{"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012037982,0.0011968823,0.97641027,0.00051418785,0.00007744692,0.00012356124,0.00017408551,0.00008985533,0.009375718],"genre_scores_gemma":[0.38010085,0.0030783336,0.60437775,0.0003158462,0.0004635153,0.0006227669,0.0006169621,0.00020302941,0.010221069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990958,0.000365393,0.000039139773,0.000103965416,0.00030010208,0.00009550271],"domain_scores_gemma":[0.9978617,0.0016299075,0.00017889605,0.00012196359,0.00015978966,0.00004774487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018602976,0.0013232008,0.0011269721,0.00088565046,0.00034962138,0.0014603804,0.0018458044,0.0010456687,0.0038685016],"category_scores_gemma":[0.0041395705,0.00078535225,0.0016038136,0.0016670593,0.000987449,0.0020719524,0.001159228,0.0022598666,0.0003381688],"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":[0.00003261751,0.000051423598,0.00015758611,0.00012555021,0.000026617725,0.000052927593,0.00002879188,0.91457677,0.00044011936,0.06390839,0.001221449,0.019377697],"study_design_scores_gemma":[0.000010494821,0.0000139474705,0.00006832456,0.000009899815,0.000007096385,0.000015733722,0.0000064537085,0.97443604,0.00018175019,0.023917383,0.0013282218,0.000004624598],"about_ca_topic_score_codex":0.0042353924,"about_ca_topic_score_gemma":0.0046690945,"teacher_disagreement_score":0.0042353924,"about_ca_system_score_codex":0.002063521,"about_ca_system_score_gemma":0.0017598062,"threshold_uncertainty_score":0.014972031},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24115403,0.00089799304,0.7271196,0.0017627474,0.0001212375,0.0001628856,0.0032031466,0.0007068424,0.024871552],"genre_scores_gemma":[0.9059514,0.00061002624,0.07936134,0.00016497157,0.0001025987,0.00018703,0.002362461,0.0001967369,0.011063448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982162,0.0008088554,0.00008770179,0.00025860115,0.0002628675,0.00036574542],"domain_scores_gemma":[0.9972742,0.0016538902,0.00022107057,0.00030882398,0.00033450229,0.00020741532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00141151,0.0012594549,0.0019369915,0.00088133285,0.0009975748,0.0024209393,0.0017997092,0.0021194557,0.013646723],"category_scores_gemma":[0.006297238,0.0010448148,0.0011967877,0.0028775106,0.0012902208,0.0047306875,0.002603116,0.0012066896,0.0010935091],"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":[0.00031453322,0.00007215604,0.0014699983,0.00036405472,0.00006912838,0.00043066233,0.00021778313,0.87105167,0.001163611,0.09621991,0.004696269,0.023930276],"study_design_scores_gemma":[0.00007811373,0.00014418855,0.0003666772,0.000036319463,0.000030090949,0.00022722104,0.00028317436,0.8730821,0.0010687123,0.11928231,0.005373372,0.000027737373],"about_ca_topic_score_codex":0.0059809,"about_ca_topic_score_gemma":0.0047024633,"teacher_disagreement_score":0.013646723,"about_ca_system_score_codex":0.0013994145,"about_ca_system_score_gemma":0.0011074097,"threshold_uncertainty_score":0.045652807},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1284697,0.0018326829,0.842454,0.0014244502,0.00018041124,0.0007182785,0.0004194347,0.00040879427,0.024092266],"genre_scores_gemma":[0.848271,0.0014127429,0.14129505,0.00012352136,0.0000781454,0.00033692282,0.0003832727,0.00010534653,0.007993954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972441,0.0010313018,0.00014219103,0.0005784905,0.00058870367,0.00041526597],"domain_scores_gemma":[0.9939413,0.003988099,0.0010378417,0.00023093166,0.00050168775,0.00030015167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004297033,0.0012820185,0.0016536415,0.0013327708,0.0014852837,0.0038227963,0.0014682568,0.0019179473,0.006675407],"category_scores_gemma":[0.008651847,0.00203577,0.0013831115,0.001134612,0.0018568035,0.002672898,0.0011376586,0.0019421957,0.0007927215],"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":[0.00029617807,0.00009942735,0.00081117894,0.00020570864,0.000039179915,0.00031423292,0.0001413552,0.939021,0.0033912435,0.030574974,0.0011891279,0.023916487],"study_design_scores_gemma":[0.00011888848,0.0004243239,0.00093844876,0.000066119865,0.000068188485,0.00014508194,0.0002126697,0.96574765,0.0037726942,0.024321513,0.004106416,0.00007792281],"about_ca_topic_score_codex":0.0059120776,"about_ca_topic_score_gemma":0.005378496,"teacher_disagreement_score":0.006675407,"about_ca_system_score_codex":0.0030974091,"about_ca_system_score_gemma":0.0039564557,"threshold_uncertainty_score":0.022725165},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1145538,0.0002129051,0.8768872,0.00056044816,0.0000771729,0.00014811821,0.0003251813,0.00038132758,0.0068538073],"genre_scores_gemma":[0.72089905,0.00025007254,0.27167234,0.00015128849,0.00007261775,0.00019756124,0.00046989732,0.0001258412,0.0061613023],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993722,0.00021520616,0.000023403321,0.0001659377,0.000120760364,0.00010255018],"domain_scores_gemma":[0.9982894,0.001007112,0.00019671292,0.00023076063,0.00012988297,0.00014610979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008030089,0.0008915629,0.0009996531,0.00032018925,0.00050408265,0.0006376003,0.0013087341,0.0007879505,0.0020921433],"category_scores_gemma":[0.002912073,0.00048302376,0.0006177417,0.00058023684,0.0008713989,0.0014643415,0.00060557685,0.0009035501,0.0003194517],"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":[0.00024955775,0.00013416554,0.00042783786,0.00014105716,0.000034053766,0.0003312668,0.00006208252,0.9534782,0.0048574074,0.017487293,0.0014016529,0.021395445],"study_design_scores_gemma":[0.000039217695,0.00005731917,0.00029590467,0.0000030471067,0.000007425051,0.00005652116,0.000013056499,0.98470575,0.00136149,0.012461843,0.0009911588,0.000007260358],"about_ca_topic_score_codex":0.003350965,"about_ca_topic_score_gemma":0.0033789289,"teacher_disagreement_score":0.003350965,"about_ca_system_score_codex":0.0006988655,"about_ca_system_score_gemma":0.0011757279,"threshold_uncertainty_score":0.006998956},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026276752,0.0001026791,0.9967769,0.000051225867,0.000024789406,0.000019934145,0.000011436119,0.000026572307,0.00035884834],"genre_scores_gemma":[0.13144037,0.00044235535,0.86646086,0.00008681944,0.00009061554,0.00022686023,0.000098951496,0.000075814714,0.0010772604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99126023,0.004385665,0.0006557029,0.0008937248,0.0026175405,0.00018718933],"domain_scores_gemma":[0.98713267,0.008019393,0.0008711185,0.0009269772,0.0028477933,0.0002020117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0082811825,0.0011749924,0.0014481436,0.0021200518,0.000710146,0.0020339882,0.001989012,0.0012968348,0.0011160318],"category_scores_gemma":[0.031939626,0.00051610253,0.0011469098,0.0031779304,0.0023200908,0.0033235839,0.001992723,0.0017323847,0.0004195469],"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":[0.00013765006,0.00009725152,0.0020287535,0.00031864108,0.00019448459,0.00020184064,0.00027652236,0.5877457,0.0047604586,0.11544936,0.0014886438,0.28730068],"study_design_scores_gemma":[0.000008063746,0.000080855345,0.00026706874,0.000019285677,0.000015249112,0.00007303125,0.000024454734,0.95097256,0.0021066337,0.045086287,0.0013222184,0.000024396591],"about_ca_topic_score_codex":0.0026748804,"about_ca_topic_score_gemma":0.0017558066,"teacher_disagreement_score":0.0082811825,"about_ca_system_score_codex":0.0011830261,"about_ca_system_score_gemma":0.0013122339,"threshold_uncertainty_score":0.043795645},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001383678,0.00034947728,0.99611723,0.00010242548,0.00001970598,0.000018951723,0.00001552409,0.000048567843,0.001944407],"genre_scores_gemma":[0.13949284,0.002633068,0.851184,0.00014682053,0.00007456378,0.0003255109,0.00016573412,0.00009871853,0.005878781],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932086,0.00032944154,0.000041598254,0.00009366876,0.00018407124,0.000030454721],"domain_scores_gemma":[0.99953663,0.0002603023,0.000059364254,0.000070937385,0.000060210667,0.000012691378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009977905,0.0007781917,0.00039701414,0.00063497096,0.0003435888,0.0010991357,0.00078614784,0.0006823266,0.0030567544],"category_scores_gemma":[0.0010946039,0.0005500076,0.00092324876,0.0009975643,0.0011679946,0.0013365995,0.0008054375,0.0008812756,0.00057743175],"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":[0.000019192972,0.000031743817,0.0006501273,0.00027401143,0.000055257657,0.00024387913,0.00035163737,0.24361277,0.0053366316,0.63432425,0.0029223007,0.11217828],"study_design_scores_gemma":[0.0000118198,0.00008042808,0.00036391077,0.000085276595,0.00003605597,0.00025257896,0.00010700825,0.68592745,0.0040909876,0.2495487,0.05946933,0.000026514197],"about_ca_topic_score_codex":0.0016062083,"about_ca_topic_score_gemma":0.0012529566,"teacher_disagreement_score":0.0030567544,"about_ca_system_score_codex":0.0009312437,"about_ca_system_score_gemma":0.0005176925,"threshold_uncertainty_score":0.010225892},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8809832,0.00128399,0.10899998,0.0006299958,0.00006297327,0.000105413725,0.00006100249,0.00011984774,0.007753509],"genre_scores_gemma":[0.9962967,0.00028507443,0.0026408294,0.00004575249,0.000028025608,0.000012921413,0.0000103865295,0.000008199357,0.0006721042],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99804187,0.00072939816,0.00011040089,0.000254554,0.0003618739,0.0005018542],"domain_scores_gemma":[0.9306981,0.05565346,0.008218239,0.0019148556,0.0023205623,0.001194785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048654703,0.0009390957,0.0008723721,0.0005367911,0.0005704744,0.0011971953,0.0012507836,0.0013177376,0.0031801928],"category_scores_gemma":[0.041714873,0.0003880027,0.00083919405,0.00037063792,0.0024059047,0.0028323357,0.0011728895,0.0017575165,0.00016061074],"study_design_candidate":"observational","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":[0.0010499632,0.0007085441,0.017099457,0.00036670163,0.00014126826,0.0008473743,0.00046509973,0.8855101,0.0048042247,0.025070371,0.00037809653,0.06355887],"study_design_scores_gemma":[0.00016628084,0.001779153,0.012880757,0.00009552823,0.000291429,0.00036175275,0.00044237674,0.9399566,0.00860844,0.03442012,0.00090404256,0.00009345452],"about_ca_topic_score_codex":0.0033582794,"about_ca_topic_score_gemma":0.0025196297,"teacher_disagreement_score":0.0048654703,"about_ca_system_score_codex":0.0018265261,"about_ca_system_score_gemma":0.0011345856,"threshold_uncertainty_score":0.025731385},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1249978,0.00064127345,0.8706997,0.0005350557,0.000045508692,0.00017454568,0.00017158265,0.00020212868,0.0025324682],"genre_scores_gemma":[0.9742968,0.00022981124,0.023677679,0.00005688194,0.000031647796,0.00017892067,0.0001364532,0.000032920838,0.0013589123],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99705184,0.0015675618,0.00012887103,0.00049936085,0.0003692634,0.00038304276],"domain_scores_gemma":[0.99109626,0.0070309006,0.0008889141,0.00019399759,0.00058520725,0.00020469839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005337109,0.0012589013,0.0029853657,0.00080491614,0.00055470056,0.0018027005,0.0010460818,0.0015383844,0.0019460743],"category_scores_gemma":[0.009194598,0.0010140009,0.0009599897,0.00089148304,0.0017037067,0.0012077678,0.0010055084,0.0011518839,0.0001574642],"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":[0.000034728,0.000013871798,0.000102098515,0.000023129422,0.000013507313,0.000024059626,0.000008563423,0.99676573,0.00018234701,0.0015717773,0.00004166505,0.0012186089],"study_design_scores_gemma":[0.000016269194,0.000035759454,0.000098411925,0.0000038066776,0.0000049467517,0.000004225132,0.0000047305703,0.99733174,0.00016898396,0.0022673307,0.000060250495,0.0000035795433],"about_ca_topic_score_codex":0.008935412,"about_ca_topic_score_gemma":0.0024141427,"teacher_disagreement_score":0.008935412,"about_ca_system_score_codex":0.0020608783,"about_ca_system_score_gemma":0.0018073329,"threshold_uncertainty_score":0.02822566},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047915943,0.0009381419,0.93765545,0.00066985004,0.00003945333,0.00011247647,0.00024062395,0.00016595652,0.0122620305],"genre_scores_gemma":[0.7904779,0.0019185294,0.19630383,0.000196376,0.00016009426,0.0003012262,0.00059127226,0.000068793786,0.009982027],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990662,0.00038708045,0.00002197044,0.0001668156,0.00017985793,0.00017816646],"domain_scores_gemma":[0.9983784,0.0010783446,0.00024305945,0.000101937905,0.00012053402,0.00007775897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009174162,0.00095369125,0.0009168774,0.0007670044,0.00068574713,0.0012912399,0.0013730773,0.0019099133,0.0027932764],"category_scores_gemma":[0.004067083,0.0005087192,0.0008009723,0.0016525035,0.0011157411,0.0016374064,0.001546678,0.0009285233,0.000425259],"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":[0.000047137277,0.00005082378,0.0006803175,0.00009380734,0.000033466094,0.00023402741,0.000088973364,0.93342423,0.00047526188,0.03706967,0.002262478,0.025539784],"study_design_scores_gemma":[0.000028935103,0.00008253354,0.00033291226,0.000014556978,0.000018784545,0.00026664036,0.00014314978,0.9455013,0.00032932506,0.048991088,0.004275752,0.0000149943935],"about_ca_topic_score_codex":0.0033825934,"about_ca_topic_score_gemma":0.0025250139,"teacher_disagreement_score":0.0033825934,"about_ca_system_score_codex":0.0008759905,"about_ca_system_score_gemma":0.00061993167,"threshold_uncertainty_score":0.009344459},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018747518,0.00009619076,0.97577524,0.00019709053,0.000015053482,0.00016356795,0.00021524502,0.0001440561,0.0046460438],"genre_scores_gemma":[0.26758453,0.00023139146,0.73010755,0.000056075238,0.000022592449,0.0007147555,0.0006116135,0.00005516809,0.0006162711],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9847009,0.007609127,0.0014977332,0.0010563022,0.0047609545,0.0003750465],"domain_scores_gemma":[0.96731645,0.020687602,0.0032504331,0.003099833,0.00546393,0.00018179955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02146108,0.0010275817,0.0011174956,0.0049690823,0.00081612583,0.004052646,0.001075721,0.00084980414,0.0017343417],"category_scores_gemma":[0.06076804,0.00073330035,0.0011465405,0.0061078696,0.0018060894,0.004863105,0.0031161695,0.0021388645,0.00055724266],"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":[0.00006365047,0.00014719287,0.0030597965,0.00016231861,0.0000705245,0.00003713163,0.00031653675,0.38542864,0.0012299134,0.49668676,0.0010179144,0.111779615],"study_design_scores_gemma":[0.000036111927,0.00011173376,0.0015875717,0.00013022573,0.000023128432,0.000022880176,0.00015134714,0.65531355,0.0034928957,0.33226857,0.00681414,0.00004783305],"about_ca_topic_score_codex":0.002901222,"about_ca_topic_score_gemma":0.002327996,"teacher_disagreement_score":0.02146108,"about_ca_system_score_codex":0.0042618047,"about_ca_system_score_gemma":0.0041531147,"threshold_uncertainty_score":0.11349839},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33011442,0.007861624,0.45442483,0.030158957,0.00068460626,0.00012892883,0.0012419099,0.00041827434,0.17496634],"genre_scores_gemma":[0.98553157,0.0012639114,0.008521884,0.000653341,0.00014705115,0.000058750073,0.00010539864,0.000054445936,0.0036636547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970041,0.00112613,0.000117132324,0.000583648,0.00037785326,0.00079113164],"domain_scores_gemma":[0.9822465,0.012749321,0.0020196398,0.001666989,0.00049700786,0.0008204909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038891954,0.00089736545,0.0010060343,0.00076864916,0.00085930043,0.004014186,0.0015437668,0.0028341424,0.012619933],"category_scores_gemma":[0.031066127,0.0007296834,0.0012812915,0.0014078928,0.0038380746,0.007524335,0.0027233555,0.0022907974,0.0007362187],"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":[0.00019763254,0.0000458645,0.0023791343,0.00023770705,0.00010299967,0.0005067394,0.00036313845,0.2050459,0.00077368814,0.7538522,0.004034887,0.0324601],"study_design_scores_gemma":[0.000020617983,0.000042368018,0.0008551526,0.00009089363,0.000020598723,0.00017082162,0.00028630003,0.07429209,0.00026073458,0.917445,0.006469193,0.000046286485],"about_ca_topic_score_codex":0.0030983433,"about_ca_topic_score_gemma":0.0022342764,"teacher_disagreement_score":0.012619933,"about_ca_system_score_codex":0.0013255185,"about_ca_system_score_gemma":0.0011799632,"threshold_uncertainty_score":0.04221791},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11706006,0.0006000174,0.8671385,0.00031176308,0.00004381253,0.0002504252,0.0001753329,0.0002079276,0.014212046],"genre_scores_gemma":[0.8349154,0.00061212375,0.15945248,0.00007327388,0.000025322244,0.00032627207,0.00017153026,0.00003997838,0.004383668],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987124,0.0004744272,0.000046359553,0.00023347056,0.00028054143,0.00025287658],"domain_scores_gemma":[0.9991373,0.00035652114,0.0001791114,0.000050033977,0.00014174785,0.00013529362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014917381,0.0011460868,0.001230094,0.0008689455,0.0006180895,0.0019368145,0.0011621907,0.0012047023,0.0032511558],"category_scores_gemma":[0.0022084413,0.0010286111,0.0010417105,0.0015756823,0.00093919685,0.0013706719,0.0017367284,0.00093240314,0.00035315062],"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":[0.00003279279,0.000026295396,0.00020509609,0.00003228161,0.000020045332,0.000045811943,0.000021548347,0.9871639,0.000588789,0.0046794964,0.00009581816,0.007087979],"study_design_scores_gemma":[0.000030015617,0.00011191405,0.0001177388,0.000010825054,0.000023397753,0.00001948036,0.000032949738,0.98935306,0.00054876186,0.008754438,0.0009888585,0.000008486188],"about_ca_topic_score_codex":0.0041143093,"about_ca_topic_score_gemma":0.0048007546,"teacher_disagreement_score":0.0041143093,"about_ca_system_score_codex":0.0018688856,"about_ca_system_score_gemma":0.0025070258,"threshold_uncertainty_score":0.013559818},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06280282,0.00041767786,0.9326323,0.00047181154,0.000015453941,0.000059967515,0.0001353947,0.00012004324,0.003344418],"genre_scores_gemma":[0.9235753,0.0004361809,0.07462199,0.000080538295,0.000016277585,0.00013487316,0.00015167451,0.000039405455,0.000943751],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99490166,0.0026780781,0.00027253866,0.0005052348,0.0013381551,0.00030433794],"domain_scores_gemma":[0.98484427,0.011310002,0.0011922076,0.0014070728,0.0011656948,0.00008070246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011082775,0.0011674995,0.0012211662,0.0010982434,0.0004960291,0.0024095948,0.0008277738,0.0011284304,0.000731142],"category_scores_gemma":[0.04294536,0.0006356975,0.0009983339,0.0021354803,0.0020293535,0.0031964716,0.0023574133,0.0021351003,0.0001447856],"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":[0.00007629509,0.00003225999,0.0032261254,0.0001183443,0.00004073851,0.000089028195,0.0002163638,0.92239195,0.0010778223,0.05476286,0.00024547082,0.01772272],"study_design_scores_gemma":[0.0000067156443,0.000049052855,0.0009103106,0.000030003486,0.000011272918,0.000038118917,0.000042992197,0.9578894,0.001539736,0.038830616,0.00063263724,0.000019167232],"about_ca_topic_score_codex":0.0040731486,"about_ca_topic_score_gemma":0.0014195329,"teacher_disagreement_score":0.011082775,"about_ca_system_score_codex":0.0022205422,"about_ca_system_score_gemma":0.001280817,"threshold_uncertainty_score":0.05861199},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84266543,0.0013737156,0.1388081,0.00022762988,0.00010432882,0.000082165,0.00011024387,0.0005275045,0.01610093],"genre_scores_gemma":[0.9838309,0.00028237898,0.013367025,0.000042689768,0.000013421229,0.000035400313,0.00006055636,0.0001973266,0.0021702773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841833,0.0005024052,0.00008038261,0.00017084219,0.000451671,0.00037638677],"domain_scores_gemma":[0.99174833,0.0049206144,0.000925476,0.00062819663,0.0013599194,0.00041745734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025066433,0.000876359,0.00052832754,0.0010311194,0.00059823814,0.0006844094,0.00066463416,0.0003809266,0.0036645718],"category_scores_gemma":[0.009933426,0.00049957004,0.0004934622,0.00076526677,0.0004948546,0.00131127,0.0011150392,0.0008188858,0.0004940774],"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":[0.002127148,0.00027955702,0.0254559,0.0005138242,0.00020859446,0.0008190483,0.0007540823,0.6650659,0.14737146,0.010391276,0.0013448669,0.14566833],"study_design_scores_gemma":[0.00012238006,0.0029860302,0.0776985,0.00011257086,0.0005615167,0.0012682691,0.0011252059,0.6766448,0.21788429,0.009795122,0.011625984,0.00017535067],"about_ca_topic_score_codex":0.002194337,"about_ca_topic_score_gemma":0.0027556915,"teacher_disagreement_score":0.0036645718,"about_ca_system_score_codex":0.000666324,"about_ca_system_score_gemma":0.0010488179,"threshold_uncertainty_score":0.01325655},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00791013,0.0001549113,0.9915705,0.00003670371,0.000007036112,0.000010930437,0.00001437981,0.00008675246,0.00020863235],"genre_scores_gemma":[0.7458337,0.00059599435,0.25077984,0.000063614876,0.000080801954,0.00019631797,0.00021845802,0.00008155165,0.002149798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992741,0.00029097436,0.00003683872,0.00020547498,0.00015327657,0.000039339386],"domain_scores_gemma":[0.9961694,0.0024154393,0.000604253,0.00031040597,0.00045382185,0.000046718724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001999218,0.0007534921,0.00087107765,0.00062746607,0.00025283484,0.00064785744,0.001060891,0.0008850014,0.00093684765],"category_scores_gemma":[0.006356408,0.0004710976,0.0009112504,0.00045186467,0.00084146805,0.0014117024,0.0008584183,0.0011441016,0.0002358469],"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":[0.000094019095,0.00007930728,0.0022962783,0.00017230285,0.000091466776,0.00005682503,0.0001735534,0.8907359,0.004727131,0.0149152465,0.00046344442,0.08619448],"study_design_scores_gemma":[0.0000015970619,0.000010965507,0.00025751893,0.0000034402542,0.0000044888634,0.000011308541,0.000003391611,0.9972995,0.00039825638,0.001903901,0.000101198384,0.0000044410494],"about_ca_topic_score_codex":0.0021661092,"about_ca_topic_score_gemma":0.001965999,"teacher_disagreement_score":0.0021661092,"about_ca_system_score_codex":0.0005597437,"about_ca_system_score_gemma":0.0007598473,"threshold_uncertainty_score":0.01057297},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56489027,0.0007559091,0.42655903,0.0006488896,0.00007042632,0.000097461016,0.00051727035,0.00032203234,0.0061386414],"genre_scores_gemma":[0.9604209,0.00028756307,0.036913346,0.000025653739,0.000033535583,0.000047773843,0.00017607318,0.000029493078,0.0020656397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989247,0.0004416234,0.00004290105,0.0001964308,0.00016343947,0.00023086915],"domain_scores_gemma":[0.9973756,0.0014470211,0.00056706334,0.00017470845,0.0002535729,0.00018200358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011134439,0.00063256687,0.0007505243,0.000771481,0.00067625905,0.0016304952,0.0016126966,0.0014251792,0.002786914],"category_scores_gemma":[0.0057592415,0.0008314533,0.00044419168,0.0017393378,0.0012597572,0.0022344303,0.0013558593,0.0007055932,0.00030231208],"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":[0.00009022308,0.000017838029,0.0012622926,0.00005329064,0.000021458021,0.00033495162,0.000063821615,0.9840098,0.00062995387,0.008986726,0.00032819188,0.0042013847],"study_design_scores_gemma":[0.000022071974,0.000049772745,0.00047175356,0.000009563214,0.000016904747,0.0001580912,0.0001335422,0.9860525,0.00096978236,0.0112596005,0.0008399004,0.000016527156],"about_ca_topic_score_codex":0.004749652,"about_ca_topic_score_gemma":0.004068727,"teacher_disagreement_score":0.004749652,"about_ca_system_score_codex":0.0015514606,"about_ca_system_score_gemma":0.0008497827,"threshold_uncertainty_score":0.011256695},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00783604,0.0010805045,0.97753763,0.00047289763,0.0001027904,0.00014147273,0.0002772645,0.00096036826,0.011591077],"genre_scores_gemma":[0.14094555,0.0014868164,0.84927076,0.0002630264,0.00018218646,0.0005225637,0.000871818,0.00033737044,0.0061199293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979426,0.0005460496,0.00010242145,0.00030809344,0.00065244164,0.00044837035],"domain_scores_gemma":[0.99630165,0.0026946305,0.0002720887,0.0003029536,0.00033863055,0.000090025496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018908512,0.0017334883,0.0016169385,0.0013744328,0.001168149,0.002691951,0.0023180477,0.002033607,0.012417421],"category_scores_gemma":[0.00878365,0.0010711326,0.0011230974,0.00320021,0.0011175541,0.003292884,0.0016248627,0.0028085783,0.002103632],"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":[0.00020183416,0.00025593882,0.00030977742,0.00028041282,0.000044714106,0.000054920827,0.000119882294,0.71471155,0.0010240781,0.09003069,0.010653882,0.18231225],"study_design_scores_gemma":[0.00012253934,0.0000430953,0.0001275382,0.000027408718,0.000017311851,0.00003969046,0.000046611574,0.9074882,0.00045269803,0.088511,0.003110633,0.000013282498],"about_ca_topic_score_codex":0.008816683,"about_ca_topic_score_gemma":0.010188861,"teacher_disagreement_score":0.012417421,"about_ca_system_score_codex":0.0028191335,"about_ca_system_score_gemma":0.0041587157,"threshold_uncertainty_score":0.041540384},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35654837,0.0009618877,0.63712406,0.0005604667,0.00007081204,0.000048337257,0.00018380737,0.0002990342,0.004203216],"genre_scores_gemma":[0.9825394,0.00035310828,0.015520542,0.000021893453,0.000031497537,0.000043162785,0.00010316414,0.000032386,0.0013548564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982836,0.0007944642,0.00007104718,0.00023633345,0.00037226026,0.00024229907],"domain_scores_gemma":[0.9887138,0.007612684,0.0015617008,0.0006589149,0.0010700743,0.0003828115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048988783,0.0011430422,0.001095498,0.0014587214,0.00048134194,0.0017195867,0.0017692089,0.0013548409,0.0013118976],"category_scores_gemma":[0.019725023,0.0005627555,0.0005197919,0.001351209,0.0017314522,0.0021980614,0.0012802845,0.0012101197,0.0002175351],"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":[0.000025360616,0.000008205301,0.00039667802,0.000010087034,0.000008166424,0.00002040367,0.000022458018,0.98704547,0.00016064012,0.011060146,0.00010232089,0.0011400611],"study_design_scores_gemma":[9.0206584e-7,0.0000064680166,0.000078016536,0.0000019917622,0.0000014601646,0.000003910246,0.000005138035,0.9967997,0.000036304664,0.0030277008,0.000036515365,0.0000019158315],"about_ca_topic_score_codex":0.008219273,"about_ca_topic_score_gemma":0.002437979,"teacher_disagreement_score":0.008219273,"about_ca_system_score_codex":0.0029815345,"about_ca_system_score_gemma":0.0006517324,"threshold_uncertainty_score":0.025908053},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31825137,0.000762196,0.6702377,0.00040767484,0.000093362876,0.00039107533,0.0001753401,0.00070757855,0.00897363],"genre_scores_gemma":[0.8758106,0.0002616755,0.121118344,0.000077228695,0.000021732767,0.00011578705,0.000107145795,0.00007182802,0.0024156375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914837,0.00036542895,0.000036504596,0.000090378264,0.00010571481,0.00025360775],"domain_scores_gemma":[0.9976671,0.0014178068,0.00036661763,0.00017909841,0.00016222823,0.00020721422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017476011,0.0008363074,0.0009518557,0.00091671327,0.0005782981,0.0012254687,0.0012191428,0.00087926135,0.0038756046],"category_scores_gemma":[0.0032759816,0.00066889776,0.00042695692,0.0009978603,0.0009094636,0.0010711021,0.0007491594,0.00063213625,0.0003681735],"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":[0.00022318377,0.000097863965,0.00043454565,0.000050767525,0.000019751415,0.00010874474,0.00005792505,0.9752671,0.001417799,0.0073821847,0.0011389859,0.0138011435],"study_design_scores_gemma":[0.00005113249,0.00012071135,0.00019971469,0.000010119758,0.000010717952,0.000030675645,0.00006875237,0.9918828,0.0009158139,0.0060694353,0.0006265478,0.000013566513],"about_ca_topic_score_codex":0.0037577068,"about_ca_topic_score_gemma":0.004111021,"teacher_disagreement_score":0.0038756046,"about_ca_system_score_codex":0.0015741655,"about_ca_system_score_gemma":0.0011887097,"threshold_uncertainty_score":0.012965202},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29902765,0.00059809414,0.6979143,0.00026729188,0.000068862246,0.000025873682,0.000070048874,0.00038152255,0.001646378],"genre_scores_gemma":[0.9613092,0.0002365412,0.037124682,0.000058905713,0.00003281196,0.000027805829,0.00007109208,0.000056933295,0.0010820286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995559,0.00009293793,0.000025322906,0.00007223972,0.00013338235,0.000120243196],"domain_scores_gemma":[0.9980026,0.00108292,0.0003031249,0.00018016681,0.00030392263,0.00012715656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018794726,0.00051481306,0.00060933083,0.0007785607,0.00038028564,0.0007523743,0.001554392,0.00074020895,0.0009295369],"category_scores_gemma":[0.005797099,0.00030584188,0.0005223602,0.0007406626,0.0006669937,0.0013647836,0.0006456973,0.00093939644,0.00017480833],"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":[0.00008602323,0.000034201887,0.003271568,0.00003656033,0.000019503377,0.0001449084,0.00013406387,0.96248907,0.003086745,0.025357613,0.00034884163,0.0049909274],"study_design_scores_gemma":[0.0000025743198,0.0000058495575,0.00016553496,0.000001430202,0.0000024898393,0.000012021518,0.0000069221655,0.9978483,0.00017285605,0.0017268807,0.00005201288,0.0000031018067],"about_ca_topic_score_codex":0.0119314585,"about_ca_topic_score_gemma":0.00464308,"teacher_disagreement_score":0.0119314585,"about_ca_system_score_codex":0.0018519997,"about_ca_system_score_gemma":0.001259651,"threshold_uncertainty_score":0.02372402},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00871049,0.00020243881,0.98986816,0.00025671156,0.000015319703,0.00004784913,0.00023261512,0.0001488464,0.00051764585],"genre_scores_gemma":[0.42409796,0.0014239838,0.55697954,0.00030016928,0.00038536216,0.0008409437,0.003299264,0.0004171446,0.012255648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9932766,0.00414664,0.00033677305,0.0007897264,0.0011337642,0.00031654706],"domain_scores_gemma":[0.9454134,0.04637958,0.0033808392,0.0021670847,0.002222784,0.00043623446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015499071,0.0013294562,0.0020105736,0.0026067346,0.00079752674,0.0026964853,0.0037823264,0.0018123094,0.0052729836],"category_scores_gemma":[0.05607591,0.0014662859,0.0022488956,0.003692888,0.002095895,0.0047499696,0.0019291395,0.0027386919,0.0010729765],"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":[0.00037014994,0.00018735063,0.009291775,0.0005196551,0.0002461715,0.0010336854,0.000579623,0.6865611,0.0022129903,0.2091226,0.0036103704,0.086264506],"study_design_scores_gemma":[0.000015524029,0.000041230083,0.0012919599,0.000027064734,0.000022281982,0.00015339271,0.000038451413,0.97334576,0.00042865882,0.023266386,0.0013362733,0.000033073804],"about_ca_topic_score_codex":0.005151281,"about_ca_topic_score_gemma":0.0038642115,"teacher_disagreement_score":0.015499071,"about_ca_system_score_codex":0.0014391663,"about_ca_system_score_gemma":0.0026963686,"threshold_uncertainty_score":0.08196789},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38314193,0.0006590016,0.5975179,0.000927442,0.000034342218,0.00017458922,0.00018446559,0.00038686325,0.01697347],"genre_scores_gemma":[0.97984225,0.0001956865,0.018662302,0.00003677142,0.000010822774,0.00004885593,0.00005369803,0.000039097235,0.001110477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937505,0.0001601291,0.0000317443,0.00011210585,0.00017726737,0.00014381105],"domain_scores_gemma":[0.9994733,0.00023235408,0.0001086619,0.00005000829,0.00009532101,0.000040457875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068844564,0.0006062927,0.000718358,0.00047151023,0.00037935073,0.0017016788,0.0006451587,0.0006143873,0.0015538423],"category_scores_gemma":[0.0023340886,0.00035284186,0.00025776742,0.00093169237,0.00031766653,0.0015553567,0.00048589747,0.00048114406,0.00030243865],"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":[0.00008932625,0.00008610877,0.0025637995,0.00010246971,0.000032103242,0.00008641975,0.00012073836,0.92801213,0.010389187,0.017656216,0.0010650678,0.03979635],"study_design_scores_gemma":[0.000016876631,0.00009270815,0.0012659823,0.000010651554,0.000017852735,0.0000668575,0.00014587879,0.9790562,0.0030563583,0.014609911,0.00164646,0.000014322081],"about_ca_topic_score_codex":0.0024565263,"about_ca_topic_score_gemma":0.0024612374,"teacher_disagreement_score":0.0024565263,"about_ca_system_score_codex":0.0014208988,"about_ca_system_score_gemma":0.0015314603,"threshold_uncertainty_score":0.010309398},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020298025,0.049459875,0.70997924,0.06388618,0.002875244,0.000121724064,0.00051936024,0.00016065157,0.15269968],"genre_scores_gemma":[0.86654824,0.018814191,0.094347276,0.0047675353,0.005023041,0.0004530966,0.00017669606,0.00010027459,0.009769728],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98593223,0.008480109,0.00066352024,0.0016864398,0.0026126243,0.000625154],"domain_scores_gemma":[0.9684427,0.026154982,0.0021514706,0.0012545822,0.0013038818,0.0006924434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013868082,0.0012039101,0.0015054761,0.003949543,0.0033041432,0.0090377,0.0022266665,0.0048292265,0.005698132],"category_scores_gemma":[0.035990864,0.00057494314,0.0013721008,0.0033409551,0.031593613,0.014636458,0.0040286784,0.0056222407,0.00065388874],"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":[0.000007604061,0.0000020740542,0.00009858482,0.00003825044,0.000007716063,0.000028104389,0.00020804867,0.0007646803,0.000020715705,0.9959085,0.0005107095,0.0024050674],"study_design_scores_gemma":[0.0000034176667,0.000009425787,0.00012956138,0.00006467332,0.0000064560695,0.000051957893,0.000120604964,0.0011549178,0.000034293273,0.99132055,0.0070929895,0.000011079536],"about_ca_topic_score_codex":0.003164369,"about_ca_topic_score_gemma":0.0021238392,"teacher_disagreement_score":0.013868082,"about_ca_system_score_codex":0.004815917,"about_ca_system_score_gemma":0.00245535,"threshold_uncertainty_score":0.07334226},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021695942,0.00020671349,0.99586946,0.00010001427,0.000013591196,0.0000558721,0.000035252844,0.000022944061,0.0015265001],"genre_scores_gemma":[0.25956622,0.0008743692,0.73606074,0.00013938807,0.00007207948,0.00086410495,0.00015891223,0.0000774057,0.002186833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9819936,0.012553499,0.000666923,0.0013884058,0.0027675452,0.0006299907],"domain_scores_gemma":[0.9828835,0.013292078,0.00095552794,0.0015816392,0.0010246238,0.0002625991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020081263,0.002295437,0.0027956406,0.0041433857,0.0010722419,0.0043834457,0.0021039075,0.0019152063,0.0027997699],"category_scores_gemma":[0.033861432,0.0013794597,0.0027731168,0.005204369,0.0031527367,0.004785181,0.00337921,0.0043318435,0.000765071],"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":[0.00006749083,0.0000751758,0.0009733195,0.00017228306,0.000118588105,0.000077376695,0.00022986176,0.3420899,0.0005659686,0.6191489,0.00057278614,0.035908308],"study_design_scores_gemma":[0.00002337506,0.000058955295,0.0002067822,0.0000765454,0.00002281886,0.000042670938,0.00007588268,0.5910956,0.0006017682,0.40216738,0.0055826567,0.000045529276],"about_ca_topic_score_codex":0.003309672,"about_ca_topic_score_gemma":0.002377488,"teacher_disagreement_score":0.020081263,"about_ca_system_score_codex":0.003995856,"about_ca_system_score_gemma":0.0029973185,"threshold_uncertainty_score":0.10620117},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33930528,0.0041399794,0.49736413,0.053669605,0.00047845012,0.0005610173,0.0021446566,0.00031661015,0.10202027],"genre_scores_gemma":[0.9676719,0.0012249666,0.021228332,0.0009161508,0.00018090731,0.00012733688,0.00016891517,0.000032678752,0.008448885],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9939557,0.002366769,0.00028604016,0.0010339203,0.0011916056,0.001165952],"domain_scores_gemma":[0.9809249,0.013424956,0.002977179,0.0012510858,0.00057921524,0.00084268843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009239401,0.0008945893,0.0012041017,0.00074187375,0.0013110971,0.00428243,0.001393625,0.005178897,0.011524759],"category_scores_gemma":[0.035014722,0.0012766509,0.001457401,0.0007962374,0.00286776,0.008392424,0.002151255,0.0059306645,0.00073307985],"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":[0.00066495617,0.00016225375,0.0049706264,0.0001582135,0.00011880218,0.0011255519,0.00043825185,0.251754,0.0016072285,0.69869256,0.003148183,0.03715932],"study_design_scores_gemma":[0.000167778,0.00019779846,0.0027909637,0.000079426434,0.00009688748,0.00033533768,0.00018206815,0.1583328,0.0011817735,0.828206,0.008330208,0.000098920034],"about_ca_topic_score_codex":0.004816817,"about_ca_topic_score_gemma":0.005309739,"teacher_disagreement_score":0.011524759,"about_ca_system_score_codex":0.004455193,"about_ca_system_score_gemma":0.005012441,"threshold_uncertainty_score":0.048863232},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029212544,0.00007713314,0.9952572,0.00004575338,0.000030451503,0.000042770254,0.000045840166,0.00040860678,0.0011710515],"genre_scores_gemma":[0.029924009,0.00007439041,0.9682745,0.000037007238,0.000028624097,0.00010339992,0.0001726501,0.000084753236,0.0013007368],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992499,0.0001652176,0.00005524436,0.0001542636,0.0002829457,0.00009238508],"domain_scores_gemma":[0.9990619,0.0004777089,0.00006970718,0.00015647736,0.00020110897,0.00003313676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010125798,0.0006608334,0.0010490393,0.0009893526,0.00056810357,0.0008579723,0.0023169178,0.0013279814,0.0065099197],"category_scores_gemma":[0.0032636453,0.00043805392,0.0007950765,0.0012668057,0.00034128316,0.001600207,0.0010047699,0.0014596477,0.0016532699],"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":[0.00019963848,0.00015057495,0.0007989409,0.0002458255,0.00007183944,0.00020444569,0.00011798954,0.4314284,0.007734929,0.029387424,0.008669574,0.52099043],"study_design_scores_gemma":[0.00006062539,0.000049896345,0.00015379903,0.000014176111,0.000015084061,0.0001157297,0.000015460868,0.984806,0.0015609801,0.007908845,0.005288711,0.000010551724],"about_ca_topic_score_codex":0.0032631177,"about_ca_topic_score_gemma":0.004559136,"teacher_disagreement_score":0.0065099197,"about_ca_system_score_codex":0.0005103168,"about_ca_system_score_gemma":0.001385416,"threshold_uncertainty_score":0.021777868},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48722255,0.0045349468,0.40986043,0.003996931,0.00042900426,0.001417832,0.07539415,0.0060064537,0.011137763],"genre_scores_gemma":[0.8136439,0.0011748134,0.14344288,0.00016914924,0.00009882321,0.0006982915,0.03975726,0.00007242089,0.0009425358],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99679035,0.0005334438,0.00070971256,0.00075854326,0.0009838191,0.00022408836],"domain_scores_gemma":[0.9872671,0.005446102,0.0025683143,0.0012196033,0.0031483315,0.0003506222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033274798,0.0014565145,0.0014277202,0.013374622,0.0006652194,0.0019302901,0.0014162388,0.000885726,0.0009269022],"category_scores_gemma":[0.020278422,0.00033217174,0.0012944734,0.0091965655,0.00050711544,0.0019785857,0.0013659813,0.0012049719,0.00062003895],"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":[0.000668601,0.00063969,0.24628937,0.002060057,0.0011361915,0.0014396678,0.0008996453,0.116937466,0.006969149,0.010202127,0.01928352,0.59347445],"study_design_scores_gemma":[0.0001141982,0.0006221251,0.13987967,0.0007716863,0.000613262,0.0014054566,0.002799969,0.7246203,0.03209435,0.052583147,0.044218984,0.00027692068],"about_ca_topic_score_codex":0.0038645898,"about_ca_topic_score_gemma":0.003426794,"teacher_disagreement_score":0.013374622,"about_ca_system_score_codex":0.0011489497,"about_ca_system_score_gemma":0.0014301874,"threshold_uncertainty_score":0.017597556},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033087615,0.000085127154,0.96401757,0.00021051658,0.000016420467,0.00006298884,0.00010860954,0.00011141526,0.002299741],"genre_scores_gemma":[0.5834979,0.00024369884,0.4116734,0.00014428905,0.000041940963,0.0002700414,0.00037363375,0.00007211436,0.003682999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990264,0.0004181345,0.00004580038,0.00017477895,0.00016640317,0.00016844772],"domain_scores_gemma":[0.9986325,0.000989477,0.00015591254,0.00005476063,0.00011116192,0.0000560633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020020609,0.0010348654,0.001119359,0.00068816193,0.00046270675,0.0013498714,0.0008817448,0.0014399792,0.0026599474],"category_scores_gemma":[0.0026495203,0.00083409104,0.0013951649,0.000808849,0.00084267964,0.0010622694,0.0009839545,0.0014116814,0.00022516587],"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":[0.000028263068,0.000018466933,0.0001443058,0.000023133405,0.000013285271,0.000021802529,0.000014765475,0.9881948,0.00033595815,0.0068914182,0.00013822608,0.0041756136],"study_design_scores_gemma":[0.0000088442885,0.000016140433,0.00003160243,0.0000028459822,0.0000040646432,0.0000063654006,0.0000069256807,0.9946221,0.00014582454,0.00502745,0.00012518938,0.0000026110997],"about_ca_topic_score_codex":0.008472712,"about_ca_topic_score_gemma":0.0054116384,"teacher_disagreement_score":0.008472712,"about_ca_system_score_codex":0.0014972605,"about_ca_system_score_gemma":0.0023101335,"threshold_uncertainty_score":0.016846776},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.708833,0.0011614541,0.27593842,0.00096224627,0.00013850268,0.00036992054,0.00022935083,0.00043633705,0.011930857],"genre_scores_gemma":[0.9930205,0.00015410194,0.0057706614,0.00003887822,0.000014002755,0.000021668044,0.000033724777,0.000010725192,0.00093581673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849176,0.00043028404,0.000071734525,0.00019525536,0.00018763043,0.000623268],"domain_scores_gemma":[0.99533963,0.0024354071,0.00091377686,0.00019609538,0.0004574703,0.00065755117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019111154,0.0011754306,0.0014167887,0.00077619427,0.00069932453,0.003071412,0.0019140862,0.0013041657,0.0028939284],"category_scores_gemma":[0.0063291495,0.00074007595,0.00071261614,0.00076308247,0.0013593445,0.002047097,0.001443083,0.0014685126,0.0003528005],"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":[0.00066326465,0.00032249317,0.00239981,0.00007792867,0.00004634789,0.00015462902,0.00010164512,0.9769712,0.0027971677,0.00609154,0.0006282925,0.009745688],"study_design_scores_gemma":[0.000028233593,0.00009330918,0.00051232247,0.000008306909,0.000019878496,0.000021838629,0.000115867064,0.9961266,0.00093556487,0.0020017182,0.0001243378,0.000012019503],"about_ca_topic_score_codex":0.0112977745,"about_ca_topic_score_gemma":0.006116899,"teacher_disagreement_score":0.0112977745,"about_ca_system_score_codex":0.0034587886,"about_ca_system_score_gemma":0.0028007473,"threshold_uncertainty_score":0.025095344},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24591759,0.0006125231,0.7431317,0.0003352143,0.000039950435,0.00008327506,0.0003196515,0.00040576875,0.009154384],"genre_scores_gemma":[0.9893713,0.000172294,0.00772187,0.000016714786,0.000010049164,0.00004834421,0.00007399955,0.000016812068,0.0025686547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966,0.000067559646,0.00001876375,0.000097824755,0.00008784205,0.00006810771],"domain_scores_gemma":[0.9993549,0.0003104047,0.0001574021,0.000043671815,0.0001048464,0.000028773125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007995189,0.0007618981,0.0006375414,0.00069624226,0.00042137862,0.0007779025,0.0009679754,0.00071617466,0.001842562],"category_scores_gemma":[0.001278204,0.0003079074,0.00070743065,0.0005090624,0.0008856736,0.00093510957,0.0006111006,0.000560332,0.0001848288],"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":[0.00003686889,0.0000131289935,0.00051056995,0.00002547844,0.000013644222,0.000082502454,0.000050905128,0.98882943,0.0010501418,0.006509059,0.00013211394,0.002746211],"study_design_scores_gemma":[0.0000021218427,0.000013179704,0.0001700999,0.0000016792267,0.0000063902626,0.000008699504,0.0000066943257,0.9983222,0.0001157939,0.0012680396,0.00008291706,0.0000021683338],"about_ca_topic_score_codex":0.010944878,"about_ca_topic_score_gemma":0.007150991,"teacher_disagreement_score":0.010944878,"about_ca_system_score_codex":0.0009687767,"about_ca_system_score_gemma":0.00057948683,"threshold_uncertainty_score":0.021762311},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38799712,0.00093528815,0.55764925,0.003246519,0.00019907452,0.00045477183,0.00091331813,0.0004000065,0.048204694],"genre_scores_gemma":[0.97027135,0.0004865798,0.01428436,0.00006860767,0.00003878204,0.00012499384,0.00017099317,0.000038998158,0.014515312],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989705,0.0003051894,0.000026097674,0.00017909808,0.00028292215,0.00023616204],"domain_scores_gemma":[0.9983954,0.0009610776,0.0002875075,0.00009639989,0.00013845028,0.00012116466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015897561,0.0010255573,0.0012675746,0.0007669846,0.00066274137,0.0014289512,0.0016020569,0.0023897216,0.0076140473],"category_scores_gemma":[0.0037091626,0.0009228095,0.0008395811,0.000794911,0.0008107283,0.0022487233,0.0007757838,0.00202345,0.0006786295],"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":[0.00026400608,0.00011065294,0.0012407991,0.000100731624,0.000039652554,0.0002703506,0.0000496697,0.9512137,0.0024871528,0.027304431,0.0008221707,0.016096668],"study_design_scores_gemma":[0.000035840905,0.0002565848,0.0018955301,0.000033101267,0.000061574836,0.00012559815,0.00006214982,0.98764485,0.0011066815,0.0070642913,0.0016850159,0.00002883792],"about_ca_topic_score_codex":0.007443573,"about_ca_topic_score_gemma":0.008904509,"teacher_disagreement_score":0.0076140473,"about_ca_system_score_codex":0.0026640464,"about_ca_system_score_gemma":0.0022456057,"threshold_uncertainty_score":0.025471509},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15291376,0.0012476449,0.8342798,0.00088771636,0.000062981395,0.00008171988,0.0007644665,0.00020216512,0.00955981],"genre_scores_gemma":[0.9346729,0.000842658,0.060238875,0.000071886716,0.00008107438,0.0001267933,0.00057562575,0.00007024196,0.0033199212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815,0.0010557439,0.00005700253,0.0002515458,0.00020890246,0.00027686724],"domain_scores_gemma":[0.99689204,0.0024413955,0.00025514566,0.00014557017,0.00013523031,0.00013058212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017235695,0.0009433554,0.0013169841,0.0006251015,0.00053916377,0.0016563124,0.0013219909,0.0014633399,0.0024412978],"category_scores_gemma":[0.0057243276,0.0007929633,0.0012109344,0.0014707876,0.0010835278,0.0023232012,0.0011086857,0.0009130303,0.00019332115],"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":[0.000051304727,0.000014839704,0.00035541964,0.00005790403,0.00003860773,0.00010506255,0.000053773045,0.9751949,0.00029152163,0.016664239,0.0006547775,0.0065176655],"study_design_scores_gemma":[0.000019045496,0.000032584976,0.0002747233,0.00001061395,0.000014891326,0.0000933922,0.000048648293,0.9676347,0.0002594968,0.03067833,0.00092252495,0.000011112213],"about_ca_topic_score_codex":0.0064382395,"about_ca_topic_score_gemma":0.0030368317,"teacher_disagreement_score":0.0064382395,"about_ca_system_score_codex":0.001782171,"about_ca_system_score_gemma":0.0008418262,"threshold_uncertainty_score":0.012930572},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38253403,0.0003249119,0.6084021,0.00041537016,0.000026441501,0.00011761718,0.00023617204,0.0003793235,0.0075640916],"genre_scores_gemma":[0.990361,0.000091374066,0.00879685,0.000014127096,0.000007153148,0.000037858958,0.00007053383,0.000022360977,0.0005986726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967771,0.0015745198,0.0001104873,0.00035558618,0.0009180406,0.00026420841],"domain_scores_gemma":[0.996049,0.0023640213,0.00071673194,0.00035394993,0.0003868245,0.00012949512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002189172,0.00064794207,0.0007623709,0.0007414469,0.0003225238,0.0009839016,0.00056818017,0.0007301422,0.000873629],"category_scores_gemma":[0.011741933,0.0003869549,0.00047229155,0.0015323864,0.0005675431,0.0013406313,0.0011035159,0.000668001,0.00015162621],"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":[0.000049943486,0.00002719073,0.002072949,0.000036096488,0.000029408126,0.000043782267,0.000046047717,0.9833535,0.002572719,0.0046514887,0.000114912145,0.007002047],"study_design_scores_gemma":[0.0000029477892,0.000052129864,0.0015366927,0.000005933157,0.000008421449,0.00001564148,0.00005087985,0.99360996,0.0014927753,0.002986492,0.00022673029,0.000011347135],"about_ca_topic_score_codex":0.004055224,"about_ca_topic_score_gemma":0.00180556,"teacher_disagreement_score":0.004055224,"about_ca_system_score_codex":0.0017824662,"about_ca_system_score_gemma":0.0010501347,"threshold_uncertainty_score":0.012932718},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8867215,0.0005569268,0.108936764,0.0002828684,0.0000706728,0.00006171344,0.000112276946,0.000222533,0.0030346916],"genre_scores_gemma":[0.99470454,0.000065243505,0.0046088737,0.000010036955,0.000011927593,0.000009349031,0.00001860206,0.00001200895,0.0005593571],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910563,0.0002416156,0.000039214512,0.00015785493,0.00013405539,0.00032156555],"domain_scores_gemma":[0.998431,0.00076073286,0.00030416332,0.000110303095,0.0001411284,0.00025248292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016054652,0.00091809424,0.0011442585,0.000822335,0.0012907604,0.0014971416,0.0015806931,0.0011624625,0.002385577],"category_scores_gemma":[0.0022443368,0.00061938365,0.001018107,0.0008605111,0.0011077446,0.0013266363,0.0011614265,0.0007355683,0.00018036804],"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":[0.00021624318,0.000060654213,0.0013284794,0.000048284848,0.00002366724,0.00029407753,0.000050891056,0.9884213,0.0020156146,0.0021272614,0.00022975715,0.005183851],"study_design_scores_gemma":[0.000015849348,0.00012190043,0.00056081096,0.000004165229,0.000018152072,0.00009734537,0.000060095208,0.99716526,0.0006324844,0.0011730583,0.00014082868,0.0000099838735],"about_ca_topic_score_codex":0.011449891,"about_ca_topic_score_gemma":0.008961593,"teacher_disagreement_score":0.011449891,"about_ca_system_score_codex":0.0026834398,"about_ca_system_score_gemma":0.0011768528,"threshold_uncertainty_score":0.02276653},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5785586,0.00029583857,0.41759524,0.00019241945,0.000015723062,0.00017322748,0.000107560205,0.00027324466,0.0027881123],"genre_scores_gemma":[0.985405,0.00007860184,0.013867106,0.000018165127,0.0000044902113,0.00007459444,0.000044220833,0.000018998731,0.0004887787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993925,0.00028623146,0.000021579,0.00010446149,0.00007125489,0.00012400319],"domain_scores_gemma":[0.9982356,0.0010173055,0.00042828574,0.000091407834,0.00012083131,0.00010661566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017081829,0.0010695884,0.000970086,0.00053826516,0.00041379727,0.001177805,0.00074269995,0.0007422037,0.00085193565],"category_scores_gemma":[0.003272662,0.0005177675,0.0004176471,0.00047467236,0.0009031271,0.00064046006,0.0005799593,0.00067936396,0.00012297851],"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":[0.000040224644,0.000028079132,0.00016475486,0.000009576768,0.000006371186,0.000025372536,0.000011290176,0.9966708,0.0009955079,0.0003053898,0.000035611272,0.0017071606],"study_design_scores_gemma":[0.000014417496,0.00007844067,0.00024609343,0.0000022541553,0.0000048509323,0.000004303807,0.000015320804,0.99795365,0.0009938385,0.00062980305,0.000053880136,0.000003061441],"about_ca_topic_score_codex":0.0044078506,"about_ca_topic_score_gemma":0.002087578,"teacher_disagreement_score":0.0044078506,"about_ca_system_score_codex":0.0011840295,"about_ca_system_score_gemma":0.0009557032,"threshold_uncertainty_score":0.009033799},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42116567,0.0006480411,0.56129116,0.0017726723,0.00015049546,0.00006145698,0.00025497907,0.00034383705,0.014311656],"genre_scores_gemma":[0.9739406,0.00031048612,0.022450574,0.00014408669,0.00015044112,0.00006620233,0.00019505846,0.00011001166,0.0026324957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99793696,0.00064353435,0.00008061924,0.00045398,0.0005035619,0.0003812793],"domain_scores_gemma":[0.9526476,0.036297422,0.0036526877,0.002478793,0.00277383,0.0021496525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056365905,0.0005064713,0.0014786756,0.00235606,0.0011870775,0.003016122,0.0016567373,0.0009893936,0.0074203396],"category_scores_gemma":[0.049536042,0.0004206845,0.0008057422,0.0010860184,0.0056283916,0.005662853,0.002155221,0.0023100148,0.00050152506],"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":[0.00019214579,0.00005437696,0.0076147374,0.00007566735,0.00004129316,0.00019932157,0.00018624653,0.07832158,0.0015830018,0.8982792,0.0019539737,0.011498498],"study_design_scores_gemma":[0.00003421113,0.00005104945,0.0013873909,0.000037296748,0.000019348709,0.00012555535,0.00007586482,0.38849384,0.0013665984,0.6074693,0.00090664474,0.00003292488],"about_ca_topic_score_codex":0.0016558606,"about_ca_topic_score_gemma":0.0008685614,"teacher_disagreement_score":0.0074203396,"about_ca_system_score_codex":0.001132385,"about_ca_system_score_gemma":0.00120715,"threshold_uncertainty_score":0.029809475},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.072927065,0.0014008608,0.9176003,0.00030513218,0.00008268602,0.0001228421,0.000088697474,0.0001244061,0.0073480257],"genre_scores_gemma":[0.9132092,0.0007447096,0.08078383,0.000052197687,0.000048954265,0.00020218696,0.00006483315,0.000066393666,0.004827734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983511,0.00078955234,0.000048277187,0.0001814478,0.0004010903,0.0002285298],"domain_scores_gemma":[0.99793684,0.0015032324,0.00023301398,0.00006667996,0.00016701619,0.0000932195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023590378,0.001685992,0.001999791,0.0010067319,0.00081014796,0.0019781939,0.0011676113,0.0016035113,0.0031702013],"category_scores_gemma":[0.0054670214,0.0014215201,0.0014715721,0.0008618626,0.0010632308,0.0016839163,0.0010192741,0.0012438856,0.00021780904],"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":[0.000017867089,0.0000059111608,0.000092793496,0.000029026329,0.000012398038,0.000035034813,0.000011860871,0.994344,0.00028569356,0.0031776775,0.00004512051,0.0019426298],"study_design_scores_gemma":[0.000011858125,0.00005693268,0.000106881314,0.000009835523,0.00002504282,0.000025880156,0.000009463259,0.99478626,0.00036256964,0.004228401,0.0003703322,0.0000064306882],"about_ca_topic_score_codex":0.0048019052,"about_ca_topic_score_gemma":0.0033106504,"teacher_disagreement_score":0.0048019052,"about_ca_system_score_codex":0.002631599,"about_ca_system_score_gemma":0.0023010941,"threshold_uncertainty_score":0.019093692},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014508554,0.00002056947,0.99795145,0.000029739964,0.000004823428,0.000031149775,0.00001571868,0.000078278485,0.0004174779],"genre_scores_gemma":[0.15800321,0.00011503208,0.8379569,0.00008107392,0.000029001956,0.00049896614,0.00019236251,0.00011072405,0.0030126136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990854,0.00036609935,0.00003570157,0.00019151681,0.00022398272,0.00009724639],"domain_scores_gemma":[0.9981628,0.0013584717,0.00015788038,0.00009646737,0.0001838411,0.000040546067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018044586,0.0011420106,0.001506594,0.0009358369,0.00044736298,0.0005819688,0.001392931,0.00088268204,0.0054652328],"category_scores_gemma":[0.004475088,0.00074241235,0.0009104667,0.00091471785,0.0007750767,0.0010685317,0.0011375194,0.0012564732,0.0006108263],"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":[0.00008786839,0.00006997159,0.000450897,0.000094624615,0.00004811903,0.00005376934,0.000058026024,0.8686823,0.0021579452,0.018858412,0.0009707796,0.108467214],"study_design_scores_gemma":[0.000010300553,0.00003524713,0.000096465614,0.000004654039,0.0000069441467,0.000013966278,0.000007551045,0.99316156,0.0005215508,0.0055458453,0.0005894821,0.0000064800865],"about_ca_topic_score_codex":0.0053216973,"about_ca_topic_score_gemma":0.00500143,"teacher_disagreement_score":0.0054652328,"about_ca_system_score_codex":0.0009358137,"about_ca_system_score_gemma":0.0021143458,"threshold_uncertainty_score":0.01828307},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014009226,0.00017373583,0.9813933,0.00022866564,0.000019731235,0.000104124,0.00011746387,0.00020344365,0.0037502933],"genre_scores_gemma":[0.62593657,0.00040231642,0.36907485,0.00016447,0.00004911504,0.00057704456,0.00043898862,0.00015065796,0.0032059608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99582005,0.0015863662,0.00024926083,0.00042887902,0.0016409098,0.00027441923],"domain_scores_gemma":[0.99662614,0.001451944,0.0007076676,0.00021251764,0.00086841127,0.00013338718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038741007,0.001424374,0.0009800821,0.00293791,0.0008082276,0.0021625154,0.0018661754,0.001259972,0.0023518272],"category_scores_gemma":[0.007452026,0.0005328021,0.0011113093,0.0031796258,0.0011402027,0.004718257,0.0015913093,0.0014511455,0.000498577],"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":[0.00012231639,0.00012720856,0.0020125112,0.000116133975,0.000050834027,0.000107161126,0.00016854086,0.8373031,0.002423037,0.11633123,0.0015068233,0.039731108],"study_design_scores_gemma":[0.000007738609,0.00015718941,0.00042544986,0.0000140277725,0.000014681603,0.000050918024,0.000038608232,0.9660353,0.0011926,0.030710623,0.0013304277,0.00002246552],"about_ca_topic_score_codex":0.00281838,"about_ca_topic_score_gemma":0.0019582477,"teacher_disagreement_score":0.0038741007,"about_ca_system_score_codex":0.0028287584,"about_ca_system_score_gemma":0.0017316748,"threshold_uncertainty_score":0.020524204},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43963948,0.00033316005,0.55339175,0.00089688227,0.000131783,0.00021543256,0.00015490236,0.00063140964,0.0046051475],"genre_scores_gemma":[0.9852636,0.00008464633,0.013599936,0.000034086865,0.00003034482,0.000019886047,0.0000339934,0.000009925246,0.00092361664],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978994,0.00051076966,0.00013937497,0.000256166,0.0007859062,0.00040820715],"domain_scores_gemma":[0.98941386,0.0056501986,0.0018896784,0.0011184283,0.0011776395,0.0007502363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003694125,0.000554726,0.00086933427,0.0007603905,0.0009571193,0.002603298,0.0013928978,0.001030427,0.0023769438],"category_scores_gemma":[0.011810243,0.0006731745,0.00034804756,0.00093793904,0.0012001044,0.0027139785,0.0010731964,0.0014288267,0.00026754633],"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":[0.0005397852,0.00023171063,0.003310918,0.00004919478,0.00004668929,0.00023206665,0.00019411505,0.925949,0.003981575,0.03685034,0.0007414485,0.02787315],"study_design_scores_gemma":[0.00005007047,0.00014007285,0.00058094284,0.000008255441,0.000020832545,0.00003252612,0.00004474646,0.9775373,0.0025226045,0.018299747,0.00074064423,0.000022256194],"about_ca_topic_score_codex":0.0053463536,"about_ca_topic_score_gemma":0.004441077,"teacher_disagreement_score":0.0053463536,"about_ca_system_score_codex":0.0016621501,"about_ca_system_score_gemma":0.0021068177,"threshold_uncertainty_score":0.019536674},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2793521,0.00063687685,0.70214856,0.0021766175,0.0001920271,0.00024033786,0.0002344755,0.00025192404,0.014767082],"genre_scores_gemma":[0.9755028,0.00015338206,0.019770179,0.00010635778,0.00008227837,0.00008842734,0.00008114797,0.00003943793,0.0041759466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969157,0.0009741679,0.000101443955,0.0004909003,0.00058313087,0.00093462435],"domain_scores_gemma":[0.9950406,0.003121715,0.00067457213,0.0003041483,0.00037107005,0.00048788404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041334755,0.000879217,0.001799256,0.0006788116,0.0010138786,0.0026935413,0.0024345303,0.0020701617,0.004699641],"category_scores_gemma":[0.011299117,0.001033623,0.0011795644,0.00086561847,0.0017966707,0.003045513,0.0014865432,0.0021291492,0.00034529815],"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":[0.00024074761,0.00013478124,0.0017722057,0.000077804565,0.00006186785,0.00034425946,0.00016539209,0.84499663,0.0015349373,0.13591635,0.0013122167,0.013442784],"study_design_scores_gemma":[0.00003073132,0.000051308507,0.00040068952,0.000005273543,0.000016182505,0.00007085099,0.0000422233,0.96289295,0.00026220008,0.03563056,0.00057825824,0.000018866147],"about_ca_topic_score_codex":0.0059222793,"about_ca_topic_score_gemma":0.0037277122,"teacher_disagreement_score":0.0059222793,"about_ca_system_score_codex":0.004754419,"about_ca_system_score_gemma":0.0015681448,"threshold_uncertainty_score":0.03449595},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3300687,0.0038658907,0.63805765,0.0020939035,0.00018769047,0.000118109114,0.00024349602,0.00018189175,0.025182642],"genre_scores_gemma":[0.9859957,0.00060773495,0.012505359,0.000036557656,0.000047727484,0.000018269862,0.000025305993,0.000016225116,0.00074702466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977314,0.0010428701,0.00009095837,0.00018967407,0.00069166074,0.000253525],"domain_scores_gemma":[0.9866774,0.011710061,0.0005987134,0.00033943678,0.0005034053,0.00017102904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029392582,0.0008185024,0.00090583734,0.00089658005,0.0007866409,0.0040195505,0.0009772498,0.0013534487,0.0012265461],"category_scores_gemma":[0.013183597,0.0005442317,0.000496131,0.0012986739,0.0020292336,0.005910696,0.0009651493,0.0012326292,0.00011313832],"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":[0.00036081672,0.0000857224,0.002225197,0.00021124232,0.000116452,0.00035600126,0.00013735107,0.860375,0.002808922,0.102279015,0.0004709026,0.030573439],"study_design_scores_gemma":[0.000019976675,0.0001885915,0.0009108694,0.000047589543,0.00006823469,0.0000790346,0.00006899499,0.9481983,0.002610099,0.046913046,0.00086257147,0.000032727934],"about_ca_topic_score_codex":0.0014874281,"about_ca_topic_score_gemma":0.000824644,"teacher_disagreement_score":0.0040195505,"about_ca_system_score_codex":0.002087837,"about_ca_system_score_gemma":0.0008776735,"threshold_uncertainty_score":0.015544474},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.117873564,0.00028176146,0.87726355,0.00031181547,0.000058508882,0.000086039894,0.00006840825,0.00021534656,0.0038410167],"genre_scores_gemma":[0.8799436,0.00022886877,0.11635743,0.000047323658,0.00006238513,0.00012367817,0.0001222909,0.000042280222,0.0030721144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993229,0.00037414697,0.000019445943,0.00008134499,0.000111102534,0.00009111484],"domain_scores_gemma":[0.9992449,0.0004875141,0.00013071494,0.000038474525,0.000049762493,0.000048589813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088325876,0.0008737265,0.0012582324,0.00042351944,0.0004733828,0.000780755,0.0007583585,0.00081003376,0.001182112],"category_scores_gemma":[0.0014722962,0.00076681067,0.0006402599,0.00074982113,0.00089889043,0.00082229316,0.00080098637,0.0009855438,0.00017760706],"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":[0.000030689727,0.000014213534,0.000058127505,0.000010827367,0.0000062288336,0.00003397085,0.000007826391,0.99595416,0.0005009552,0.0017459453,0.00008064689,0.0015565389],"study_design_scores_gemma":[0.000006925121,0.000011134572,0.000029112976,7.936795e-7,0.0000018963018,0.0000033627232,0.0000018805096,0.9990496,0.00013472185,0.00068263523,0.00007644747,0.00000144006],"about_ca_topic_score_codex":0.0063203275,"about_ca_topic_score_gemma":0.0039824173,"teacher_disagreement_score":0.0063203275,"about_ca_system_score_codex":0.0010835222,"about_ca_system_score_gemma":0.0013860196,"threshold_uncertainty_score":0.012567103},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016978618,0.0011638328,0.97880024,0.00048309122,0.00013325474,0.00008438605,0.0001563824,0.00040399982,0.001796256],"genre_scores_gemma":[0.5777033,0.0022850293,0.41221517,0.00041491064,0.00057223084,0.0004838595,0.00074169895,0.0001716505,0.005412144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969112,0.0016116158,0.00016790601,0.00041253207,0.000753227,0.00014350207],"domain_scores_gemma":[0.96932405,0.026681695,0.0012283442,0.00082711846,0.0017351934,0.00020360427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008781371,0.0013180138,0.002255205,0.00205437,0.00074342225,0.0015012702,0.0022973411,0.0016771746,0.0033202732],"category_scores_gemma":[0.04285547,0.0008239512,0.0009779274,0.0017273839,0.00080820447,0.0026141638,0.000715378,0.0021662535,0.0009419704],"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":[0.00014770542,0.000094460716,0.0023295903,0.00014214705,0.00010783207,0.000066666966,0.00010000741,0.8666717,0.0003983037,0.021906467,0.0018074453,0.10622772],"study_design_scores_gemma":[0.000013365735,0.000014985538,0.00020529513,0.000018704593,0.000009434817,0.000019581992,0.000011273554,0.982379,0.00014755371,0.016820833,0.00034995523,0.0000100315165],"about_ca_topic_score_codex":0.011609475,"about_ca_topic_score_gemma":0.008803071,"teacher_disagreement_score":0.011609475,"about_ca_system_score_codex":0.0010556686,"about_ca_system_score_gemma":0.001582553,"threshold_uncertainty_score":0.0464409},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5345121,0.00035343427,0.45757464,0.00030742545,0.000044819382,0.00008173374,0.0000731677,0.00039322843,0.0066594407],"genre_scores_gemma":[0.9838817,0.00010428056,0.014398694,0.000027230775,0.000013735392,0.000023518403,0.000018102039,0.000024883253,0.0015078194],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988036,0.00043080034,0.000034834924,0.00016941533,0.00017835779,0.0003828595],"domain_scores_gemma":[0.9976719,0.0014060888,0.0003479408,0.000120592056,0.00019920361,0.00025419504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018566321,0.0007579991,0.0008168159,0.00065587566,0.00072286744,0.0016945201,0.001231289,0.00089198176,0.0016019279],"category_scores_gemma":[0.004406654,0.0005833616,0.00039576358,0.0013482126,0.0019460161,0.002020617,0.00091998396,0.00073855557,0.0003294544],"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":[0.0003245198,0.00011736354,0.00075514696,0.000038526836,0.000022635524,0.00014500883,0.00007940502,0.9641035,0.0065910993,0.017889021,0.00042107832,0.0095126685],"study_design_scores_gemma":[0.000026982183,0.00011568423,0.00021421045,0.0000055319433,0.000012971763,0.000029283996,0.00005636144,0.98175645,0.0026662494,0.014931798,0.00017187672,0.000012643738],"about_ca_topic_score_codex":0.0036986717,"about_ca_topic_score_gemma":0.0036894495,"teacher_disagreement_score":0.0036986717,"about_ca_system_score_codex":0.0028810864,"about_ca_system_score_gemma":0.0016747636,"threshold_uncertainty_score":0.020903766},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77996457,0.0006963787,0.1908607,0.0017809714,0.00005989961,0.00039496657,0.00039985124,0.00020909109,0.025633555],"genre_scores_gemma":[0.9876351,0.00020875297,0.008041794,0.000054372762,0.000015475824,0.0000660716,0.000045072255,0.000017833963,0.003915515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9981706,0.00067114946,0.00009943662,0.0003849347,0.00017225945,0.0005015243],"domain_scores_gemma":[0.9913384,0.0046376693,0.002314735,0.00045035736,0.00029349,0.00096544565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040490944,0.0007589463,0.0016291824,0.00078699226,0.0010093787,0.0032009722,0.0023375445,0.0030921618,0.008015618],"category_scores_gemma":[0.012293489,0.0011767116,0.00087918265,0.0006718391,0.002492602,0.0044199475,0.002009923,0.002076974,0.00054169446],"study_design_candidate":"observational","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":[0.00085586554,0.00047358358,0.005876713,0.00015856815,0.000093214294,0.00041524853,0.00028604013,0.866493,0.0048977276,0.097197115,0.0012672037,0.021985725],"study_design_scores_gemma":[0.00032999393,0.00057696,0.0044793696,0.000048068374,0.00009829664,0.00012218699,0.0005908478,0.90713567,0.002319948,0.082192905,0.0020024832,0.00010330856],"about_ca_topic_score_codex":0.013369502,"about_ca_topic_score_gemma":0.010250823,"teacher_disagreement_score":0.013369502,"about_ca_system_score_codex":0.0048303017,"about_ca_system_score_gemma":0.003040842,"threshold_uncertainty_score":0.03504646},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46570653,0.004252698,0.38815823,0.0059582656,0.00019462749,0.00022320241,0.00019817852,0.000364634,0.13494365],"genre_scores_gemma":[0.99079365,0.00045940134,0.0045898207,0.000054760556,0.00005292447,0.000032309625,0.000013533599,0.000007955613,0.0039955755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974343,0.0011575784,0.00016334013,0.00034776074,0.0005780512,0.00031884],"domain_scores_gemma":[0.9895381,0.005931899,0.0023579558,0.0008432701,0.0007292822,0.00059961266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00253332,0.0005128444,0.00061211956,0.001018877,0.0014253611,0.0037074802,0.0006162631,0.0017370692,0.009581193],"category_scores_gemma":[0.009134114,0.00049595605,0.0005215341,0.0009848792,0.0029068456,0.0037617648,0.003207163,0.001628728,0.0006540371],"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":[0.0001821061,0.00010268096,0.0036749942,0.00015992788,0.00008990565,0.00083577883,0.00085444376,0.11745875,0.002971209,0.84650964,0.0012856658,0.025874896],"study_design_scores_gemma":[0.000049377675,0.00008617699,0.0006236292,0.00010629764,0.000048560712,0.00019199908,0.00025412565,0.13193384,0.0013736121,0.8577958,0.007495135,0.000041438136],"about_ca_topic_score_codex":0.0011061624,"about_ca_topic_score_gemma":0.00062283006,"teacher_disagreement_score":0.009581193,"about_ca_system_score_codex":0.0017157969,"about_ca_system_score_gemma":0.0012317431,"threshold_uncertainty_score":0.03205222},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15189268,0.0026416578,0.8116319,0.002618829,0.00087612943,0.00019401379,0.00029902247,0.00042547533,0.029420238],"genre_scores_gemma":[0.96441555,0.0012844923,0.017588276,0.00034318015,0.00039167257,0.000086922504,0.00009339415,0.000059532973,0.015736999],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965933,0.0012734815,0.00011179519,0.0006081797,0.00069859537,0.0007146157],"domain_scores_gemma":[0.9873394,0.00802739,0.0013744781,0.0013797183,0.0011415137,0.00073762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004615328,0.0013062803,0.0018397463,0.0008106893,0.0014162848,0.005434446,0.003672298,0.0028387764,0.010459379],"category_scores_gemma":[0.016402371,0.0010621414,0.0017639039,0.0015655153,0.0031725997,0.0069073373,0.0025012887,0.0047359397,0.0009432395],"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":[0.00042799898,0.00036797108,0.0023844563,0.00014391443,0.00014518986,0.00041640157,0.00036420475,0.3287557,0.0022560684,0.644291,0.0032460443,0.017201042],"study_design_scores_gemma":[0.00007978087,0.00011254521,0.00045806653,0.000012159741,0.00008074832,0.00011371538,0.00004264693,0.8945241,0.00040286354,0.10275297,0.0013683599,0.000052045965],"about_ca_topic_score_codex":0.005064372,"about_ca_topic_score_gemma":0.003359564,"teacher_disagreement_score":0.010459379,"about_ca_system_score_codex":0.0032523475,"about_ca_system_score_gemma":0.0023215548,"threshold_uncertainty_score":0.03499013},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23743755,0.001981644,0.69395715,0.00066645036,0.00032027345,0.00049759005,0.0026360722,0.004234423,0.058268927],"genre_scores_gemma":[0.9025554,0.00024859322,0.09343594,0.0000621502,0.000047542,0.0003321853,0.0010590365,0.000094808056,0.0021643732],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9922654,0.002828615,0.0006078332,0.00050649623,0.0035300767,0.00026153828],"domain_scores_gemma":[0.98299927,0.0068117087,0.0036595208,0.0016673963,0.00431199,0.0005501228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036607038,0.00097654574,0.00042995356,0.0068079676,0.00044299202,0.002532277,0.0005535173,0.00083977595,0.0033383488],"category_scores_gemma":[0.023064587,0.00023376309,0.0003358004,0.004193987,0.00072628615,0.002199756,0.0013312566,0.0008012269,0.0012890465],"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":[0.0009947857,0.0005968931,0.10496402,0.0008038656,0.0003025879,0.00017720598,0.001166127,0.15849395,0.043368947,0.11270308,0.016015496,0.560413],"study_design_scores_gemma":[0.00010259036,0.0035491022,0.11629382,0.0004406909,0.00012560059,0.00078472984,0.000947103,0.72933996,0.052903663,0.05372631,0.041447,0.00033947336],"about_ca_topic_score_codex":0.0014647349,"about_ca_topic_score_gemma":0.0007213355,"teacher_disagreement_score":0.0068079676,"about_ca_system_score_codex":0.0012015261,"about_ca_system_score_gemma":0.0006084023,"threshold_uncertainty_score":0.019359887},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02569825,0.00020495358,0.9733333,0.00007444513,0.0000084969615,0.00003417382,0.00013871357,0.00019145559,0.00031616364],"genre_scores_gemma":[0.6778108,0.00086914503,0.31762934,0.000097285316,0.00008918111,0.00040674728,0.0015852855,0.00014472086,0.001367492],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99642533,0.002045143,0.00017712079,0.00050325005,0.00069371716,0.00015543908],"domain_scores_gemma":[0.9505381,0.042173844,0.0025998433,0.002837364,0.0016593041,0.000191446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014800959,0.00063317793,0.0011691588,0.0028009722,0.0003643809,0.0012561758,0.0014727988,0.0011377035,0.0013155462],"category_scores_gemma":[0.06468493,0.0005767648,0.00082343316,0.002329248,0.0011900221,0.0025048116,0.0014164838,0.0015870694,0.00043661485],"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":[0.00030488995,0.000119862096,0.022256142,0.00034720878,0.00022194271,0.00042007418,0.0006797176,0.6796862,0.0025279291,0.09503374,0.0027107652,0.19569156],"study_design_scores_gemma":[0.000030282086,0.000072308416,0.0054456764,0.000075950986,0.000023503466,0.00024776327,0.00013768945,0.87581706,0.0012401206,0.11492769,0.0019330716,0.000048960865],"about_ca_topic_score_codex":0.0028379234,"about_ca_topic_score_gemma":0.0016564603,"teacher_disagreement_score":0.014800959,"about_ca_system_score_codex":0.00094047823,"about_ca_system_score_gemma":0.0010672738,"threshold_uncertainty_score":0.07827592},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011474718,0.0025811149,0.97950107,0.00086954224,0.00009338622,0.000018761415,0.0000791643,0.000118600336,0.0052636666],"genre_scores_gemma":[0.5858181,0.013360892,0.37961265,0.0007514226,0.0014152926,0.00027173085,0.0006195797,0.00040556453,0.01774485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983235,0.0007083194,0.00007744719,0.00020162915,0.0005620152,0.00012708807],"domain_scores_gemma":[0.98582155,0.009543398,0.0011934788,0.0010324252,0.00199219,0.00041694278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064808475,0.0012971343,0.0011551705,0.0019657128,0.00054812804,0.003155138,0.0014197107,0.0016975469,0.0022338054],"category_scores_gemma":[0.032375194,0.0004922309,0.0007462811,0.0024355506,0.0022482963,0.004284697,0.0019949262,0.0030724371,0.001023077],"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":[0.00018020824,0.00012551539,0.0049548843,0.00024151916,0.00009648355,0.00029196605,0.0002164776,0.17129453,0.0026706392,0.55342376,0.008879366,0.25762457],"study_design_scores_gemma":[0.000022457923,0.00010583286,0.0012663873,0.00007969439,0.000042178624,0.0004951616,0.00005908197,0.56847584,0.001074276,0.42246786,0.0058709215,0.000040358045],"about_ca_topic_score_codex":0.0014877213,"about_ca_topic_score_gemma":0.00068412145,"teacher_disagreement_score":0.0064808475,"about_ca_system_score_codex":0.0009426165,"about_ca_system_score_gemma":0.0012164332,"threshold_uncertainty_score":0.0342744},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.667736,0.00035748296,0.32748213,0.00024334957,0.000045362773,0.00016711515,0.00014029573,0.00023824131,0.0035899081],"genre_scores_gemma":[0.9829532,0.000047109424,0.016538762,0.000008723689,0.000004843739,0.000030208597,0.000043793043,0.000010159514,0.00036327666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942064,0.00019415481,0.000030201318,0.00007969503,0.00011963926,0.0001557534],"domain_scores_gemma":[0.9987134,0.0006776818,0.00024996002,0.000059969352,0.00014551994,0.00015347205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012493005,0.0005230672,0.0007042137,0.00058912794,0.00055145693,0.0007603177,0.00066651014,0.00070201315,0.0016552757],"category_scores_gemma":[0.0031236156,0.0005077609,0.00037129605,0.0005843404,0.0006884703,0.0005302502,0.00030320717,0.0004889908,0.00013753891],"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":[0.00009703024,0.000032451193,0.00034576532,0.000023973189,0.0000119896995,0.000072781186,0.000030587,0.9895307,0.00138089,0.0020585563,0.00013889094,0.006276405],"study_design_scores_gemma":[0.000031109084,0.000102512495,0.00041629566,0.0000044683134,0.000008644392,0.000014809721,0.000021032925,0.9963761,0.0007322348,0.0020670586,0.00021788642,0.000007725761],"about_ca_topic_score_codex":0.008348377,"about_ca_topic_score_gemma":0.0046404516,"teacher_disagreement_score":0.008348377,"about_ca_system_score_codex":0.0013428585,"about_ca_system_score_gemma":0.0015512035,"threshold_uncertainty_score":0.016599536},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70255995,0.00048997847,0.2830378,0.0009409514,0.000055637083,0.00021086958,0.0006648497,0.0001869049,0.011853058],"genre_scores_gemma":[0.966113,0.00021817892,0.02754128,0.00003670176,0.000027444867,0.00010908857,0.00023305923,0.000039817656,0.005681502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802434,0.0009184296,0.000048899994,0.00034647933,0.00024405666,0.00041788758],"domain_scores_gemma":[0.99736243,0.0016332321,0.00052266766,0.00014883403,0.0001735598,0.0001592167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018668204,0.0011173914,0.0011124287,0.0012259667,0.0011605837,0.0021630782,0.0020695943,0.002423157,0.0068199234],"category_scores_gemma":[0.005636315,0.0010160025,0.0013209367,0.0022379553,0.002003118,0.0035724891,0.0018049637,0.0011861066,0.00060770917],"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":[0.00009851458,0.000029598403,0.0009988871,0.000027593745,0.000024090976,0.000088133405,0.000040216102,0.98778766,0.00023749747,0.007818538,0.00026619365,0.0025831617],"study_design_scores_gemma":[0.000048220852,0.00008567676,0.0007965001,0.000012359163,0.000037112703,0.000066985,0.00025328115,0.9829244,0.00038623746,0.014566772,0.0008057407,0.000016673996],"about_ca_topic_score_codex":0.013501783,"about_ca_topic_score_gemma":0.012470083,"teacher_disagreement_score":0.013501783,"about_ca_system_score_codex":0.004007264,"about_ca_system_score_gemma":0.00089825556,"threshold_uncertainty_score":0.029074907},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01007908,0.07507361,0.8342014,0.000821777,0.00083085237,0.00014356716,0.00011100339,0.0005670753,0.07817174],"genre_scores_gemma":[0.2051297,0.18448015,0.5188354,0.0007055793,0.0018745132,0.00038368106,0.00048171563,0.00027043725,0.08783881],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998845,0.00002996102,0.0000083749865,0.00003419519,0.000034211764,0.0000088133465],"domain_scores_gemma":[0.99989057,0.00006464637,0.000011551038,0.0000067799706,0.000021744874,0.0000047927774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020996196,0.0009412523,0.0005169513,0.00060909597,0.00025959002,0.0008811745,0.00059595663,0.0006184705,0.006298745],"category_scores_gemma":[0.00032628054,0.00030482624,0.0005795645,0.0009181162,0.0003393335,0.0013884361,0.0002902829,0.000719366,0.0023149971],"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":[0.0000706291,0.00028188503,0.000497788,0.002440255,0.0000529311,0.00045166063,0.00032927896,0.11267966,0.01362454,0.2552339,0.028829386,0.58550805],"study_design_scores_gemma":[0.00002814717,0.00043872485,0.0010708545,0.0008261592,0.00006359119,0.0013022564,0.00018164967,0.40190437,0.008636507,0.16662249,0.41883373,0.000091510556],"about_ca_topic_score_codex":0.00082556746,"about_ca_topic_score_gemma":0.000759313,"teacher_disagreement_score":0.006298745,"about_ca_system_score_codex":0.00038318787,"about_ca_system_score_gemma":0.00031046453,"threshold_uncertainty_score":0.021071434},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03170984,0.00049118063,0.94661367,0.001990764,0.00011639193,0.00021462617,0.00088368525,0.00020760465,0.017772282],"genre_scores_gemma":[0.61189896,0.0014447969,0.34912747,0.0003696504,0.0002765234,0.0007105276,0.001527106,0.00018371738,0.034461264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985843,0.00055212225,0.00004253066,0.00034642764,0.00025707652,0.0002175632],"domain_scores_gemma":[0.9984792,0.0010758828,0.00016323125,0.00006980219,0.00010377985,0.00010820025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013243001,0.001257955,0.0015739414,0.0011117534,0.0009950157,0.0022194004,0.0019085839,0.0034309716,0.016334012],"category_scores_gemma":[0.003959736,0.0010241449,0.0010868567,0.0019145127,0.0011827946,0.0032704866,0.0020844163,0.0023783296,0.0012149909],"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":[0.0001440942,0.00012750695,0.0009554016,0.00029042587,0.00006730502,0.00049929664,0.00012932743,0.792775,0.001170673,0.1578108,0.0060129394,0.04001724],"study_design_scores_gemma":[0.000093250215,0.00010705433,0.00061259035,0.000039863437,0.00004450677,0.00031444198,0.00018254598,0.8762823,0.0010756033,0.10790673,0.0132954065,0.000045712637],"about_ca_topic_score_codex":0.0067611155,"about_ca_topic_score_gemma":0.0048237504,"teacher_disagreement_score":0.016334012,"about_ca_system_score_codex":0.0019957884,"about_ca_system_score_gemma":0.0029278593,"threshold_uncertainty_score":0.054642737},"labels":[],"label_agreement":null}]}