{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":518,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":518,"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":"bfe3ee414a5f","filters":{"venue":"European Journal of Operational Research"}},"results":[{"id":"W1978415596","doi":"10.1016/s0377-2217(00)00248-4","title":"Recent trends in modeling of deteriorating inventory","year":2001,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1300,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Operations research; Computer science; Class (philosophy); Management science; Economics; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1881618412603019,"gpt":0.352647981333951,"spread":0.1644861400736492,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006379297,0.0000879095,0.0001546119,0.001364564,0.0001126836,0.0001783313,0.0003647016,0.00001380922,0.001133721],"category_scores_gemma":[0.000366447,0.00007706404,0.00006550419,0.0009107972,0.00005074199,0.0008842718,0.0001845455,0.0003187361,0.00005985711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009406477,"about_ca_system_score_gemma":0.00004665928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003689344,"about_ca_topic_score_gemma":0.00003216569,"domain_scores_codex":[0.9978528,0.000219536,0.0006771151,0.0001308205,0.0008818316,0.0002378799],"domain_scores_gemma":[0.9988165,0.00002971181,0.0001743087,0.000123072,0.0008331828,0.00002318031],"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":[0.001315792,0.001452323,0.09432949,0.0002540854,0.0001792651,0.002143845,0.001806851,0.2486393,0.01062071,0.03351728,0.04488499,0.560856],"study_design_scores_gemma":[0.002964741,0.000263868,0.02077695,0.0004978547,0.00001807898,0.00003431849,0.002338937,0.5635343,0.00006940561,0.000925431,0.4082384,0.0003376838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8393801,0.0004126012,0.0005265925,0.002491852,0.0002635353,0.00009127019,4.101031e-7,0.00000706122,0.1568265],"genre_scores_gemma":[0.9976313,0.0001862432,0.0002725855,0.0003231383,0.0009810315,0.000001341729,0.00000666389,0.00002052114,0.0005771979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5605184,"threshold_uncertainty_score":0.9997794,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969029115","doi":"10.1016/j.ejor.2013.12.033","title":"A review of recent research on green road freight transportation","year":2014,"lang":"en","type":"review","venue":"European Journal of Operational Research","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":738,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Transport engineering; Traffic management; Green logistics; Sustainable transport; Traffic planning; Road traffic; Business; Computer science; Environmental economics; Engineering; Sustainability; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.2809694111096483,"gpt":0.4583880352755617,"spread":0.1774186241659133,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01701055,0.0002235203,0.0009441361,0.0008337051,0.0001711773,0.00005186064,0.0007855319,0.00007728767,0.001180456],"category_scores_gemma":[0.0003744043,0.0001578257,0.0002930569,0.001059824,0.0001028701,0.000147186,0.00003043044,0.002433521,0.0003159918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871924,"about_ca_system_score_gemma":0.0005597548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004540768,"about_ca_topic_score_gemma":0.000001407015,"domain_scores_codex":[0.9931296,0.002773874,0.001534007,0.0001970714,0.002003403,0.0003620895],"domain_scores_gemma":[0.996501,0.0004998061,0.0002058036,0.000359972,0.002197446,0.0002359323],"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":[0.00001285614,0.00004119103,4.578646e-7,0.04349842,0.00007561946,0.00005463387,0.00004264625,0.0001787551,0.000007654055,0.0001919491,0.04648563,0.9094102],"study_design_scores_gemma":[0.0001342262,0.000339381,0.00002962206,0.1206841,0.00002898385,0.00003760643,0.000004092276,0.0001306754,0.000008118337,0.000006565056,0.878479,0.0001176161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002590754,0.9821084,0.00006023589,0.0002625998,0.000153304,0.0003816481,0.00004201398,0.000008176386,0.01695778],"genre_scores_gemma":[0.00009090482,0.9981592,0.0002394517,0.0000437803,0.0008151653,0.000009962349,0.00008413503,0.00008168411,0.0004757074],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9092926,"threshold_uncertainty_score":0.9998679,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2154429979","doi":"10.1016/j.ejor.2003.08.027","title":"Executing production schedules in the face of uncertainties: A review and some future directions","year":2003,"lang":"en","type":"review","venue":"European Journal of Operational Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":690,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Scheduling (production processes); Production (economics); Schedule; Operations research; Production schedule; Face (sociological concept); Work schedule; Work (physics); Management science; Operations management; Economics; Mathematics; Engineering; Microeconomics; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.09072389035271536,"gpt":0.3721100444108805,"spread":0.2813861540581651,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006832136,0.0001559306,0.0005314515,0.0003986314,0.0001330426,0.00008559164,0.0002876374,0.00004233275,0.00002794267],"category_scores_gemma":[0.0008867825,0.0001007035,0.0001157178,0.000792205,0.00007898322,0.0001872755,0.00002652995,0.001110795,0.000007914515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007710333,"about_ca_system_score_gemma":0.0002091712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.449948e-7,"about_ca_topic_score_gemma":4.864888e-7,"domain_scores_codex":[0.9965271,0.001821009,0.0007924521,0.00013679,0.000558699,0.0001639637],"domain_scores_gemma":[0.9989097,0.0002246907,0.0001560196,0.000167113,0.0004912785,0.0000512491],"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":[0.000006285604,0.0001161462,0.000004233638,0.03063002,0.000304676,0.00005995755,0.001517603,0.02045799,0.000003071806,0.001991309,0.005610241,0.9392985],"study_design_scores_gemma":[0.0001058942,0.00005756002,0.000008926327,0.01620415,0.0001074486,0.0003193846,0.0006564101,0.0003183643,0.000001300599,0.0000127611,0.9820771,0.0001307358],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000223047,0.9980474,0.0002268551,0.0005193103,0.0002941191,0.0003379326,0.000006289124,0.000006895217,0.0005388986],"genre_scores_gemma":[0.00002669092,0.9945705,0.004595931,0.00002736821,0.0005860744,0.000008899541,0.00001041223,0.00003436501,0.000139767],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9764668,"threshold_uncertainty_score":0.4825914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2122672261","doi":"10.1016/j.ejor.2008.05.011","title":"Additive efficiency decomposition in two-stage DEA","year":2008,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":684,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"China Scholarship Council; Worcester Polytechnic Institute","keywords":"Data envelopment analysis; Returns to scale; Decomposition; Stage (stratigraphy); Efficiency; Constant (computer programming); Process (computing); Product (mathematics); Computer science; Econometrics; Additive model; Scale (ratio); Operations research; Economics; Mathematical optimization; Mathematics; Statistics; Production (economics); Microeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.2300218538597624,"gpt":0.5026539069179089,"spread":0.2726320530581465,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.03343412,0.0001195168,0.0002810451,0.001943241,0.0006212296,0.0003189574,0.001288959,0.00001770593,0.001007297],"category_scores_gemma":[0.01066965,0.00008787687,0.0001643982,0.002659857,0.0004353933,0.0007121277,0.0001804188,0.000809344,0.001076092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001847438,"about_ca_system_score_gemma":0.0006711298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001866197,"about_ca_topic_score_gemma":0.00002623591,"domain_scores_codex":[0.9871339,0.005417423,0.001400175,0.000363484,0.005293882,0.0003910929],"domain_scores_gemma":[0.9927678,0.002886779,0.0003077503,0.0003288249,0.003509221,0.0001996452],"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":[0.001526616,0.003867632,0.07535941,0.00001095723,0.0001551746,0.02367778,0.01648036,0.6282749,0.06858086,0.03049335,0.1010129,0.05056009],"study_design_scores_gemma":[0.007544378,0.002856216,0.7855924,0.0003709692,0.00002351348,0.003008965,0.004270017,0.1026177,0.009065306,0.004381483,0.07928469,0.0009843827],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401576,0.0002004564,0.01204372,0.001428634,0.0001545143,0.0001063317,0.0000120352,0.000005257176,0.04589143],"genre_scores_gemma":[0.9948707,0.00004528372,0.002476307,0.0001433273,0.0002671324,9.487463e-7,0.000004446395,0.00001460112,0.002177302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.710233,"threshold_uncertainty_score":0.9999059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2040075495","doi":"10.1016/j.ejor.2013.08.002","title":"The bi-objective Pollution-Routing Problem","year":2013,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":442,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"University of Southampton","keywords":"Weighting; Mathematical optimization; Computer science; Normalization (sociology); Vehicle routing problem; Set (abstract data type); Routing (electronic design automation); Minification; Constraint (computer-aided design); Extension (predicate logic); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05395561392824383,"gpt":0.3389584209137308,"spread":0.285002806985487,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008382143,0.00008873171,0.00009838456,0.0001700608,0.0006011438,0.0004516336,0.0003935686,0.00001850004,0.0001685544],"category_scores_gemma":[0.001287012,0.00006047003,0.00005591024,0.0004279917,0.000111394,0.000380041,0.00007039839,0.0007000036,0.0002955001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001379245,"about_ca_system_score_gemma":0.0001318591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004609836,"about_ca_topic_score_gemma":7.97861e-7,"domain_scores_codex":[0.9968314,0.001506424,0.0004927564,0.00008983911,0.0007661122,0.0003134969],"domain_scores_gemma":[0.9975724,0.0005902085,0.00006715637,0.0001386328,0.001507995,0.0001236608],"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":[0.00002786083,0.00004409257,0.0006712497,0.00001961597,0.0001652705,0.00004105341,0.001818887,0.8523622,0.0257733,0.01098735,0.04111831,0.06697085],"study_design_scores_gemma":[0.002657887,0.0009014104,0.1304321,0.0004393444,0.00002580758,0.0006667879,0.003859307,0.769015,0.01114298,0.003006512,0.07705238,0.0008005665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3036712,0.002206209,0.3461417,0.01525903,0.001472383,0.001476429,0.00001081622,0.0002394581,0.3295228],"genre_scores_gemma":[0.9555721,0.0001078,0.04275326,0.00004636657,0.0005118414,0.000004924719,0.00000110034,0.00004132644,0.0009612485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6519009,"threshold_uncertainty_score":0.4623573,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980201624","doi":"10.1016/j.ejor.2007.12.014","title":"An exact -constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits","year":2007,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":363,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Travelling salesman problem; Mathematical optimization; Heuristics; Combinatorial optimization; 2-opt; Traveling purchaser problem; Vertex (graph theory); Mathematics; Multi-objective optimization; Bottleneck traveling salesman problem; Pareto principle; Constraint (computer-aided design); Computer science; Combinatorics; Graph","retraction":null,"screen_n_in":null,"score":{"opus":0.04206008863009993,"gpt":0.3738648753142147,"spread":0.3318047866841148,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01492814,0.0001765566,0.0001913814,0.0003914631,0.0007112113,0.0004440792,0.001108603,0.00003462703,0.000006011826],"category_scores_gemma":[0.0005508286,0.0001208409,0.00005584349,0.001128583,0.0001059752,0.001090053,0.0001049645,0.0005120307,0.000009254066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002619879,"about_ca_system_score_gemma":0.000519883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004599754,"about_ca_topic_score_gemma":0.000006966969,"domain_scores_codex":[0.9960355,0.001220958,0.0006619585,0.0004551595,0.001204018,0.0004223991],"domain_scores_gemma":[0.9932691,0.0006651412,0.0003016389,0.0003549041,0.005140606,0.0002686247],"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":[0.000212337,0.0001767554,0.00002817423,0.000009210233,0.00003494711,0.00001247093,0.002242816,0.9271317,0.003033038,0.02608404,0.00004688592,0.04098758],"study_design_scores_gemma":[0.002690071,0.003175122,0.001223171,0.0001077121,0.00001229931,0.0002494241,0.0007253129,0.9819117,0.005740713,0.001044837,0.002808039,0.0003116186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003513339,0.00001975306,0.99471,0.001582518,0.0001503182,0.001971449,0.000006757812,0.00003139704,0.001176505],"genre_scores_gemma":[0.165919,0.000005658586,0.8333071,0.0001225777,0.0004922317,0.0000539005,0.00001267677,0.00003723047,0.00004962219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1655676,"threshold_uncertainty_score":0.5470134,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008806816","doi":"10.1016/s0377-2217(02)00915-3","title":"Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies","year":2003,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":347,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Computer science; Vehicle routing problem; Fleet management; Time horizon; Field (mathematics); Routing (electronic design automation); Operations research; Routing algorithm; Algorithm; Emphasis (telecommunications); Mathematical optimization; Telecommunications; Computer network; Routing protocol; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.06723250682678367,"gpt":0.3664937950685185,"spread":0.2992612882417349,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008181138,0.0001193769,0.000174861,0.0001769148,0.0003198588,0.0003350879,0.0001790397,0.00003150777,0.0001064494],"category_scores_gemma":[0.0006478077,0.0001140335,0.00004145014,0.0002735643,0.0001285631,0.0004071197,0.00004551709,0.0005212091,0.00004366726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009117485,"about_ca_system_score_gemma":0.0001686577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000293289,"about_ca_topic_score_gemma":2.354476e-7,"domain_scores_codex":[0.9964715,0.001930306,0.0005198328,0.0001413922,0.0006164682,0.0003205611],"domain_scores_gemma":[0.9985932,0.0004074637,0.00007746373,0.0001100278,0.0006535304,0.0001583089],"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":[0.00002473563,0.00004150307,0.0005426837,0.00002868243,0.00007171644,0.0001055281,0.001491784,0.913367,0.06223197,0.01218682,0.002069191,0.007838325],"study_design_scores_gemma":[0.001290931,0.0002636543,0.008963018,0.000115812,0.000009756664,0.0002570584,0.0009807989,0.9837227,0.001631863,0.0002131627,0.002306313,0.0002448587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4498955,0.0006700851,0.484542,0.0004016523,0.0002849577,0.0002280251,0.000004773066,0.0001135896,0.06385941],"genre_scores_gemma":[0.8012952,0.0001748613,0.1980412,0.0000116201,0.0002189395,4.203172e-7,0.000003199219,0.00003808062,0.0002163827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3513997,"threshold_uncertainty_score":0.465015,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994217814","doi":"10.1016/j.ejor.2010.05.006","title":"Network DEA: Additive efficiency decomposition","year":2010,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":323,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Computer science; Process (computing); Set (abstract data type); Decomposition; Function (biology); Data envelopment analysis; Mathematical optimization; Black box; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1442268597334244,"gpt":0.4682453511546586,"spread":0.3240184914212342,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.05328759,0.0001225039,0.0002540128,0.0008273114,0.0009317056,0.0009284077,0.001673753,0.00003616067,0.002120328],"category_scores_gemma":[0.01555504,0.00008508169,0.0001894924,0.002141869,0.000432432,0.0006067416,0.000227195,0.001433154,0.001754823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005497273,"about_ca_system_score_gemma":0.0005334081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002953955,"about_ca_topic_score_gemma":0.00001301631,"domain_scores_codex":[0.9888096,0.003822662,0.001240437,0.000354712,0.005326033,0.000446488],"domain_scores_gemma":[0.9887701,0.003921631,0.0003765842,0.000432791,0.006224571,0.0002743246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006581279,0.001318278,0.008778609,0.000004982315,0.0001632243,0.001859192,0.002568445,0.1332466,0.1515139,0.08959413,0.4978788,0.1124156],"study_design_scores_gemma":[0.003092794,0.00336842,0.3750698,0.0002404003,0.00007342798,0.002030064,0.001472474,0.06110486,0.005576238,0.03802288,0.5089466,0.001002092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8791957,0.0002009847,0.03942291,0.005800883,0.001257525,0.000158541,0.00001236121,0.0000129142,0.07393821],"genre_scores_gemma":[0.988874,0.00001018093,0.007992807,0.0002667051,0.001730355,8.372562e-7,0.00000451389,0.00001716662,0.001103393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3662912,"threshold_uncertainty_score":0.9990224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2756063524","doi":"10.1016/j.ejor.2017.08.040","title":"High dimensional data classification and feature selection using support vector machines","year":2017,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":320,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Feature selection; Support vector machine; Binary classification; Classifier (UML); Artificial intelligence; Data mining; Machine learning; Big data; Linear classifier; Data classification","retraction":null,"screen_n_in":null,"score":{"opus":0.1663939795343459,"gpt":0.419157855783111,"spread":0.2527638762487652,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002118877,0.00007608934,0.00008035844,0.00009239162,0.0006471375,0.0002502403,0.0004975635,0.00003819708,0.00005597701],"category_scores_gemma":[0.0005936411,0.00006156945,0.00002394739,0.00004767651,0.0001258344,0.00004858857,0.0002839213,0.0002444861,0.000006851935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002279441,"about_ca_system_score_gemma":0.0003062806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006329946,"about_ca_topic_score_gemma":0.000006034796,"domain_scores_codex":[0.9985649,0.0004085336,0.0002061654,0.0002419038,0.0004543282,0.0001241998],"domain_scores_gemma":[0.9985773,0.00001319691,0.0001925779,0.0004170167,0.0006985162,0.00010142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001710931,0.00003837301,0.00370592,0.000005559924,0.00002688244,0.000007133406,0.00001739605,0.0001140185,0.9566143,0.0003325498,0.03332504,0.005641788],"study_design_scores_gemma":[0.001722779,0.0008025425,0.8261345,0.00007913789,0.00002739595,0.0004944432,0.00008266927,0.01261397,0.04031017,0.00008919367,0.11738,0.0002631941],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903306,0.0003496031,0.002287053,0.005501941,0.0003376169,0.0001180214,0.00003568859,0.000002731162,0.001036735],"genre_scores_gemma":[0.9932027,0.00009853783,0.00416811,0.00006916626,0.001053543,8.227538e-7,0.0001605559,0.00001617684,0.001230419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9163041,"threshold_uncertainty_score":0.4977324,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2068400656","doi":"10.1016/s0377-2217(02)00243-6","title":"A multivariate statistical approach to reducing the number of variables in data envelopment analysis","year":2003,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":294,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Data envelopment analysis; Efficiency; Econometrics; Statistics; Multivariate statistics; Computer science; Variables; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.3616397145239165,"gpt":0.5072767616607607,"spread":0.1456370471368443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.09764312,0.0001001671,0.0003669375,0.001149198,0.0002644032,0.0004177719,0.002362729,0.0000180462,0.0006778986],"category_scores_gemma":[0.04351958,0.00005755324,0.00008782603,0.005378751,0.0002081261,0.0003177192,0.0004378158,0.0005233302,0.0001324399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008379438,"about_ca_system_score_gemma":0.0007126828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006214281,"about_ca_topic_score_gemma":0.00001139619,"domain_scores_codex":[0.9833549,0.009430327,0.001675546,0.0004785649,0.004735943,0.0003247194],"domain_scores_gemma":[0.9920509,0.004622691,0.0002762541,0.0009184277,0.001962409,0.0001693438],"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":[0.00028594,0.001629934,0.04350086,0.000009290617,0.0009442846,0.0002046261,0.008083697,0.802352,0.004206895,0.1079427,0.02038911,0.01045062],"study_design_scores_gemma":[0.002013947,0.0002633206,0.5577996,0.0001486375,0.000321454,0.0002393812,0.007301944,0.3652467,0.0007478541,0.005127213,0.06024387,0.0005460241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1941399,0.0001066017,0.743928,0.002330502,0.0001263688,0.0002512684,0.00006474832,0.000002787954,0.05904984],"genre_scores_gemma":[0.8692629,0.00000779389,0.1299909,0.00005702952,0.00004823915,9.771649e-7,0.000008533669,0.00000842066,0.0006151692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.675123,"threshold_uncertainty_score":0.9645373,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2035380861","doi":"10.1016/j.ejor.2007.03.007","title":"A review of the joint replenishment problem literature: 1989–2005","year":2007,"lang":"en","type":"review","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":294,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Joint (building); Computer science; Quality (philosophy); Mathematical optimization; Operations research; Mathematical economics; Economics; Mathematics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.2120009324741855,"gpt":0.3912949006372418,"spread":0.1792939681630563,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0239345,0.0003275989,0.000988395,0.0009307719,0.0002840662,0.0005039599,0.001464088,0.00005476222,0.001062227],"category_scores_gemma":[0.001158631,0.0001870359,0.000873278,0.00150281,0.0001781681,0.0005831799,0.0008888348,0.001416782,0.0003080714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002138019,"about_ca_system_score_gemma":0.0004266874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004848184,"about_ca_topic_score_gemma":0.000001618334,"domain_scores_codex":[0.9938108,0.0009796474,0.00214987,0.0003220421,0.002290233,0.0004473537],"domain_scores_gemma":[0.9957359,0.0001439812,0.001396479,0.0005914066,0.00208428,0.00004795766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001375894,0.0001617053,0.000002541801,0.1064496,0.0001956127,0.0001519153,0.00002801494,0.000004707129,0.000001605152,0.009510227,0.5604871,0.3229932],"study_design_scores_gemma":[0.0001713039,0.00003432185,0.00001047993,0.1777188,0.0001420169,0.00005791579,0.00001456006,0.000004730478,6.62286e-7,0.00005893976,0.8216467,0.0001395922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[8.361318e-7,0.9335999,0.00002735942,0.00195423,0.0004906033,0.001084331,0.000007766682,0.000006906567,0.0628281],"genre_scores_gemma":[0.000009645372,0.9903488,0.0002846407,0.002298927,0.003315262,0.00001366002,0.00005464293,0.00006979911,0.00360465],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3228536,"threshold_uncertainty_score":0.9998509,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1963617203","doi":"10.1016/j.ejor.2003.08.068","title":"An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty","year":2004,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":283,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interval (graph theory); Stochastic programming; Mathematical optimization; Fuzzy logic; Computer science; Economic shortage; Process (computing); Stage (stratigraphy); Robust optimization; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.05360354090258693,"gpt":0.3331294540138367,"spread":0.2795259131112497,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002286055,0.0001449028,0.0001432866,0.0004062914,0.0001962337,0.0004935865,0.0004514745,0.0000178602,0.0001036491],"category_scores_gemma":[0.00002979478,0.0001034391,0.00008617423,0.0001540432,0.00007631885,0.0003943892,0.00008555492,0.0002859965,0.00006026936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001494628,"about_ca_system_score_gemma":0.00001121098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002860963,"about_ca_topic_score_gemma":0.000004934029,"domain_scores_codex":[0.9981087,0.0002499931,0.000434064,0.00017235,0.0006515615,0.0003833485],"domain_scores_gemma":[0.9992294,0.00005063398,0.00003731274,0.0001848265,0.0003554008,0.0001424748],"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":[0.0001206725,0.000107486,0.000006887299,0.0000508447,0.0001103791,0.00004681704,0.0009183031,0.9917144,0.0006860822,0.001594582,0.0004013692,0.004242163],"study_design_scores_gemma":[0.01732871,0.00737745,0.0037421,0.0008374269,0.0001910598,0.0000957805,0.00411462,0.8230953,0.004050948,0.008148446,0.1295451,0.001473093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7236465,0.00008586828,0.2663885,0.0006189633,0.0002302877,0.0009709347,0.000008515193,0.00009546393,0.007954986],"genre_scores_gemma":[0.9811718,0.00001148848,0.01716487,0.00006147431,0.0003685769,0.00002517384,0.00004812685,0.00006080882,0.001087655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2575254,"threshold_uncertainty_score":0.4759666,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099860183","doi":"10.1016/j.ejor.2009.06.034","title":"An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles","year":2009,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":272,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Vehicle routing problem; Column generation; Mathematical optimization; Benchmark (surveying); Computer science; Routing (electronic design automation); Shortest path problem; Lagrangian relaxation; Set (abstract data type); Linear programming; Dynamic programming; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.06359111993787328,"gpt":0.3323522610403489,"spread":0.2687611411024756,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004128777,0.0001058066,0.0001856613,0.0002098188,0.0001566964,0.0001896112,0.0001794701,0.00002362518,0.00001365531],"category_scores_gemma":[0.00040041,0.00008744001,0.00003478644,0.0002319258,0.00006551816,0.0006332279,0.00001916371,0.0003055828,0.000002726229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004178917,"about_ca_system_score_gemma":0.00008057009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001746352,"about_ca_topic_score_gemma":3.420783e-7,"domain_scores_codex":[0.9980466,0.0006389552,0.0004423163,0.0001303368,0.00050476,0.0002370173],"domain_scores_gemma":[0.9981675,0.0005410778,0.00008691329,0.0001246853,0.0009323222,0.0001475063],"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":[0.0001458218,0.0001039624,0.001306328,0.00002251197,0.00005537567,0.00003315548,0.000698733,0.7455714,0.1144578,0.0001251578,0.0003124075,0.1371674],"study_design_scores_gemma":[0.001231776,0.001129718,0.01349472,0.0001129929,0.000008327923,0.00006293878,0.00005940915,0.976464,0.006857392,0.00002179124,0.0004474687,0.0001094188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6098316,0.0001068815,0.3889534,0.000248793,0.00002169047,0.0003763297,0.00002212,0.00003625351,0.0004028926],"genre_scores_gemma":[0.5798408,0.00001374262,0.4199263,0.0000171604,0.0001124532,7.245367e-7,0.000004864396,0.00002740337,0.00005652455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2308927,"threshold_uncertainty_score":0.35657,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2332834184","doi":"10.1016/j.ejor.2016.03.040","title":"An adaptive large neighborhood search for the two-echelon multiple-trip vehicle routing problem with satellite synchronization","year":2016,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":266,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Vehicle routing problem; Heuristics; Computer science; Synchronization (alternating current); Routing (electronic design automation); Set (abstract data type); Mathematical optimization; Real-time computing; Operations research; Computer network; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.0590928165349166,"gpt":0.340670755225449,"spread":0.2815779386905324,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01164114,0.0001539576,0.0001642881,0.0002167256,0.0005340619,0.0002558902,0.0004939969,0.00003130135,0.00005759904],"category_scores_gemma":[0.0006239368,0.00008703938,0.00005648539,0.0004947542,0.00009921734,0.0006723507,0.0000576971,0.0004804095,0.00002620408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002310143,"about_ca_system_score_gemma":0.0002469092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002249881,"about_ca_topic_score_gemma":0.000005546371,"domain_scores_codex":[0.9962,0.001639443,0.0005138787,0.0002071501,0.0009472609,0.0004922159],"domain_scores_gemma":[0.9957244,0.001810274,0.00009127669,0.0002453973,0.001955049,0.000173596],"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":[0.0005424445,0.0001191411,0.007245197,0.00003438722,0.000172193,0.00004239656,0.001610687,0.8223668,0.03468287,0.007256199,0.0001567327,0.125771],"study_design_scores_gemma":[0.003439461,0.001045255,0.007317424,0.0002464811,0.0000179888,0.0000664129,0.0005759452,0.9776703,0.008197859,0.00004816814,0.001169301,0.0002054794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02674543,0.0002705262,0.9701048,0.0008574836,0.00007515882,0.0005001739,0.00002213009,0.00004877083,0.001375593],"genre_scores_gemma":[0.9217843,0.0001196019,0.07726195,0.00003101496,0.0005598101,0.000009896176,0.000007287259,0.00009058121,0.0001356017],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8950388,"threshold_uncertainty_score":0.4107626,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1996809294","doi":"10.1016/s0377-2217(99)00013-2","title":"Determination of economic production–shipment policy for a single-vendor–single-buyer system","year":2000,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":258,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Concordia University","keywords":"Vendor; Production (economics); Product (mathematics); Business; Operations management; Computer science; Operations research; Industrial organization; Marketing; Economics; Microeconomics; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.115056820812557,"gpt":0.3257794824584556,"spread":0.2107226616458986,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004024005,0.0001098196,0.000170556,0.000747192,0.0002329501,0.0002991096,0.0003450827,0.00001609201,0.0005109262],"category_scores_gemma":[0.0003333474,0.00009782846,0.0001117575,0.0002092085,0.00008287021,0.00091493,0.00007101297,0.0001372928,0.0002370134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003549711,"about_ca_system_score_gemma":0.0001090139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002245814,"about_ca_topic_score_gemma":0.000006348919,"domain_scores_codex":[0.9981499,0.0001623626,0.0006524497,0.0001869845,0.0006033885,0.0002448735],"domain_scores_gemma":[0.9987029,0.0000711372,0.0002508712,0.0001609531,0.0007862045,0.00002796725],"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":[0.003111427,0.002721309,0.001388835,0.002784629,0.0004595596,0.000280019,0.001548884,0.02161739,0.06545267,0.2181502,0.1166676,0.5658175],"study_design_scores_gemma":[0.003176203,0.0007921471,0.002535866,0.0007553208,0.0000663982,0.00009856612,0.001538829,0.01272387,0.006188393,0.00103724,0.9706746,0.0004125588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5765147,0.0003186811,0.002615184,0.01573581,0.001665068,0.001789787,0.00001538316,0.00005397006,0.4012915],"genre_scores_gemma":[0.9899715,0.00001461171,0.0009909868,0.0001649166,0.004886756,0.00001065051,0.00001510924,0.00003286684,0.003912633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8540071,"threshold_uncertainty_score":0.5594283,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3027680723","doi":"10.1016/j.ejor.2020.05.014","title":"Manufacturer vs. Consumer Subsidy with Green Technology Investment and Environmental Concern","year":2020,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":250,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Youth Innovation Promotion Association of the Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Subsidy; Production (economics); Incentive; Profit (economics); Consumption (sociology); Economics; Business; Welfare; Investment (military); Microeconomics; Industrial organization; Market economy","retraction":null,"screen_n_in":null,"score":{"opus":0.04526066025482519,"gpt":0.2637256614478679,"spread":0.2184650011930427,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001305782,0.00013193,0.0001581474,0.0004005408,0.0002313784,0.0003009156,0.0003448724,0.00001985998,0.0005909949],"category_scores_gemma":[0.0001467415,0.00009910388,0.00002702469,0.0003063981,0.0003534192,0.000600933,0.0004057497,0.0004383739,0.0002023805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006772609,"about_ca_system_score_gemma":0.00005632449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001855514,"about_ca_topic_score_gemma":0.00000306998,"domain_scores_codex":[0.9982754,0.0001179019,0.0002935093,0.0002158346,0.0008254237,0.0002719526],"domain_scores_gemma":[0.999406,0.00004866884,0.0001292722,0.0001169264,0.0002447027,0.00005442557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005580215,0.001066782,0.4166514,0.001232341,0.001926716,0.0223038,0.00412455,0.006605772,0.0143339,0.1669008,0.3006855,0.0585883],"study_design_scores_gemma":[0.002786662,0.0005074914,0.02950537,0.0000573553,0.00004607544,0.0000820642,0.005189522,0.001646728,0.0003563692,0.0007107801,0.9588292,0.0002824169],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9097943,0.0006459879,0.0006009793,0.07072647,0.00006500725,0.0005420704,0.000005101712,0.00002969273,0.0175904],"genre_scores_gemma":[0.9921241,0.00004002863,0.000471417,0.006137258,0.0006414657,0.000003554914,0.00001289788,0.00003291707,0.0005363472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6581437,"threshold_uncertainty_score":0.647098,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2045599420","doi":"10.1016/j.ejor.2005.12.026","title":"A heuristic for the multi-satellite, multi-orbit and multi-user management of Earth observation satellites","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Satellite Communication Systems","field":"Engineering","cited_by":244,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Tabu search; Earth observation satellite; Computer science; Satellite; Bounding overwatch; Scheduling (production processes); Heuristic; Column generation; Earth observation; Orbit determination; Operations research; Time horizon; Real-time computing; Remote sensing; Mathematical optimization; Algorithm; Aerospace engineering; Artificial intelligence; Geology; Mathematics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1788735015970575,"gpt":0.3574932122903898,"spread":0.1786197106933323,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004113242,0.0001319476,0.0001803719,0.0002006228,0.0002074588,0.0001626563,0.0004847427,0.0000256229,0.00001888053],"category_scores_gemma":[0.0001814787,0.00009852032,0.00007435705,0.0002897524,0.0001303766,0.0002267946,0.00009343715,0.0003036067,0.00002634616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003829611,"about_ca_system_score_gemma":0.0000310108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001051145,"about_ca_topic_score_gemma":0.00001374763,"domain_scores_codex":[0.9977456,0.0005366491,0.0007904485,0.0001327944,0.0005678022,0.0002267207],"domain_scores_gemma":[0.9976631,0.000809035,0.0001230514,0.00032187,0.001013762,0.00006914382],"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":[0.001042384,0.002610957,0.0934073,0.004524156,0.002734801,0.0003895248,0.01005427,0.3093605,0.2549425,0.06132638,0.004940999,0.2546661],"study_design_scores_gemma":[0.003746534,0.0001940704,0.631066,0.0004943209,0.00004286143,0.0000626945,0.001072108,0.1436621,0.005488436,0.00004073283,0.2138429,0.0002873158],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4374873,0.116123,0.4354927,0.001586577,0.0008540229,0.003728985,0.0001167182,0.0001261328,0.004484647],"genre_scores_gemma":[0.7992621,0.006905154,0.1897648,0.00002229192,0.0001973832,0.00002163207,0.00002568224,0.00006835409,0.003732588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5376586,"threshold_uncertainty_score":0.4017542,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2027362250","doi":"10.1016/j.ejor.2007.05.042","title":"Retailer’s optimal replenishment decisions with credit-linked demand under permissible delay in payments","year":2007,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":240,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Trade credit; Payment; Order (exchange); Economic order quantity; Business; Microeconomics; Period (music); Economics; Actuarial science; Finance; Supply chain; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.1167070718986254,"gpt":0.3446620012063871,"spread":0.2279549293077617,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01251069,0.0001576356,0.0001938591,0.001009114,0.000345823,0.0005316284,0.0005268651,0.00002626033,0.001035459],"category_scores_gemma":[0.000495923,0.0001167565,0.00007248118,0.0007204707,0.0001199754,0.001129705,0.0002747588,0.0005543563,0.0002345983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764223,"about_ca_system_score_gemma":0.0001310699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002257119,"about_ca_topic_score_gemma":0.00003593813,"domain_scores_codex":[0.9965345,0.0001929573,0.0007570619,0.0002698915,0.001763743,0.0004818073],"domain_scores_gemma":[0.9983041,0.0002121787,0.0001980645,0.0002342639,0.000974944,0.0000764448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.009462014,0.004487983,0.1572609,0.0002987228,0.0008949236,0.01999228,0.002134131,0.1346038,0.009103909,0.09335422,0.5303066,0.03810051],"study_design_scores_gemma":[0.007359656,0.000758441,0.3801517,0.0007883716,0.00005180998,0.0001588647,0.004556553,0.009550647,0.000276458,0.0007266253,0.5950253,0.0005955116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056129,0.0002273437,0.009729054,0.003768264,0.0003350513,0.0004084223,0.000001531789,0.00001672945,0.07990068],"genre_scores_gemma":[0.9931905,0.00005274648,0.002299182,0.0009831855,0.001367153,0.000003302003,0.00001627192,0.00003838017,0.002049338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2228908,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2793538957","doi":"10.1016/j.ejor.2018.02.055","title":"Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles","year":2018,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":226,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Université de Montréal; HEC Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Relocation; Context (archaeology); Dynamism; Computer science; Operations research; Field (mathematics); Risk analysis (engineering); Management science; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1135363571816246,"gpt":0.3555186643399212,"spread":0.2419823071582966,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005305996,0.00007514377,0.0001122201,0.0006999515,0.000174388,0.00007973156,0.0001913448,0.00002051092,0.0008056747],"category_scores_gemma":[0.0008755261,0.000066054,0.0000168423,0.0008941432,0.0001264747,0.0009791376,0.0001472433,0.0001751905,0.00001234584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002602445,"about_ca_system_score_gemma":0.00005438356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001180095,"about_ca_topic_score_gemma":0.0002144621,"domain_scores_codex":[0.9980456,0.0001791339,0.0006452932,0.0001540231,0.0008395669,0.0001363672],"domain_scores_gemma":[0.997665,0.0000255799,0.00009070685,0.0001016991,0.002081867,0.00003518151],"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":[0.0003956774,0.0006160068,0.02053925,0.00032981,0.00008743165,0.00002436111,0.002409436,0.4447679,0.0003081384,0.1031512,0.02248708,0.4048837],"study_design_scores_gemma":[0.0007593889,0.00009004344,0.118134,0.0001468577,0.000009900151,0.000005720172,0.0005487892,0.8701636,0.0000144852,0.001123843,0.008879131,0.0001242757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9080889,0.001469556,0.04558104,0.02744377,0.0004913276,0.0002288803,0.000001760363,0.00001415101,0.01668068],"genre_scores_gemma":[0.9968126,0.001656184,0.0007245833,0.000157945,0.0004434985,0.000001706464,0.00001415398,0.00001103252,0.0001782964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4253958,"threshold_uncertainty_score":0.8821573,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012920499","doi":"10.1016/j.ejor.2009.05.012","title":"Deriving the DEA frontier for two-stage processes","year":2009,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":223,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Efficient frontier; Frontier; Econometrics; Stage (stratigraphy); Process (computing); Projection (relational algebra); Envelopment; Economics; Computer science; Mathematical optimization; Mathematics; Algorithm; Financial economics","retraction":null,"screen_n_in":null,"score":{"opus":0.275618365468491,"gpt":0.4997166474752832,"spread":0.2240982820067922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04304622,0.00009765579,0.0002009944,0.0005076263,0.0009647403,0.001318901,0.00180724,0.00001357699,0.0002902002],"category_scores_gemma":[0.03597433,0.00005176795,0.0001532419,0.001385769,0.0001986806,0.0005888384,0.00009263992,0.0004395193,0.0001554174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005326709,"about_ca_system_score_gemma":0.0007185793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002029049,"about_ca_topic_score_gemma":0.000009264244,"domain_scores_codex":[0.9927097,0.002042485,0.000926443,0.0002577422,0.003734598,0.0003290495],"domain_scores_gemma":[0.9891986,0.003747379,0.0002854831,0.0003487834,0.006292013,0.0001276986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001064241,0.001107743,0.005816127,0.00003063815,0.0002471961,0.0005643371,0.008516,0.202557,0.04334059,0.04436728,0.4364302,0.2559587],"study_design_scores_gemma":[0.002817192,0.002527925,0.05919616,0.0002222663,0.0000548578,0.000285005,0.004399645,0.04540643,0.007169918,0.01770591,0.8596832,0.0005315358],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4922777,0.002482894,0.4045728,0.05468131,0.000493226,0.0005832731,0.00002091775,0.00001721533,0.0448707],"genre_scores_gemma":[0.9857584,0.00001739962,0.006484553,0.0005901724,0.0006279919,0.000001233573,0.000001226249,0.00001167461,0.006507323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4934808,"threshold_uncertainty_score":0.9997178,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2036961948","doi":"10.1016/j.ejor.2009.01.026","title":"Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach","year":2009,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":216,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Fuzzy logic; Computer science; Selection (genetic algorithm); Supply chain; Programming paradigm; Operations research; Mathematical optimization; Machine learning; Artificial intelligence; Mathematics; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.3715824838578539,"gpt":0.5019066362398276,"spread":0.1303241523819737,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04659226,0.0001673714,0.000331304,0.0008362844,0.0008924467,0.001520039,0.0007346931,0.00004870658,0.00003533199],"category_scores_gemma":[0.02055938,0.0001169097,0.0001633175,0.0008431883,0.0001192133,0.0008503135,0.0001425077,0.0008193773,0.000021303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321014,"about_ca_system_score_gemma":0.0003185292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008244446,"about_ca_topic_score_gemma":0.000004850268,"domain_scores_codex":[0.9915034,0.003192468,0.001278065,0.0006163838,0.002989289,0.0004204476],"domain_scores_gemma":[0.9915959,0.00154565,0.0003293115,0.0002942682,0.005948815,0.0002860294],"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":[0.003735122,0.00210398,0.01182113,0.0000222497,0.0001539527,0.00005944977,0.008651354,0.1416635,0.01163171,0.004489042,0.004264675,0.8114039],"study_design_scores_gemma":[0.002502206,0.001140726,0.04207812,0.00003239453,0.0000151728,0.0002343832,0.001790071,0.9419771,0.0001431659,0.007369033,0.002509329,0.0002082849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.447406,0.0001588096,0.5498318,0.0002579712,0.00008050785,0.0005311965,0.0000145248,0.000009055043,0.001710076],"genre_scores_gemma":[0.7090271,0.00001883009,0.2903121,0.00003280311,0.0003175257,0.000004798521,0.000002920033,0.00001521216,0.000268712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8111956,"threshold_uncertainty_score":0.9995165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2029049650","doi":"10.1016/j.ejor.2007.01.054","title":"Solving circle packing problems by global optimization: Numerical results and industrial applications","year":2007,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":215,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Circle packing; Rectangle; Packing problems; Container (type theory); Heuristic; Mathematical optimization; Global optimization; Computer science; Set packing; Work (physics); Mathematics; Combinatorics; Geometry; Engineering; Mechanical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.06645379157372057,"gpt":0.3199350637391034,"spread":0.2534812721653829,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00470585,0.0001019745,0.0001303258,0.0001499778,0.00027724,0.0002870965,0.0002159327,0.00004637316,0.00006118492],"category_scores_gemma":[0.0003244874,0.000102968,0.00003383751,0.0005745713,0.00008153556,0.0003050133,0.00005479967,0.0005192223,0.00002102287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211658,"about_ca_system_score_gemma":0.00008695381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002327302,"about_ca_topic_score_gemma":0.000001038351,"domain_scores_codex":[0.99801,0.0002532306,0.0006414482,0.0001507244,0.0006534467,0.0002911148],"domain_scores_gemma":[0.9987792,0.0002036818,0.00008551938,0.0001149264,0.0005877474,0.0002289734],"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":[0.00005342534,0.00004683088,0.0005298397,0.00001521403,0.00003633099,0.00001975344,0.0002371219,0.9630729,0.0004923679,0.0003688572,0.01207006,0.02305728],"study_design_scores_gemma":[0.007992225,0.001130622,0.006196234,0.0006140917,0.00004439718,0.0008873016,0.0007144261,0.5665427,0.001595351,0.0002884672,0.4128763,0.001117881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002633886,0.0007559313,0.9606091,0.0008318141,0.0001999654,0.0002949929,0.0000374365,0.00005445159,0.0345824],"genre_scores_gemma":[0.9808667,0.000219447,0.01798541,0.00004933562,0.0006533358,0.000002837054,0.00004216722,0.00003373173,0.0001470456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9782328,"threshold_uncertainty_score":0.4198912,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994948315","doi":"10.1016/j.ejor.2014.03.009","title":"Optimal credit period and lot size for deteriorating items with expiration dates under two-level trade credit financing","year":2014,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":211,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Trade credit; Expiration; Period (music); Business; Finance; Expiration date; Economics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.1076970169518836,"gpt":0.3142374156106111,"spread":0.2065403986587274,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004710227,0.0001451826,0.0001763109,0.0002541662,0.0005799953,0.00115662,0.0002665977,0.00001711235,0.0001358979],"category_scores_gemma":[0.0008733465,0.0001133855,0.00004794621,0.0002061789,0.0001134643,0.001465916,0.0001297223,0.0002548887,0.0000182171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004559559,"about_ca_system_score_gemma":0.00006869308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001096523,"about_ca_topic_score_gemma":0.00001318557,"domain_scores_codex":[0.998139,0.0001616763,0.0004434496,0.000226917,0.0007344182,0.0002945134],"domain_scores_gemma":[0.9987935,0.0002665001,0.0002045691,0.0001255462,0.0005701266,0.00003974923],"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":[0.005912773,0.001504711,0.02521974,0.002283158,0.0009889388,0.0006940222,0.006543778,0.2143559,0.1728459,0.2462527,0.1973124,0.126086],"study_design_scores_gemma":[0.01512944,0.003198101,0.1215163,0.001196801,0.0001576194,0.0002012043,0.009805622,0.3680649,0.001503689,0.001205271,0.4766891,0.001331927],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9151351,0.0001241024,0.06665652,0.008684059,0.0004144654,0.000528054,0.000006515065,0.00002430775,0.008426857],"genre_scores_gemma":[0.984287,0.000006337634,0.009787143,0.0007537836,0.00462532,0.000009583186,0.0000184315,0.00004079566,0.0004716378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2793767,"threshold_uncertainty_score":0.9998803,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090370952","doi":"10.1016/j.ejor.2013.10.002","title":"Fixed cost and resource allocation based on DEA cross-efficiency","year":2013,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":207,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Data envelopment analysis; Resource allocation; Computer science; Maximization; Resource (disambiguation); Mathematical optimization; Operations research; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1909925153001464,"gpt":0.4596566418996745,"spread":0.2686641265995281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.03462287,0.0001250865,0.0002141396,0.001121188,0.0007465977,0.002018041,0.001127154,0.00003028647,0.001346979],"category_scores_gemma":[0.02118918,0.00008470484,0.0001047911,0.001412951,0.0004808734,0.0005859102,0.0001407252,0.000613501,0.001776357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009540554,"about_ca_system_score_gemma":0.0003931981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009422353,"about_ca_topic_score_gemma":0.000001931669,"domain_scores_codex":[0.9895586,0.003616589,0.001068967,0.0003899181,0.005019175,0.0003467086],"domain_scores_gemma":[0.990465,0.003864015,0.0002913938,0.0004569373,0.004629181,0.0002935161],"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":[0.0005673912,0.001342664,0.03376717,0.00001496545,0.00006431171,0.000334808,0.001713714,0.6078541,0.02241053,0.01382808,0.1731395,0.1449628],"study_design_scores_gemma":[0.001901268,0.001636664,0.3908239,0.0001405714,0.00001217926,0.0001022182,0.0006557373,0.4942582,0.001738935,0.001023076,0.1073661,0.0003412147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9095474,0.0002228031,0.02392133,0.01530861,0.0001528915,0.0003804886,0.000007316506,0.00001179085,0.0504474],"genre_scores_gemma":[0.9947005,0.00000624066,0.001674118,0.0006273747,0.0001818989,0.00000283525,0.000004059811,0.00001699586,0.002785959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3570567,"threshold_uncertainty_score":0.9995659,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2016338503","doi":"10.1016/s0377-2217(02)00641-0","title":"Retail promotions with negative brand image effects: Is cooperation possible?","year":2003,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":205,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Promotion (chess); Brand image; Image (mathematics); Revenue; Nash equilibrium; Business; Differential (mechanical device); Advertising; Differential game; Channel (broadcasting); Marketing; Microeconomics; Computer science; Economics; Mathematics; Mathematical optimization; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.05521878976130972,"gpt":0.3122879218777673,"spread":0.2570691321164575,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004607909,0.0001306899,0.0001589955,0.0004430937,0.0006222616,0.00103533,0.0002291229,0.00001795984,0.00157231],"category_scores_gemma":[0.00131215,0.00009568973,0.00005823396,0.0007646577,0.0001406053,0.001821927,0.00005495309,0.0005152182,0.0002650465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003892566,"about_ca_system_score_gemma":0.0002024901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001645237,"about_ca_topic_score_gemma":0.00001369992,"domain_scores_codex":[0.9978287,0.0005311032,0.000372318,0.0001827806,0.0008317607,0.0002533098],"domain_scores_gemma":[0.9969214,0.0002430733,0.0001465112,0.0001470149,0.002502883,0.00003915295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005016079,0.003996193,0.2818967,0.001675011,0.001347147,0.006836479,0.007572231,0.001232048,0.2452306,0.1210265,0.1833777,0.1407932],"study_design_scores_gemma":[0.01845698,0.001980904,0.6614581,0.002152682,0.0004939848,0.001014321,0.002055046,0.003000627,0.023298,0.002083292,0.2822024,0.001803721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8160576,0.0001676602,0.004249925,0.002891593,0.0001995909,0.0004858333,0.000003194161,0.00001997244,0.1759246],"genre_scores_gemma":[0.9951797,0.00001937663,0.001856655,0.0003671476,0.0004454813,0.000004601314,0.000006535461,0.00003337606,0.002087177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3795614,"threshold_uncertainty_score":0.9993404,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2051997331","doi":"10.1016/j.ejor.2006.09.021","title":"A multicriteria facility location model for municipal solid waste management in North Greece","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":205,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Plan (archaeology); Lexicographical order; Minimax; Linear programming; Operations research; Municipal solid waste; Facility location problem; Location model; Integer programming; Regional planning; Business; Computer science; Environmental planning; Urban planning; Geography; Engineering; Mathematics; Mathematical optimization; Civil engineering; Waste management","retraction":null,"screen_n_in":null,"score":{"opus":0.1282017273757428,"gpt":0.3490702394681768,"spread":0.220868512092434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004587493,0.0001291241,0.0001554497,0.0006541616,0.0002458228,0.0002799667,0.0004517658,0.00001600352,0.00009795759],"category_scores_gemma":[0.0002344387,0.0001204485,0.0000752901,0.0006371775,0.00006850804,0.0009090761,0.0001949111,0.0002202729,0.0001838403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000110573,"about_ca_system_score_gemma":0.00004601718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002576523,"about_ca_topic_score_gemma":0.001873675,"domain_scores_codex":[0.9977231,0.0001365992,0.0007857517,0.0002324583,0.000793629,0.0003284652],"domain_scores_gemma":[0.9982666,0.00003127662,0.00008174463,0.0002165785,0.001380684,0.00002311221],"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":[0.0003358499,0.0004428013,0.001426455,0.0002964334,0.00003605233,0.00003482989,0.0002286457,0.9667935,0.0002857503,0.01398584,0.01152002,0.004613775],"study_design_scores_gemma":[0.001375568,0.00003230571,0.02835037,0.00004084151,0.00001302768,0.00000139524,0.0004444473,0.9553767,0.0000166679,0.0004790833,0.01372475,0.0001447777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.948495,0.00008778525,0.03952845,0.00211784,0.0002451157,0.0007729399,0.00001487942,0.00001647808,0.008721459],"genre_scores_gemma":[0.9953343,0.00001892973,0.001891418,0.0002511253,0.0004803571,0.00002193569,0.00009762114,0.00001528316,0.001889004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04683927,"threshold_uncertainty_score":0.4911746,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1966716113","doi":"10.1016/j.ejor.2006.02.019","title":"An exact algorithm for a single-vehicle routing problem with time windows and multiple routes","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Vehicle routing problem; Benchmark (surveying); Computer science; Set (abstract data type); Shortest path problem; Routing (electronic design automation); Mathematical optimization; Path (computing); Algorithm; Euclidean geometry; Mathematics; Theoretical computer science; Graph","retraction":null,"screen_n_in":null,"score":{"opus":0.04058463769978288,"gpt":0.3074463557067402,"spread":0.2668617180069573,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004591458,0.0001249912,0.0001666964,0.0002027403,0.0002631695,0.0003546281,0.0001984542,0.00002471837,0.00002611977],"category_scores_gemma":[0.0002136202,0.0001040357,0.00003385892,0.0002364915,0.00007356752,0.0005160838,0.00002916365,0.0003255263,0.000008615417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008045208,"about_ca_system_score_gemma":0.00007121646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005752064,"about_ca_topic_score_gemma":0.000001979323,"domain_scores_codex":[0.9979326,0.0006426281,0.000428427,0.0001596119,0.0005313529,0.0003053878],"domain_scores_gemma":[0.9983571,0.0005001691,0.00007268193,0.000113907,0.0008238227,0.0001322882],"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":[0.00006902608,0.0001187477,0.001787562,0.0000242445,0.0000465155,0.00005963409,0.0003243655,0.8313988,0.1244668,0.0001525361,0.0005174119,0.04103439],"study_design_scores_gemma":[0.001407016,0.0006896286,0.003518713,0.00008316957,0.000008242731,0.0001600176,0.00006427254,0.9861697,0.006817905,0.00003510032,0.000897545,0.0001486851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2283994,0.0001925163,0.7662514,0.0002437744,0.00004457701,0.0004403027,0.00002262206,0.0000757535,0.004329704],"genre_scores_gemma":[0.58465,0.000003743854,0.4147351,0.00001021389,0.0003741667,0.000002078308,0.00001178066,0.00005246236,0.0001604515],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3562506,"threshold_uncertainty_score":0.4242455,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979114706","doi":"10.1016/j.ejor.2010.06.026","title":"Social responsibility allocation in two-echelon supply chains: Insights from wholesale price contracts","year":2010,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":202,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Corporate social responsibility; Supply chain; Profit (economics); Upstream (networking); Business; Microeconomics; Industrial organization; Social responsibility; Downstream (manufacturing); Economics; Marketing; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.04416915676319654,"gpt":0.3388783040624034,"spread":0.2947091472992068,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01016603,0.0001608494,0.0002218158,0.001029269,0.0004127195,0.0007794812,0.0006955306,0.00003799129,0.000392337],"category_scores_gemma":[0.003533716,0.0001461735,0.00007592147,0.0008848166,0.000167024,0.001858687,0.0003264854,0.001255524,0.0002713127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001959486,"about_ca_system_score_gemma":0.0003060221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003283075,"about_ca_topic_score_gemma":0.000456579,"domain_scores_codex":[0.996426,0.0006774953,0.0007365413,0.0003200568,0.001438411,0.0004014611],"domain_scores_gemma":[0.9968182,0.0004169648,0.0002721137,0.0002537273,0.002195719,0.00004320361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.004523985,0.002773399,0.05605843,0.0002746524,0.0002685882,0.00441951,0.006035406,0.004715037,0.2537021,0.5901248,0.04467459,0.03242952],"study_design_scores_gemma":[0.004318677,0.00007522979,0.7895169,0.0001042118,0.00001845981,0.000008726905,0.003012632,0.006946877,0.000573524,0.009555086,0.1855113,0.0003583628],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634756,0.00007390573,0.0003691049,0.009783209,0.0003026846,0.000416349,0.000002320797,0.00001768,0.02555917],"genre_scores_gemma":[0.994137,0.000007986877,0.0006456038,0.0007536831,0.003576611,0.000007476168,0.00004371226,0.00003823087,0.0007896944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7334585,"threshold_uncertainty_score":0.7516555,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2773971719","doi":"10.1016/j.ejor.2017.11.061","title":"Simulation of intermodal freight transportation systems: a taxonomy","year":2017,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":191,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Taxonomy (biology); Computer science; Container (type theory); Field (mathematics); Operations research; Transport engineering; Traffic management; Transportation planning; Decision support system; Engineering; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.1453678605602083,"gpt":0.3406096048827289,"spread":0.1952417443225206,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001771278,0.00005900419,0.0001227351,0.0001352808,0.0001550871,0.0001603589,0.0002745701,0.00001669668,0.0001604177],"category_scores_gemma":[0.0003233895,0.00005025697,0.00004501957,0.00003339966,0.000085559,0.0002870816,0.00001205658,0.0002520912,0.00001294389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003291457,"about_ca_system_score_gemma":0.000055526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008853414,"about_ca_topic_score_gemma":0.000003628397,"domain_scores_codex":[0.9987873,0.0001426742,0.0004527109,0.00005650579,0.0004517133,0.0001091399],"domain_scores_gemma":[0.9987492,0.0001311549,0.0001238778,0.0001546131,0.0007727341,0.00006844233],"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":[0.0000371737,0.00002867856,0.001456561,0.00007563504,0.00004636502,0.0001269472,0.000172078,0.988177,0.0009202441,0.003107827,0.001831899,0.004019587],"study_design_scores_gemma":[0.001185859,0.0004240457,0.1367834,0.0004037581,0.00002438804,0.00002958019,0.0001834923,0.767987,0.0008528385,0.0001220667,0.09179184,0.0002117806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4486205,0.000853076,0.3967783,0.0003056033,0.001276796,0.0005645176,0.0001093684,0.00002838021,0.1514634],"genre_scores_gemma":[0.9984658,0.00002591986,0.0008558873,0.000002588884,0.0003533818,0.000001505825,0.000009308437,0.00001535562,0.0002702656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5498453,"threshold_uncertainty_score":0.204942,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004480472","doi":"10.1016/j.ejor.2006.12.057","title":"Variable neighborhood search for minimum cost berth allocation","year":2007,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":186,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Variable neighborhood search; Mathematical optimization; Tardiness; Heuristic; Computer science; Minification; Variable (mathematics); Memetic algorithm; Genetic algorithm; Retard; Local search (optimization); Mathematics; Metaheuristic; Job shop scheduling","retraction":null,"screen_n_in":null,"score":{"opus":0.08025433142720256,"gpt":0.3410985650891733,"spread":0.2608442336619707,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009044541,0.00008284587,0.00011581,0.0002409643,0.0001763623,0.0001443766,0.0002533799,0.00002587863,0.0003750756],"category_scores_gemma":[0.0004518628,0.00007321869,0.00004492331,0.0002246423,0.000058659,0.0001706791,0.00003508053,0.0004234777,0.00004455927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009662053,"about_ca_system_score_gemma":0.0001711289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003135377,"about_ca_topic_score_gemma":0.000002410484,"domain_scores_codex":[0.9982568,0.0001560179,0.0004648773,0.00009525317,0.0006754652,0.0003516038],"domain_scores_gemma":[0.9977747,0.0005036271,0.00003147622,0.0001171481,0.001384505,0.0001885212],"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":[0.0007722345,0.0005716011,0.002665365,0.0003772526,0.0004107785,0.0006689338,0.001503899,0.2513924,0.04735959,0.3213732,0.2076347,0.1652701],"study_design_scores_gemma":[0.003880863,0.001712884,0.02526185,0.0002432762,0.0000402711,0.0004155033,0.0006856496,0.163214,0.01368987,0.001668037,0.7885543,0.0006334941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00802187,0.0003279737,0.8273253,0.0005847038,0.0004027805,0.0003599384,0.00002515182,0.00002129393,0.162931],"genre_scores_gemma":[0.9794556,0.00005799473,0.01762636,0.00006112996,0.001084855,0.000002401001,0.00003207946,0.00004082259,0.001638731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9714338,"threshold_uncertainty_score":0.4106815,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2482679439","doi":"10.1016/j.ejor.2016.07.031","title":"When to introduce an online channel, and offer money back guarantees and personalized pricing?","year":2016,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":186,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Channel (broadcasting); Order (exchange); Product (mathematics); Business; Dual (grammatical number); Selection (genetic algorithm); Microeconomics; Computer science; Industrial organization; Marketing; Economics; Telecommunications; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.1063444822412994,"gpt":0.3308322412738877,"spread":0.2244877590325883,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003735092,0.0001145274,0.0001668791,0.0004428889,0.0002362928,0.0004565933,0.0002311704,0.00001512707,0.0006567448],"category_scores_gemma":[0.0007161617,0.00007403122,0.00002902518,0.0001917203,0.0001178613,0.001095133,0.0002475368,0.0002160008,0.00008809783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001977225,"about_ca_system_score_gemma":0.00004506777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003623887,"about_ca_topic_score_gemma":0.00002146496,"domain_scores_codex":[0.9984063,0.0002336178,0.0003216527,0.0002206207,0.0005814541,0.0002363904],"domain_scores_gemma":[0.9986715,0.0001419263,0.0000793746,0.0001222795,0.000916011,0.00006891367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004219302,0.0008766043,0.1386752,0.000300399,0.0002401423,0.0006950998,0.004604226,0.00004066122,0.2736339,0.01085455,0.07157753,0.4942824],"study_design_scores_gemma":[0.004191022,0.0005304762,0.7664275,0.0006736846,0.00006169931,0.0002079498,0.0009759198,0.00108797,0.0002794092,0.0005558074,0.2245106,0.0004980088],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844447,0.0002955529,0.0005437601,0.01275427,0.00009803514,0.0001427945,0.000005007785,0.000007162205,0.001708664],"genre_scores_gemma":[0.9947794,0.0001022419,0.001047368,0.0008009696,0.001556864,9.86799e-7,0.000004202323,0.00002804774,0.001679939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6277523,"threshold_uncertainty_score":0.7190894,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046989465","doi":"10.1016/j.ejor.2012.03.038","title":"Allocation of information granularity in optimization and decision-making models: Towards building the foundations of Granular Computing","year":2012,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":184,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Granularity; Granular computing; Computer science; Rough set; Set (abstract data type); Theoretical computer science; Suite; Information processing; Data mining; Mathematical optimization; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.0866097097615769,"gpt":0.3643384741984717,"spread":0.2777287644368948,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009403766,0.00006005048,0.000122839,0.0003815731,0.0002132464,0.0001715909,0.0004850242,0.00001817582,0.000004887662],"category_scores_gemma":[0.0007365072,0.00004239794,0.00003588957,0.0005683462,0.00009013753,0.002398548,0.000215345,0.0002526229,9.294787e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004567595,"about_ca_system_score_gemma":0.0001423489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001283169,"about_ca_topic_score_gemma":0.000001060366,"domain_scores_codex":[0.9976951,0.0005998636,0.0006608726,0.0000699768,0.0008165842,0.0001575516],"domain_scores_gemma":[0.9980835,0.0004490414,0.0002572082,0.0001525895,0.001008825,0.00004888423],"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":[0.00002491036,0.00007151435,0.001097838,0.00001768477,0.000009891409,0.000001635698,0.003738055,0.7623231,0.0001700335,0.09498985,0.00004550652,0.13751],"study_design_scores_gemma":[0.0003127911,0.0000945513,0.02889908,0.0001299203,0.00000306168,0.00003467171,0.0001972203,0.96523,0.00007177455,0.004877047,0.00009950635,0.00005040119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1064211,0.0002104112,0.8914877,0.0004619408,0.00008118472,0.0001090082,0.000001196196,0.000002478032,0.00122501],"genre_scores_gemma":[0.7176905,0.0000727014,0.2821588,0.00002903865,0.00004372858,3.860031e-7,0.000001784576,0.000002778885,3.146602e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6112695,"threshold_uncertainty_score":0.3259176,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1995986371","doi":"10.1016/j.ejor.2004.01.039","title":"A simple method for computation of fuzzy linear regression","year":2004,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":171,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; University of Saskatchewan","funders":"","keywords":"Simple (philosophy); Fuzzy logic; Computation; Variable (mathematics); Simple linear regression; Mathematics; Computer science; Mathematical optimization; Regression; Regression analysis; Algorithm; Artificial intelligence; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.2072447309299977,"gpt":0.4825660956785808,"spread":0.275321364748583,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007682914,0.00007613623,0.0002025813,0.000248812,0.000167733,0.00004559133,0.0001816025,0.00002522519,0.00002030258],"category_scores_gemma":[0.002417158,0.00005555793,0.00009873261,0.0002326145,0.00004103573,0.0001926134,0.00004163248,0.0002128375,0.000005874409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007458845,"about_ca_system_score_gemma":0.0002703515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006292018,"about_ca_topic_score_gemma":0.000002142703,"domain_scores_codex":[0.9974392,0.0008151775,0.0006869562,0.0001076457,0.0008028201,0.0001481798],"domain_scores_gemma":[0.9963886,0.0006246252,0.0002934598,0.0001011335,0.002510007,0.00008215501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001539024,0.001230158,0.0002387226,0.0009766902,0.0002841653,0.0001434536,0.00678017,0.5739457,0.06434629,0.2893008,0.04274091,0.01847387],"study_design_scores_gemma":[0.03089882,0.01315722,0.005620651,0.005620399,0.0001829184,0.0009365764,0.005333279,0.2193569,0.07389499,0.6155909,0.02821811,0.001189245],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06348936,0.0001291503,0.9319579,0.0009616239,0.0001249814,0.0003839544,0.00002058987,0.000007318962,0.00292514],"genre_scores_gemma":[0.5518603,0.00001344951,0.4475078,0.00001997895,0.0003803131,0.000002094435,0.00001190112,0.00002538456,0.0001788032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.488371,"threshold_uncertainty_score":0.2893738,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2071327538","doi":"10.1016/s0377-2217(99)00274-x","title":"On the single-assignment p-hub center problem","year":2000,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":168,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Center (category theory); Computer science; Basis (linear algebra); Mathematical optimization; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1222070768181107,"gpt":0.3048564898713042,"spread":0.1826494130531935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004869879,0.00009295376,0.00008235325,0.000205311,0.0003502837,0.0004756998,0.0004795333,0.000009287898,0.01501001],"category_scores_gemma":[0.0002246444,0.00005781454,0.00007125874,0.0003269836,0.00007867657,0.0004908847,0.00008631007,0.0003237709,0.005045709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006302055,"about_ca_system_score_gemma":0.00003048915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001776259,"about_ca_topic_score_gemma":0.000009538967,"domain_scores_codex":[0.9977631,0.0002575428,0.0004171073,0.0001390409,0.001191986,0.0002312329],"domain_scores_gemma":[0.9991217,0.0000627164,0.0000432264,0.0001810209,0.000568371,0.00002291088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003863541,0.001235895,0.0003401283,0.00005516653,0.000101865,0.0001072871,0.0002676705,0.02492322,0.001042415,0.213738,0.6835029,0.07429914],"study_design_scores_gemma":[0.0006077159,0.0001447848,0.004915562,0.00008480882,0.000006279996,0.000007072596,0.0001845328,0.002116491,0.00004857041,0.001132818,0.990638,0.0001133201],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.310053,0.00004688727,0.0003556721,0.04922286,0.0002448704,0.0003464225,0.000002175643,0.00001583331,0.6397123],"genre_scores_gemma":[0.9876984,0.00002810648,0.0001067813,0.003297929,0.0007998793,0.000003910099,0.000007208012,0.00001609632,0.008041627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6776455,"threshold_uncertainty_score":0.995729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1998833643","doi":"10.1016/j.ejor.2007.10.057","title":"Service network design with management and coordination of multiple fleets","year":2007,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":167,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Natural Sciences and Engineering Research Council; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd","keywords":"Fleet management; Computer science; Service (business); Network planning and design; Throughput; Synchronization (alternating current); Operations research; Flow network; Service system; Computer network; Business; Mathematical optimization; Telecommunications; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.07081002622745247,"gpt":0.2960951960183646,"spread":0.2252851697909122,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004141732,0.00005029665,0.00007542517,0.0001136492,0.00006893941,0.00003892969,0.00009561457,0.000009126536,0.00004996695],"category_scores_gemma":[0.00005412915,0.00003927186,0.000009595838,0.0001839183,0.00003661701,0.00008624751,0.00002944292,0.0001718399,0.000004081299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002245532,"about_ca_system_score_gemma":0.00001805489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002613772,"about_ca_topic_score_gemma":0.000007061947,"domain_scores_codex":[0.9990051,0.0001325819,0.0002497401,0.00005081667,0.0004189424,0.0001427727],"domain_scores_gemma":[0.9990952,0.0001978834,0.00003455511,0.00005721611,0.0005439365,0.00007120181],"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":[0.0003325836,0.00007172602,0.003898767,0.0001678108,0.0001602945,0.0007106013,0.0003693991,0.9338971,0.001303241,0.004792506,0.02071226,0.03358373],"study_design_scores_gemma":[0.005647397,0.002224769,0.5582783,0.0009277754,0.00007835036,0.0006444966,0.001115356,0.3176532,0.004088138,0.0006674347,0.1080676,0.0006072232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08581064,0.0007017709,0.8650084,0.0003774329,0.0001252792,0.0002735515,0.000003152745,0.0000147189,0.04768506],"genre_scores_gemma":[0.9547527,0.00006775284,0.04472395,0.00002317516,0.000161481,3.596502e-7,0.000002409772,0.00001438386,0.0002537384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8689421,"threshold_uncertainty_score":0.160146,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2075038193","doi":"10.1016/j.ejor.2005.08.027","title":"Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions","year":2006,"lang":"en","type":"review","venue":"European Journal of Operational Research","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":167,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Operations research; New product development; Product (mathematics); Resource (disambiguation); Cellular manufacturing; Product mix; Resource planning; Risk analysis (engineering); Management science; Industrial engineering; Operations management; Economics; Business; Environmental resource management; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.08361112438579654,"gpt":0.3795534717682478,"spread":0.2959423473824513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001600382,0.0002306578,0.0006640799,0.0004272664,0.0001526387,0.0001359675,0.0001636138,0.00006112229,0.00002337102],"category_scores_gemma":[0.0001380004,0.000183759,0.00007010178,0.0001634101,0.00007426576,0.0001505695,0.00006300246,0.0011164,0.00000525223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001166756,"about_ca_system_score_gemma":0.00006463586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003415491,"about_ca_topic_score_gemma":0.000002068131,"domain_scores_codex":[0.9980644,0.0005673103,0.0006502537,0.0001903678,0.0003048333,0.0002228377],"domain_scores_gemma":[0.9993878,0.0001395869,0.0001034837,0.0001226414,0.0001442695,0.0001022177],"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":[0.00000993917,0.00007269502,0.000004529481,0.02973324,0.0001702049,0.0009359632,0.0003811162,0.1493596,0.000004397692,0.0001092871,0.004560919,0.814658],"study_design_scores_gemma":[0.0001691567,0.0000409822,0.00004951615,0.007807077,0.00006366701,0.0001872509,0.00002558562,0.0006016477,0.000002867373,0.000007740793,0.9908738,0.0001707193],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001073015,0.9970225,0.001840617,0.0001418394,0.0001171966,0.000260102,0.00001666461,0.00001716621,0.0005731669],"genre_scores_gemma":[0.00008373052,0.9923383,0.006589566,0.000009533987,0.0005570353,0.000006876472,0.00005081955,0.00005611577,0.000308039],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9863129,"threshold_uncertainty_score":0.7493473,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103676410","doi":"10.1016/j.ejor.2013.05.024","title":"Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach","year":2013,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Column generation; Vehicle routing problem; Branch and price; Computer science; Mathematical optimization; Column (typography); Operations research; Shortest path problem; Integer programming; Integer (computer science); Set (abstract data type); Routing (electronic design automation); Service (business); Mathematics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.0456891675178521,"gpt":0.283754516223337,"spread":0.2380653487054849,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003197468,0.0001161371,0.0001604425,0.0001768551,0.0003035308,0.0003768909,0.00009381967,0.00003017895,0.00005742997],"category_scores_gemma":[0.0003425337,0.0001002761,0.00001513458,0.0001980217,0.0001298906,0.0005205719,0.00005289943,0.0004081386,0.00001801242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005196168,"about_ca_system_score_gemma":0.00006649751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000547019,"about_ca_topic_score_gemma":4.884592e-7,"domain_scores_codex":[0.9981491,0.0006411482,0.0003351912,0.0001650902,0.0004766422,0.0002328387],"domain_scores_gemma":[0.9989504,0.0002249555,0.00006072562,0.00008146565,0.000511993,0.0001704351],"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":[0.0000641708,0.00006002508,0.0006963745,0.00007294033,0.0001146028,0.00001448937,0.00279916,0.7958131,0.1798453,0.0004375706,0.0015076,0.01857472],"study_design_scores_gemma":[0.0007912965,0.0001924851,0.01577843,0.00005059587,0.000009555417,0.0002339899,0.0001199709,0.9824321,0.0002344125,0.00001618697,0.00002576474,0.0001151747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4494518,0.0003306763,0.5480261,0.0002929287,0.00002189838,0.0002516359,0.000002239981,0.00001912758,0.00160351],"genre_scores_gemma":[0.9443302,0.00003228555,0.05499144,0.00003013895,0.0002433486,0.000004925011,0.000005845319,0.0000394901,0.0003223153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4948784,"threshold_uncertainty_score":0.408914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2094566145","doi":"10.1016/j.ejor.2012.05.029","title":"A diversified Tabu search approach for the open-pit mine production scheduling problem with metal uncertainty","year":2012,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tabu search; Metaheuristic; Guided Local Search; Mathematical optimization; Computer science; Scheduling (production processes); Exploit; Variable neighborhood search; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.162049171885197,"gpt":0.332156140681703,"spread":0.170106968796506,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009158479,0.00009459536,0.000133706,0.0001287111,0.000354572,0.0002475505,0.0005792539,0.00001742217,0.0000616622],"category_scores_gemma":[0.0001282549,0.00005963834,0.00004549563,0.0001809864,0.00008019548,0.0005876078,0.000151823,0.0004797125,0.000009053233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001118093,"about_ca_system_score_gemma":0.00009756361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007396609,"about_ca_topic_score_gemma":0.000001640857,"domain_scores_codex":[0.9986823,0.0002160079,0.0002831795,0.0001159777,0.0003752351,0.0003273178],"domain_scores_gemma":[0.9990101,0.0001457001,0.00004485302,0.0001624384,0.000523604,0.0001132775],"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":[0.0004640262,0.0001502122,0.0006292103,0.00008082322,0.0002824152,0.000005867613,0.00177698,0.9678297,0.004847525,0.005795068,0.01294593,0.005192238],"study_design_scores_gemma":[0.004780506,0.002897824,0.006229665,0.0003677652,0.0001575978,0.001083194,0.007613407,0.8373231,0.01532719,0.000191385,0.1230453,0.0009830437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7048776,0.001249779,0.2613834,0.002032594,0.0003629175,0.002276066,0.00002481979,0.00006467957,0.02772809],"genre_scores_gemma":[0.8648741,0.00007283703,0.1337431,0.00001522919,0.0007309329,0.00002074647,0.00001132558,0.00003475193,0.0004969832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1599965,"threshold_uncertainty_score":0.3174164,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2036016884","doi":"10.1016/j.ejor.2006.03.048","title":"Classifying inputs and outputs in data envelopment analysis","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":161,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Computer science; Aggregate (composite); Constant (computer programming); Returns to scale; Scale (ratio); Econometrics; Mathematical optimization; Operations research; Production (economics); Mathematics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.3869024093103371,"gpt":0.4902033584011331,"spread":0.103300949090796,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05555726,0.00009897932,0.0003172522,0.002988307,0.0002941789,0.0009238725,0.001721896,0.00002106219,0.0002063972],"category_scores_gemma":[0.00634618,0.000070243,0.00008116948,0.004001632,0.0002155813,0.0007312452,0.0006873829,0.0005255947,0.000121892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009211796,"about_ca_system_score_gemma":0.0003499958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003195848,"about_ca_topic_score_gemma":0.0002042838,"domain_scores_codex":[0.9902436,0.00324556,0.001414685,0.0004616859,0.004339537,0.0002949706],"domain_scores_gemma":[0.9958403,0.001701832,0.0002668147,0.0006047885,0.001456886,0.0001293507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002894078,0.001105704,0.6809698,0.00001101391,0.0006593231,0.002972126,0.002595548,0.1292662,0.01316799,0.01135306,0.07328586,0.08432398],"study_design_scores_gemma":[0.000655375,0.00009647808,0.8956953,0.00003826901,0.00004862632,0.00005564439,0.000330759,0.04654443,0.0001991533,0.001069109,0.05510271,0.0001640947],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9417458,0.0009755634,0.02961907,0.01121576,0.0001166973,0.0001028886,0.00001677052,0.000005001746,0.01620243],"genre_scores_gemma":[0.9928163,0.00004481676,0.005261987,0.0001013178,0.000190132,2.848624e-7,0.00001406289,0.000008527517,0.001562585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2147256,"threshold_uncertainty_score":0.9725025,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2074019423","doi":"10.1016/j.ejor.2010.02.022","title":"A general variable neighborhood search for solving the uncapacitated single allocation p-hub median problem","year":2010,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":156,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"Science and Engineering Research Board","keywords":"Variable neighborhood search; Heuristics; Variable (mathematics); Mathematical optimization; PlanetLab; Computer science; Descent (aeronautics); Local search (optimization); Mathematics; Metaheuristic","retraction":null,"screen_n_in":null,"score":{"opus":0.0700874788475297,"gpt":0.332055878703394,"spread":0.2619683998558643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01385108,0.0001206519,0.0001415418,0.000261102,0.0004499519,0.0003984189,0.0005335005,0.00004358191,0.0001767052],"category_scores_gemma":[0.001444752,0.00009075955,0.00006194993,0.0005487254,0.0001169842,0.0003683039,0.00005914099,0.001098673,0.00002120338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009670507,"about_ca_system_score_gemma":0.0003102229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003115999,"about_ca_topic_score_gemma":0.000003970088,"domain_scores_codex":[0.9972634,0.0007830662,0.0005469391,0.000145353,0.0008601708,0.0004010779],"domain_scores_gemma":[0.9965203,0.0008403948,0.0000659669,0.0002110246,0.002194501,0.0001677623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003728985,0.00006205849,0.0001419776,0.00003514013,0.00007016055,0.000009447966,0.001108802,0.466235,0.5070778,0.01353709,0.004023399,0.007661929],"study_design_scores_gemma":[0.001212542,0.0003998302,0.001430868,0.00007959153,0.00001655494,0.000152126,0.0002732698,0.9564787,0.02380239,0.0008387924,0.01508859,0.000226758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1557495,0.0001577635,0.8089276,0.005450806,0.0009589875,0.0008323533,0.00002258813,0.00008763735,0.02781273],"genre_scores_gemma":[0.6901949,0.00001786598,0.3080994,0.00005957862,0.001084064,0.000009623862,0.00001738238,0.0000670511,0.0004500968],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5344453,"threshold_uncertainty_score":0.4800534,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2168381469","doi":"10.1016/s0377-2217(99)00073-9","title":"An efficient transformation of the generalized vehicle routing problem","year":2000,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":155,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"Arc routing; Vehicle routing problem; Transformation (genetics); Computer science; Routing (electronic design automation); Mathematical optimization; Arc (geometry); Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.05034688933492008,"gpt":0.338411005547141,"spread":0.2880641162122209,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006502471,0.00007142254,0.0001092709,0.0001154217,0.0001977293,0.00008491101,0.0003691776,0.00001804502,0.0003398982],"category_scores_gemma":[0.000108838,0.00005138722,0.00006396622,0.0003989721,0.00006148915,0.0002159807,0.00001324919,0.0003775215,0.00001854193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006286961,"about_ca_system_score_gemma":0.00008349666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000214638,"about_ca_topic_score_gemma":4.326673e-7,"domain_scores_codex":[0.9967557,0.00164077,0.0005680163,0.00007002379,0.0007842729,0.0001812002],"domain_scores_gemma":[0.9990954,0.0000933083,0.00005640387,0.0001506547,0.0005256694,0.00007855273],"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":[0.00002363786,0.00003290044,0.0001012052,0.00001187073,0.00001249559,0.000002494666,0.001423151,0.9567255,0.02758731,0.0007289427,0.0001031956,0.01324724],"study_design_scores_gemma":[0.0007344484,0.0001253595,0.007621503,0.00008171414,0.000005866999,0.00003536523,0.0001157433,0.9745666,0.01524973,0.00002764685,0.001357984,0.000078049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591845,0.00007020865,0.02530455,0.0003682657,0.00007002675,0.000152535,0.000004046954,0.00001858323,0.0148273],"genre_scores_gemma":[0.9726346,0.00003066024,0.02702096,0.00002145577,0.0001407286,9.192929e-7,0.000002211031,0.00002561396,0.0001228525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01784103,"threshold_uncertainty_score":0.3721647,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2017259383","doi":"10.1016/s0377-2217(99)00220-9","title":"Using GIS to assess the risks of hazardous materials transport in networks","year":2000,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":154,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Hazardous waste; SAFER; Routing (electronic design automation); Flow network; Computer science; Population; Geographic information system; Risk analysis (engineering); Environmental science; Data mining; Geography; Mathematical optimization; Engineering; Mathematics; Business; Cartography; Computer network; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.6070050088753729,"gpt":0.5414467475301,"spread":0.06555826134527287,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.04050766,0.0000815505,0.0003056981,0.0004887825,0.0002464861,0.0002506388,0.001159341,0.00002245417,0.003995763],"category_scores_gemma":[0.001351482,0.00004617094,0.0001263418,0.001416472,0.0001458377,0.0003057945,0.00005295252,0.0003966404,0.000117284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004337687,"about_ca_system_score_gemma":0.0002528607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009348752,"about_ca_topic_score_gemma":0.00004499438,"domain_scores_codex":[0.9910778,0.004259819,0.001370025,0.0001886268,0.002852529,0.0002511375],"domain_scores_gemma":[0.9970076,0.001063415,0.0001662454,0.0002996149,0.001330655,0.0001324351],"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":[0.0005613908,0.0001020378,0.008420438,0.000001641443,0.00004596973,0.0003134194,0.001224547,0.9277128,0.007750849,0.0003461262,0.001957424,0.05156338],"study_design_scores_gemma":[0.00130967,0.0006661575,0.9346451,0.0002019455,0.00003705968,0.0002211217,0.00184866,0.0247117,0.003551955,0.001817952,0.03071204,0.0002766064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843377,0.0001399355,0.007355443,0.002835049,0.00008702318,0.0001028628,0.00001109674,0.000001096227,0.00512974],"genre_scores_gemma":[0.9966543,0.0002589058,0.001771122,0.00009806818,0.0002831039,5.63351e-7,0.000001309632,0.00001075074,0.0009218482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9262247,"threshold_uncertainty_score":0.9969147,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004102594","doi":"10.1016/j.ejor.2012.02.021","title":"Multi-criteria analysis and the resolution of sustainable development dilemmas: A stakeholder management approach","year":2012,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":153,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Stakeholder; Variety (cybernetics); Sustainable development; Stakeholder analysis; Corporate governance; Business; Process management; Management science; Environmental resource management; Computer science; Economics; Political science; Management","retraction":null,"screen_n_in":null,"score":{"opus":0.09652732781226708,"gpt":0.3090058861997092,"spread":0.2124785583874421,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02152381,0.0001493855,0.0002715114,0.001568164,0.0005346117,0.0004814494,0.0004981901,0.00001771632,0.0001787063],"category_scores_gemma":[0.0004665497,0.0001008762,0.0001035706,0.001713267,0.0002710338,0.001271327,0.0007892215,0.0002884951,0.0000219364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001427431,"about_ca_system_score_gemma":0.00005585796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005733633,"about_ca_topic_score_gemma":0.000002861944,"domain_scores_codex":[0.996693,0.0005973528,0.0007051478,0.0001879479,0.001267365,0.0005492056],"domain_scores_gemma":[0.9977561,0.0001318877,0.0002968959,0.0002468679,0.0015255,0.00004271613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.003059553,0.002958197,0.04492925,0.003071518,0.006820106,0.0007401967,0.01185567,0.01690757,0.0004344255,0.8565546,0.03853051,0.01413842],"study_design_scores_gemma":[0.008520045,0.00006661432,0.5411773,0.0001116132,0.0008103373,0.00002223686,0.06934267,0.02444224,0.00007323437,0.0004424228,0.3545004,0.0004909358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6903294,0.002925064,0.1794128,0.00533405,0.0003428491,0.003138479,0.000003550788,0.00004253522,0.1184713],"genre_scores_gemma":[0.9796919,0.00003654971,0.01593219,0.0001854697,0.0004999715,0.00002059695,0.00001746124,0.00002523151,0.003590626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8561122,"threshold_uncertainty_score":0.7459767,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052997156","doi":"10.1016/j.ejor.2014.04.013","title":"The static bicycle relocation problem with demand intervals","year":2014,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"University of Southampton","keywords":"Mathematical optimization; Bounding overwatch; Relocation; Vehicle routing problem; Travelling salesman problem; Context (archaeology); Branch and cut; Computer science; Integer programming; Routing (electronic design automation); Traveling purchaser problem; Facility location problem; Node (physics); Mathematics; 2-opt; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04100789879994455,"gpt":0.3139234970845028,"spread":0.2729155982845583,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004272654,0.00005404184,0.00006287363,0.0001164798,0.0002392986,0.0001461011,0.0001854903,0.000007861818,0.00003688136],"category_scores_gemma":[0.0001837408,0.00003315061,0.00002034791,0.0002709999,0.00008856048,0.0001951809,0.000006891455,0.0002987284,0.00004676083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003634804,"about_ca_system_score_gemma":0.00007389922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001098541,"about_ca_topic_score_gemma":0.00001319143,"domain_scores_codex":[0.9986015,0.000354108,0.0003650741,0.00005690072,0.0004892091,0.0001331839],"domain_scores_gemma":[0.998614,0.0002622494,0.00004062201,0.0001091515,0.0009139769,0.00006006953],"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":[0.0003242747,0.0002321405,0.00487716,0.0001829073,0.0003923725,0.00005151576,0.005953986,0.6957147,0.02691796,0.09595084,0.07099526,0.09840693],"study_design_scores_gemma":[0.003384797,0.002225035,0.4565387,0.0005438881,0.00004166021,0.0001981939,0.001783899,0.07260064,0.006500829,0.00261969,0.4530821,0.0004805913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7375651,0.0001681326,0.2207757,0.006973505,0.0001666769,0.0003258253,0.000005406614,0.00004485933,0.03397474],"genre_scores_gemma":[0.9959885,0.00004195149,0.003439187,0.00005180898,0.0001061853,0.000004272273,0.000006098347,0.0000174923,0.0003445036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.623114,"threshold_uncertainty_score":0.1840515,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2964487007","doi":"10.1016/j.ejor.2019.07.049","title":"Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics","year":2019,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Österreichische Forschungsförderungsgesellschaft","keywords":"Vehicle routing problem; Computer science; Operations research; Synchronization (alternating current); City logistics; Routing (electronic design automation); Business; Mathematical optimization; Transport engineering; Computer network; Mathematics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03837452215620379,"gpt":0.3206628979252961,"spread":0.2822883757690923,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004611081,0.0001354643,0.0002335735,0.0004733129,0.0001066466,0.0001293706,0.000174272,0.000039499,0.00002535887],"category_scores_gemma":[0.0005203895,0.0001248751,0.00002601908,0.0007778958,0.0001007968,0.0004878591,0.000063885,0.0005987993,0.000006492311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002467501,"about_ca_system_score_gemma":0.0001764182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001494869,"about_ca_topic_score_gemma":0.0000055126,"domain_scores_codex":[0.9973022,0.0009965926,0.0006176559,0.0001854051,0.0006295395,0.0002686498],"domain_scores_gemma":[0.9981182,0.000322831,0.0001706179,0.0001299626,0.001164553,0.00009382071],"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":[0.00006686402,0.00004875379,0.02627838,0.00006066662,0.00003040179,0.00002151339,0.00143678,0.9598897,0.0101985,0.0001877232,0.00001153752,0.001769222],"study_design_scores_gemma":[0.001905369,0.0002765498,0.01105194,0.0003306163,0.000008823462,0.00003122728,0.000459596,0.984259,0.001527768,0.000004190088,0.00001479156,0.0001300954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3608261,0.000156184,0.63707,0.00006140689,0.00005438183,0.0002945456,0.00000344749,0.00002112578,0.001512765],"genre_scores_gemma":[0.7739227,0.00004613928,0.2258558,0.000008120157,0.00005723432,0.000001227017,0.00000600198,0.00004679981,0.0000560137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4130965,"threshold_uncertainty_score":0.509226,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2036909357","doi":"10.1016/j.ejor.2006.03.053","title":"An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":148,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; University of Regina","funders":"","keywords":"Linearization; Mathematical optimization; Fuzzy logic; Interval (graph theory); Nonlinear programming; Nonlinear system; Computer science; Optimization problem; Fuzzy set; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.07461369782545231,"gpt":0.3359253354396741,"spread":0.2613116376142218,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002663223,0.0001290044,0.0001407665,0.0003134795,0.00015993,0.0003271007,0.0003220465,0.000023779,0.00008532833],"category_scores_gemma":[0.00002029736,0.00009650885,0.00008074938,0.000118424,0.00004381391,0.0004799363,0.00005891777,0.0001982917,0.00001955675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001155141,"about_ca_system_score_gemma":0.00001257734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004369452,"about_ca_topic_score_gemma":0.000005807507,"domain_scores_codex":[0.9980603,0.0003375374,0.0005627726,0.0001580299,0.0005942959,0.0002869936],"domain_scores_gemma":[0.9991194,0.00004570954,0.00004648524,0.0001744009,0.0005338393,0.000080175],"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":[0.0000925194,0.00009209655,0.00003740715,0.0000433254,0.0000540555,0.000008391574,0.000164263,0.9946091,0.0003899664,0.001747111,0.002077828,0.0006839352],"study_design_scores_gemma":[0.0007702204,0.000129433,0.0003328942,0.00002621736,0.00001413658,0.000002366991,0.00009448148,0.9966053,0.0002617983,0.0005323648,0.001106039,0.0001247525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.100275,0.00002896969,0.8920385,0.0002284966,0.00009244673,0.0002989781,0.00001392159,0.00003446095,0.006989255],"genre_scores_gemma":[0.8653046,0.00002798339,0.1317592,0.000056803,0.0004038208,0.00000830372,0.0002781264,0.00005668896,0.002104387],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7650296,"threshold_uncertainty_score":0.3935517,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015646948","doi":"10.1016/j.ejor.2011.11.009","title":"General network design: A unified view of combined location and network design problems","year":2011,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":147,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Facility location problem; Computer science; Network planning and design; Tree network; Service (business); Operations research; Flow network; Star (game theory); Mathematical optimization; Computer network; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.2199906032158702,"gpt":0.3099742105751759,"spread":0.08998360735930577,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01030132,0.0001184666,0.0001912592,0.0002222261,0.0002800013,0.0001498026,0.0003426636,0.00002029143,0.0004682809],"category_scores_gemma":[0.0003103823,0.0001001755,0.00003914041,0.0008977025,0.0001016808,0.0006460214,0.0001588863,0.0002293733,0.0001141636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002575837,"about_ca_system_score_gemma":0.0001080963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008881967,"about_ca_topic_score_gemma":0.00002121816,"domain_scores_codex":[0.9976027,0.0006098868,0.0006786869,0.0001658707,0.0006631595,0.0002797049],"domain_scores_gemma":[0.9975351,0.00006717879,0.0001463226,0.0001623401,0.002051305,0.00003775341],"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":[0.0006522106,0.00026525,0.0009759741,0.0002752025,0.0001372801,0.00002619334,0.0003970663,0.8424795,0.0004209359,0.08630833,0.06058881,0.007473261],"study_design_scores_gemma":[0.00605153,0.001815606,0.1733582,0.001473569,0.0001970481,0.00004152536,0.0005856517,0.6932698,0.0002568401,0.02021159,0.1016919,0.00104674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0441497,0.00194963,0.9249701,0.004528949,0.0009248375,0.001813739,0.000001221422,0.00004323428,0.02161857],"genre_scores_gemma":[0.9719613,0.0002991783,0.02519603,0.0006286678,0.001185188,0.00000893772,0.0000112747,0.00002844419,0.0006810141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9278116,"threshold_uncertainty_score":0.5127348,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975192801","doi":"10.1016/j.ejor.2008.06.032","title":"Bargaining in competing supply chains with uncertainty","year":2008,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":143,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stackelberg competition; Supply chain; Microeconomics; Bargaining problem; Competition (biology); Economics; Nash equilibrium; Mathematical economics; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.1046317168021848,"gpt":0.3038569881112279,"spread":0.1992252713090432,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005576288,0.0001123065,0.0001630198,0.000770012,0.000381552,0.0002261671,0.0004061253,0.0000118278,0.0006852586],"category_scores_gemma":[0.0004111619,0.00008633629,0.00004746506,0.0006473251,0.0001534397,0.000850393,0.0001714943,0.00049883,0.0001964425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009115275,"about_ca_system_score_gemma":0.0001172963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006070071,"about_ca_topic_score_gemma":0.00003691029,"domain_scores_codex":[0.997718,0.0002466046,0.0004471735,0.0001659758,0.001088019,0.0003341952],"domain_scores_gemma":[0.9988269,0.0001187302,0.0001398728,0.0001242349,0.000759061,0.000031198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001729745,0.001145623,0.5117105,0.000183754,0.0002350283,0.01487991,0.004337898,0.12964,0.002645111,0.2209833,0.1000342,0.01247493],"study_design_scores_gemma":[0.008184542,0.0006727147,0.4796535,0.001021683,0.00002048074,0.0003950576,0.009181285,0.05018914,0.00009651856,0.0005179396,0.4493143,0.0007528085],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7894657,0.0001080714,0.0003833339,0.002459691,0.0001219423,0.0001816606,7.739865e-7,0.00001357463,0.2072652],"genre_scores_gemma":[0.9962495,0.00002807751,0.000571044,0.000933108,0.001379979,0.000002310134,0.00001003628,0.00002756303,0.000798362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3492801,"threshold_uncertainty_score":0.7503101,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1965776203","doi":"10.1016/j.ejor.2008.10.037","title":"Incorporating congestion in preventive healthcare facility network design","year":2008,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":140,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; McGill University; University of British Columbia","funders":"National Cancer Institute; Public Health Agency","keywords":"Heuristics; Computer science; Facility location problem; Health care; Context (archaeology); Workload; Operations research; Population; Network planning and design; Queueing theory; Operations management; Engineering; Computer network; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.218172015007648,"gpt":0.3461847430738333,"spread":0.1280127280661853,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01106408,0.000096779,0.0001485659,0.0003675091,0.0004209748,0.0001193803,0.0002891055,0.00001851008,0.0002577729],"category_scores_gemma":[0.001012892,0.00008808652,0.00005102574,0.0007534471,0.0001083437,0.0009790849,0.0001362105,0.0004525638,0.0004015807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073303,"about_ca_system_score_gemma":0.0001740046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001910629,"about_ca_topic_score_gemma":0.0001315876,"domain_scores_codex":[0.997197,0.000816461,0.0006692279,0.0001774404,0.0008756777,0.0002642421],"domain_scores_gemma":[0.9982507,0.00008064865,0.0001072147,0.0001282699,0.001402777,0.0000304101],"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":[0.0006896498,0.0004955385,0.06287808,0.0002134337,0.00006382821,0.00063499,0.0008281498,0.8252796,0.0003221336,0.0313989,0.0626509,0.01454478],"study_design_scores_gemma":[0.002611252,0.000378365,0.8848425,0.0003984192,0.00001400096,0.00006655043,0.001207615,0.05945087,0.00004282254,0.003771804,0.04673144,0.00048435],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172086,0.0006503224,0.04639062,0.01804577,0.0009377559,0.001182594,0.000005800357,0.00004251115,0.01553603],"genre_scores_gemma":[0.9965162,0.00005327652,0.001836462,0.0004008019,0.0007407312,0.000004882163,0.00001848768,0.000009249326,0.0004199473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8219644,"threshold_uncertainty_score":0.5161641,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2022679355","doi":"10.1016/j.ejor.2010.08.025","title":"A bargaining game model for measuring performance of two-stage network structures","year":2010,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":140,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Worcester Polytechnic Institute","keywords":"Data envelopment analysis; Bargaining problem; Measure (data warehouse); Stage (stratigraphy); Computer science; Nash equilibrium; Game theory; Efficiency; Process (computing); Mathematical optimization; Economics; Black box; Mathematical economics; Econometrics; Mathematics; Statistics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.3824778200704557,"gpt":0.4825757472755606,"spread":0.100097927205105,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0248262,0.00007513927,0.0001674412,0.0002584304,0.0004673937,0.0001982854,0.0008839964,0.00001874944,0.0003765043],"category_scores_gemma":[0.003652931,0.00005362775,0.0001015817,0.0004277106,0.0002166022,0.0004378899,0.0001120502,0.0006107613,0.00003258717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001546653,"about_ca_system_score_gemma":0.0003190691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.558647e-7,"about_ca_topic_score_gemma":0.000002184581,"domain_scores_codex":[0.9965113,0.000596528,0.0008065628,0.0001792517,0.001678728,0.0002276639],"domain_scores_gemma":[0.9952198,0.001234841,0.0003097657,0.0002748394,0.002823209,0.000137576],"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":[0.0002433449,0.00003309763,0.0009304256,0.000003784148,0.0000189462,0.000002932823,0.0006426248,0.7113856,0.03907015,0.2350095,0.002101271,0.01055828],"study_design_scores_gemma":[0.001356335,0.0004131646,0.008887329,0.00004790657,0.000008576255,0.00008736987,0.0004573125,0.8666508,0.00874466,0.09699934,0.01616738,0.000179895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8368506,0.00004068865,0.1544634,0.000382975,0.0001511561,0.0001480889,0.00001382547,0.000004011463,0.007945241],"genre_scores_gemma":[0.97223,0.000007478333,0.02464036,0.00004824334,0.0007244445,0.000003457416,0.000001452116,0.0000140313,0.002330532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1552651,"threshold_uncertainty_score":0.8604315,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}