{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":12,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":12,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"412d8c6a46fa","filters":{"venue":"Journal of Industrial Engineering and Management"}},"results":[{"id":"W3160944769","doi":"10.3926/jiem.3331","title":"Demand Driven Material Requirements Planning (DDMRP): A systematic review and classification","year":2021,"lang":"en","type":"review","venue":"Journal of Industrial Engineering and Management","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Scope (computer science); Originality; Computer science; Robustness (evolution); Context (archaeology); Data science; Field (mathematics); Management science; Risk analysis (engineering); Scientific literature; Operations research; Process management; Engineering; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.07445199418213214,"gpt":0.2905920507945028,"spread":0.2161400566123707,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001130094,0.0004096953,0.001993682,0.000749971,0.00008248205,0.0005293269,0.0002775752,0.0001917757,0.00003424241],"category_scores_gemma":[0.0001826696,0.0003310627,0.0002103322,0.0004417329,0.00001861653,0.0005627158,0.0003170178,0.000296347,0.000003644307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007154071,"about_ca_system_score_gemma":0.00001950479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002360408,"about_ca_topic_score_gemma":1.492875e-7,"domain_scores_codex":[0.9976851,0.00004425524,0.001433515,0.0002747903,0.0003413924,0.000220937],"domain_scores_gemma":[0.997916,0.0000397648,0.001649308,0.0002348971,0.0001258512,0.0000341291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005065282,0.00003289245,0.00000328848,0.9530773,0.0009107396,0.00008732121,0.000007399782,0.00006882464,3.091247e-7,0.003786397,0.01088362,0.03113683],"study_design_scores_gemma":[0.0003203335,0.00001742124,9.076013e-7,0.4545307,0.008962725,0.00002797495,0.00002926475,0.0003654554,1.505965e-7,0.00001043992,0.5354157,0.0003188959],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002444938,0.9952766,0.00151262,0.00009300636,0.0006017139,0.001690584,0.000002950368,0.00006739013,0.0007527312],"genre_scores_gemma":[0.00001338496,0.9978988,0.0007180229,0.0001556303,0.0008182214,0.0000915406,0.00005051139,0.00005056896,0.0002033165],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5245321,"threshold_uncertainty_score":0.9999142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043472740","doi":"10.3926/jiem.451","title":"Workforce scheduling: A new model incorporating human factors","year":2012,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Workforce; Overtime; Human resources; Originality; Workforce management; Scheduling (production processes); Human resource management; Engineering; Operations management; Operations research; Computer science; Labour economics; Economics; Knowledge management; Psychology; Management; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.06319480430748918,"gpt":0.254115396641964,"spread":0.1909205923344748,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000244128,0.0001237822,0.0001745887,0.0001473258,0.00003466905,0.00005221419,0.00007300497,0.00006990624,0.000005504515],"category_scores_gemma":[0.00004735178,0.0001087611,0.00004939388,0.000124328,0.000006740964,0.0002361483,0.00003021252,0.0002209475,8.20246e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004316666,"about_ca_system_score_gemma":0.000007380871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.806144e-7,"about_ca_topic_score_gemma":8.640875e-8,"domain_scores_codex":[0.999278,0.000004293057,0.0003374845,0.00004422431,0.0001408723,0.0001950993],"domain_scores_gemma":[0.9996009,0.00002416713,0.00007668275,0.00006208839,0.0000157762,0.0002203162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002152023,0.00001640243,0.000109564,0.00006192312,0.00006700812,0.000001660477,0.0001830376,0.9801194,0.0001943982,0.01184177,0.0004010821,0.007001621],"study_design_scores_gemma":[0.001603565,0.00007275584,0.0000467397,0.0005801442,0.0001577559,0.0000172873,0.0004198263,0.9897878,0.0007499462,0.0004566385,0.005703132,0.0004044491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1856963,0.000488969,0.8103715,0.00005696017,0.0007892718,0.0001947102,5.04442e-7,0.000177533,0.002224233],"genre_scores_gemma":[0.9393603,0.00005664457,0.06002663,0.000008160604,0.0003910334,0.000001406387,9.334629e-7,0.00002595344,0.0001289034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.753664,"threshold_uncertainty_score":0.4435151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099184181","doi":"10.3926/jiem.543","title":"Determining supply chain safety stock level and location","year":2014,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Safety stock; Supply chain; Stock (firearms); Minification; Supply chain management; Lean manufacturing; Operations research; Business; Computer science; Operations management; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.03793534376489328,"gpt":0.2201771914332676,"spread":0.1822418476683743,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001382108,0.0001631755,0.0002508158,0.0004019916,0.0001017328,0.0002220594,0.000137163,0.00006716955,0.0000140496],"category_scores_gemma":[0.0001765925,0.0001499236,0.00003934265,0.0002637402,0.00002264276,0.0005325385,0.0001675101,0.0001961087,0.000004106516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003187588,"about_ca_system_score_gemma":0.000006795833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003189758,"about_ca_topic_score_gemma":0.000005316919,"domain_scores_codex":[0.9989045,0.00001464101,0.0004672592,0.0001512263,0.0002563428,0.000206007],"domain_scores_gemma":[0.9994597,0.00005239192,0.0002512407,0.0001160827,0.00008852492,0.00003199228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002583195,0.0001303764,0.00626831,0.001321035,0.0004250599,0.00006123498,0.0002105005,0.04306447,0.0001385407,0.1475382,0.01045886,0.7901251],"study_design_scores_gemma":[0.006117464,0.0001848567,0.03055109,0.00110465,0.0004089314,0.00003207997,0.0006563788,0.1310206,0.00003673087,0.0008037663,0.8284079,0.0006755329],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6431923,0.0005795825,0.3298797,0.01008576,0.004441132,0.001435325,0.000005912805,0.0002249199,0.01015536],"genre_scores_gemma":[0.9965689,0.0001076428,0.001111324,0.0004324274,0.001531512,0.000005577259,0.000003927941,0.00001962268,0.0002190847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8179491,"threshold_uncertainty_score":0.6113709,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001558460","doi":"10.3926/jiem.326","title":"Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: A systematic literature review","year":2011,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Université TÉLUQ; Polytechnique Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; Université Laval","keywords":"Management science; Systematic review; Supply chain; Process (computing); Computer science; Identification (biology); Scale (ratio); Process management; Data science; Risk analysis (engineering); Engineering; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.1123329539742864,"gpt":0.2858005340624672,"spread":0.1734675800881808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001016976,0.0001668927,0.0004586422,0.0002477097,0.00002887896,0.00003808858,0.0001050337,0.0001807148,0.000003320169],"category_scores_gemma":[0.0001203432,0.0001327215,0.00009855763,0.000311652,0.000007146122,0.00010466,0.000004760662,0.0004859092,1.98928e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004989867,"about_ca_system_score_gemma":0.000009984966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.890224e-7,"about_ca_topic_score_gemma":8.015736e-8,"domain_scores_codex":[0.9988267,0.00003784772,0.0007442718,0.00009721775,0.000134298,0.0001596597],"domain_scores_gemma":[0.999401,0.0001325164,0.0001524841,0.0001091558,0.0001292754,0.00007560758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003782226,0.00001977364,0.000005776762,0.0323352,0.0002189645,0.00002966256,0.0002070077,0.9635744,0.00004206295,0.002377136,0.0003248457,0.0008273418],"study_design_scores_gemma":[0.001902872,0.0002189197,0.00002643484,0.2110324,0.0005868688,0.00003613201,0.0005286805,0.7809319,0.0001276378,0.0000405139,0.004209635,0.0003580248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003234343,0.02106271,0.9736608,0.00004924025,0.0008623952,0.0009827644,0.0000137358,0.00009570328,0.00003833084],"genre_scores_gemma":[0.6787029,0.01723836,0.3025399,0.0002955775,0.0003872817,0.000586145,0.00007371427,0.0001019497,0.00007413136],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6754686,"threshold_uncertainty_score":0.5412228,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2767074990","doi":"10.3926/jiem.2253","title":"A multi-criteria vertical coordination framework for a reliable aid distribution","year":2017,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Stakeholder; Supply chain; Humanitarian Logistics; Process management; Process (computing); Humanitarian aid; Business; Originality; Order (exchange); Management science; Risk analysis (engineering); Computer science; Knowledge management; Marketing; Qualitative research; Economics; Management; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.05082191573570207,"gpt":0.2766054510763174,"spread":0.2257835353406153,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006904466,0.000130541,0.0001916439,0.0001447824,0.0002492421,0.0004231817,0.0002332892,0.00008329488,0.00002405067],"category_scores_gemma":[0.0006708579,0.0001220257,0.00008425763,0.00008380033,0.00002339087,0.0007153951,0.0001356335,0.0001471068,0.00000734336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005339532,"about_ca_system_score_gemma":0.000007012633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000600032,"about_ca_topic_score_gemma":0.000004431586,"domain_scores_codex":[0.9990851,0.000003242408,0.0003853203,0.0001409082,0.0001911721,0.0001942573],"domain_scores_gemma":[0.9994511,0.00001569494,0.0001483694,0.0002059027,0.0001518965,0.00002700794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001075084,0.0007832575,0.003170803,0.002109826,0.0008656776,0.00005161936,0.00009865729,0.02656561,0.0005791679,0.7714899,0.1116724,0.08153809],"study_design_scores_gemma":[0.005457058,0.0000967163,0.008461308,0.0006558265,0.0003706969,0.000003273547,0.0001887363,0.2774326,0.00008764123,0.002285209,0.7045602,0.0004007385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1627982,0.000174056,0.8114815,0.01417584,0.008949554,0.001445476,0.00001527106,0.0001255591,0.0008346133],"genre_scores_gemma":[0.9904353,0.00007733748,0.007495592,0.0001618365,0.001534468,0.00003155055,0.0000188538,0.00001754052,0.0002275398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8276371,"threshold_uncertainty_score":0.4976065,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2791560910","doi":"10.3926/jiem.2528","title":"Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach","year":2018,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TOPSIS; Kanban; Analytic hierarchy process; Multiple-criteria decision analysis; Fuzzy logic; Engineering; Ideal solution; Production (economics); Operations research; Manufacturing engineering; Industrial engineering; Control (management); Computer science; Reliability engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.04428575752939568,"gpt":0.2512371560191563,"spread":0.2069513984897606,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002724177,0.0001626033,0.0002470049,0.0006415391,0.0000673524,0.0002119085,0.0001633967,0.00008243231,0.00004439254],"category_scores_gemma":[0.0001268332,0.0001369555,0.00005471173,0.0004733347,0.000045487,0.001150146,0.00004773135,0.0001450967,0.00000112247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006537817,"about_ca_system_score_gemma":0.00003211191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007900599,"about_ca_topic_score_gemma":0.000008670867,"domain_scores_codex":[0.9985715,0.00003377372,0.0004896561,0.000168249,0.0005835282,0.0001532498],"domain_scores_gemma":[0.9984643,0.0000098926,0.000470702,0.0001493173,0.0008869727,0.00001883763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002571121,0.0002492374,0.0001746018,0.0002248476,0.0005764801,0.000002426784,0.00009414891,0.8468926,0.0003398533,0.04687978,0.005365312,0.0989436],"study_design_scores_gemma":[0.00731707,0.0004736128,0.001202872,0.0006253899,0.00300272,0.000009706896,0.006502457,0.9380878,0.0004284498,0.005573445,0.03604631,0.0007301846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5339804,0.0003804507,0.422726,0.00180376,0.004484877,0.003444243,0.000005101747,0.0004517137,0.03272344],"genre_scores_gemma":[0.9958397,0.00005219041,0.002324324,0.00006902307,0.00160281,0.00001637471,0.00001151136,0.00001824419,0.00006581433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4618593,"threshold_uncertainty_score":0.5584884,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2045818236","doi":"10.3926/jiem.1275","title":"Research on the Competitiveness of Crediting Rating Industry using PCA Method","year":2014,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Lagging; Credit rating; Rating system; Competition (biology); Actuarial science; Originality; Business; Empirical research; Accounting; Economics; Environmental economics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.2881172524778674,"gpt":0.4474281160766733,"spread":0.1593108635988059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03144605,0.0001079462,0.0003453575,0.0008532744,0.0001934974,0.0001761843,0.0005381619,0.0001250895,0.0000330743],"category_scores_gemma":[0.005837617,0.00006673026,0.0001027253,0.001293473,0.0000718832,0.0001208195,0.00018563,0.001017681,0.000001522091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005663346,"about_ca_system_score_gemma":0.00004170286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001513393,"about_ca_topic_score_gemma":4.775326e-7,"domain_scores_codex":[0.9962754,0.0007429462,0.0008691737,0.0001820157,0.001704335,0.0002260797],"domain_scores_gemma":[0.9936101,0.004992693,0.0005735862,0.0002774761,0.0004658141,0.00008036732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004299993,0.00005031064,0.0007427434,0.00001748199,0.0001230908,0.0000154072,0.0001987685,0.9348083,0.001859205,0.02771551,0.0003847761,0.03404142],"study_design_scores_gemma":[0.001703185,0.0005824426,0.00220446,0.002186965,0.0001825045,0.00005391855,0.01030458,0.9498321,0.008851442,0.001447916,0.0223321,0.0003183312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8515001,0.0000577374,0.1442873,0.001175428,0.0007167382,0.0001462919,0.000001396117,0.000008047286,0.002106944],"genre_scores_gemma":[0.9934631,0.000006943873,0.00585945,0.0000340032,0.0005562659,0.000001010037,8.696731e-8,0.00000892719,0.00007019321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.141963,"threshold_uncertainty_score":0.9973301,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391963095","doi":"10.3926/jiem.6404","title":"Hospitalization forecast to inform COVID-19 pandemic planning and resource allocation using discrete event simulation","year":2024,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"European Regional Development Fund; Generalitat Valenciana","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Event (particle physics); Resource allocation; Discrete event simulation; Computer science; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Operations research; 2019-20 coronavirus outbreak; Resource (disambiguation); Simulation; Engineering; Medicine; Virology; Computer network; Disease; Outbreak; Infectious disease (medical specialty)","retraction":null,"screen_n_in":null,"score":{"opus":0.1590734521704715,"gpt":0.4428605080897655,"spread":0.283787055919294,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098512,0.00008925439,0.0001302358,0.0003336771,0.0002726293,0.00006157391,0.00003588396,0.0001106943,0.000006629281],"category_scores_gemma":[0.0003093552,0.00007793679,0.00002022988,0.0002810431,0.000005602033,0.0002217125,0.00004068078,0.0002623059,6.996793e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003137837,"about_ca_system_score_gemma":0.0001150738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002502336,"about_ca_topic_score_gemma":0.000002421877,"domain_scores_codex":[0.9990173,0.00005224353,0.000513839,0.0001047143,0.0001658635,0.0001460213],"domain_scores_gemma":[0.9994292,0.000136374,0.0001167715,0.0000570425,0.00007029856,0.0001903507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003130542,0.000003074522,0.001689826,0.0002379579,0.00003174062,0.000005289106,0.002184734,0.9856598,0.00002258126,0.001075915,0.0002093318,0.008848468],"study_design_scores_gemma":[0.00051387,0.000104076,0.0004501823,0.001126735,0.00004914047,0.000008551265,0.001253798,0.9380767,0.000001542303,0.0000209297,0.05829972,0.00009472538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2511379,0.0003092334,0.7456951,0.001630418,0.0005806975,0.0005427936,0.000003335271,0.0000441527,0.0000563765],"genre_scores_gemma":[0.994878,0.0001140569,0.004191786,0.0002261084,0.0004392056,0.00001135975,0.000013347,0.00001628969,0.0001098643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.74374,"threshold_uncertainty_score":0.317817,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4221008141","doi":"10.3926/jiem.3825","title":"An optimization model for demand-driven distribution resource planning DDDRP","year":2022,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Computer science; Supply chain; Network planning and design; Supply chain network; Operations research; Resource (disambiguation); Distribution (mathematics); Industrial engineering; Supply chain management; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03346280966992971,"gpt":0.2248383675885362,"spread":0.1913755579186065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008300736,0.0001416027,0.0001860442,0.0003224647,0.0002528576,0.0001676356,0.0002204109,0.00003890493,0.00002358755],"category_scores_gemma":[0.0000355576,0.0001447111,0.00007733057,0.000220678,0.000009968454,0.0005201276,0.0001691998,0.000187266,3.578879e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001099026,"about_ca_system_score_gemma":0.000009056534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004492488,"about_ca_topic_score_gemma":1.714455e-7,"domain_scores_codex":[0.9989432,0.00001153851,0.0003764214,0.0001587615,0.0003016909,0.000208368],"domain_scores_gemma":[0.9994855,0.00001801945,0.0002956077,0.0001170252,0.00005524318,0.0000286021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001360883,0.00006399121,0.0001096195,0.00007254024,0.0000723833,0.00001142334,0.0000507092,0.9746368,0.00002039923,0.006794364,0.01635485,0.001676844],"study_design_scores_gemma":[0.001409542,0.00007419592,0.00002283118,0.00004797577,0.0001174411,0.000003461414,0.000452048,0.8545964,0.000003405404,0.0000845411,0.143048,0.0001401049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01993187,0.0001095141,0.9770159,0.0007365465,0.0009266385,0.000619776,0.00001403037,0.00008068217,0.0005650791],"genre_scores_gemma":[0.9906819,0.00003076743,0.005680905,0.0006556711,0.002287211,0.0001019057,0.0002069974,0.0000541077,0.0003005716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9713349,"threshold_uncertainty_score":0.5901148,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2810507723","doi":"10.3926/jiem.2574","title":"The contribution of global sourcing to the economic performance of organizations: Analysis of the points of view of the supply chain participants","year":2018,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Purchasing; Safety stock; Business; Supply chain management; Supply chain risk management; Risk management; Supply chain; Originality; Stock management; Stock (firearms); Supplier relationship management; Supplier evaluation; Operations management; Risk analysis (engineering); Process management; Marketing; Qualitative research; Service management; Engineering; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.01030178963015363,"gpt":0.2165247364731818,"spread":0.2062229468430282,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001374642,0.0001044541,0.0003231391,0.0001493493,0.0001126183,0.00002665262,0.0005026711,0.00003610445,0.00001404842],"category_scores_gemma":[0.0002705581,0.00005074757,0.0001294707,0.001413594,0.0001098392,0.0001288585,0.0002929287,0.00008190682,5.789298e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005360181,"about_ca_system_score_gemma":0.00003538418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001735969,"about_ca_topic_score_gemma":0.00008537193,"domain_scores_codex":[0.9986481,0.00002813771,0.000771278,0.00008442452,0.0003050982,0.0001629539],"domain_scores_gemma":[0.9983463,0.00006525993,0.0009900318,0.0002805921,0.0003056235,0.00001223019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002997694,0.0001396605,0.2506368,0.0003776596,0.00304625,6.928181e-7,0.0004654276,0.6997187,0.0006849961,0.02475202,0.002274907,0.01760315],"study_design_scores_gemma":[0.003799018,0.0003814225,0.7228649,0.002565035,0.006838536,0.000002859392,0.004575704,0.2170547,0.01271222,0.0002134582,0.02858938,0.0004027436],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969434,0.0001618415,0.0006546243,0.001269543,0.0005231909,0.0003649683,0.000006650644,0.000002634653,0.00007315053],"genre_scores_gemma":[0.9994559,0.000240274,0.00002470562,0.00005048315,0.0002014995,0.00000338292,7.139611e-7,0.000005460568,0.00001752619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4826639,"threshold_uncertainty_score":0.2069426,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399054801","doi":"10.3926/jiem.6045","title":"Analysis of a new dynamic capacity management approach in DDMRP: Application on a real industrial case","year":2024,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Operations Management Techniques","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Originality; Workload; Computer science; Capacity management; Production (economics); Operations research; Service level; Industrial engineering; Operations management; Engineering; Business; Economics; Marketing; Microeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.1012453991469756,"gpt":0.3393637462078191,"spread":0.2381183470608434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00347217,0.0001884988,0.000488947,0.004328394,0.00003616779,0.0002575256,0.000367397,0.0001290473,0.00001413986],"category_scores_gemma":[0.0001217744,0.0001525058,0.0001920192,0.003595646,0.00002535092,0.0002847388,0.0001491231,0.000389956,0.00000224281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244848,"about_ca_system_score_gemma":0.00002773358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001463056,"about_ca_topic_score_gemma":0.00002717211,"domain_scores_codex":[0.997306,0.00008435461,0.001187043,0.0003595807,0.0008744128,0.0001886471],"domain_scores_gemma":[0.9989767,0.0001802515,0.0002906339,0.0003794125,0.00006551108,0.0001074944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001663125,0.0002990143,0.0008133324,0.0001005432,0.002572998,0.0009893854,0.0005907915,0.3706802,0.00007444982,0.04255866,0.006820213,0.5743341],"study_design_scores_gemma":[0.003599229,0.0006793151,0.004181324,0.0006975013,0.003159017,0.0001677897,0.002463535,0.9496602,0.0001112413,0.001342752,0.03331246,0.0006256058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7269285,0.0001622563,0.263209,0.0007579529,0.0009170718,0.001544013,0.00002009336,0.0001153716,0.006345738],"genre_scores_gemma":[0.9936233,0.0002390556,0.005502944,0.00001381024,0.0001432003,0.00002536772,0.000004063902,0.0000141379,0.0004341527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.57898,"threshold_uncertainty_score":0.6219005,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403262956","doi":"10.3926/jiem.7771","title":"Analysis of optimization models under different approaches to deal with uncertainty regarding pre-disaster planning in food bank supply chains","year":2024,"lang":"en","type":"article","venue":"Journal of Industrial Engineering and Management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Supply chain; Computer science; Risk analysis (engineering); Operations research; Economics; Business; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.05819769122586363,"gpt":0.2235796229990522,"spread":0.1653819317731886,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004847086,0.0002036046,0.0003994866,0.002148366,0.00003734236,0.0002296512,0.0001680477,0.00006380893,0.00001016828],"category_scores_gemma":[0.000008045713,0.00014749,0.0001076973,0.001295478,0.00001581589,0.0005351747,0.0001338239,0.0001968149,2.637034e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009047034,"about_ca_system_score_gemma":0.00001087041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004299113,"about_ca_topic_score_gemma":0.00002361701,"domain_scores_codex":[0.9986496,0.0000107984,0.000493741,0.0002318615,0.0003706757,0.0002433163],"domain_scores_gemma":[0.9996083,0.00004511726,0.0001608802,0.0001171102,0.00003657829,0.00003197998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001397326,0.0000462918,0.001672709,0.0002227098,0.001087913,0.00002974234,0.0003626986,0.9779353,0.00000440258,0.01127845,0.0001084065,0.007111687],"study_design_scores_gemma":[0.0008682453,0.0001019797,0.001681614,0.0009268789,0.0008214746,0.000001866985,0.001705314,0.9926021,0.000006869864,0.00006886729,0.001013677,0.0002011118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6750877,0.0003223095,0.322653,0.0006601765,0.0002425453,0.0004675183,0.000002522875,0.00003793911,0.0005262911],"genre_scores_gemma":[0.9983211,0.00007660308,0.001157416,0.0000619224,0.0002825929,0.00001812463,0.000009216401,0.00002167662,0.00005133159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3232334,"threshold_uncertainty_score":0.6014469,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}