_scores_gemma":[0.0006358479,0.000019561878,0.013009622,0.000040857663,0.00011686993,0.000013281045,0.001750334,0.055455424,0.000074679585,0.015603792,0.9129593,0.00032042814],"about_ca_topic_score_codex":0.00033344523,"about_ca_topic_score_gemma":0.0017914007,"teacher_disagreement_score":0.900469,"about_ca_system_score_codex":0.000016492926,"about_ca_system_score_gemma":0.0000069598586,"threshold_uncertainty_score":0.43479037},"labels":[],"label_agreement":null}]}