{"meta":{"query_hash":"a5dc42673ba5","filters":{"venue":"Annals of Operations Research"},"cohort_total":352,"direct_labels_cover":0,"predictions_cover":352,"exported":352,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/a5dc42673ba5","api":"https://metacan.xera.ac/api/v1/cohort?venue=Annals+of+Operations+Research"},"results":[{"id":"W101737918","doi":"10.1023/a:1026115027615","title":"Aggregation and Surrogation Error in the p-Median Model","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Theory of computation; Algorithm","score_opus":0.36250419437538056,"score_gpt":0.43087589796570797,"score_spread":0.0683717035903274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W101737918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9568507,0.000105454514,0.00088880013,0.02449413,0.000045901987,0.00052157114,0.000002034756,0.0000111321015,0.017080247],"genre_scores_gemma":[0.998478,0.00009859476,0.00015994946,0.0006967599,0.00003370433,0.00006550967,0.0000250882,0.0000042037555,0.00043817516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904007,0.000074668926,0.00020486982,0.00013867186,0.00037600877,0.00016569706],"domain_scores_gemma":[0.99931556,0.000024681307,0.000009495596,0.00019160754,0.00045141368,0.0000072138423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027723522,0.00005352638,0.000061685234,0.0003653799,0.00022262163,0.00014160351,0.00013391259,0.000027259655,0.00010457535],"category_scores_gemma":[0.00064107997,0.000042292693,0.000018243458,0.00076495233,0.00007753932,0.000694457,0.00003313789,0.00010695926,0.00006204676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013786972,0.00025149336,0.003183905,0.00013355866,0.000010506851,0.0000010730647,0.0014230745,0.17485727,0.00023243726,0.8038079,0.008148932,0.007936015],"study_design_scores_gemma":[0.00023521011,0.000013060664,0.008721508,0.000021297972,0.0000035064227,3.1633246e-7,0.0030533224,0.9685885,0.00022668457,0.010329549,0.008712785,0.000094277726],"about_ca_topic_score_codex":0.0014933436,"about_ca_topic_score_gemma":0.0063890847,"teacher_disagreement_score":0.7937312,"about_ca_system_score_codex":0.000006306381,"about_ca_system_score_gemma":0.0000309464,"threshold_uncertainty_score":0.35652593},"labels":[],"label_agreement":null},{"id":"W104314163","doi":"10.1023/a:1020759332183","title":"Minmax p-Traveling Salesmen Location Problems on a Tree","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Theory of computation; Order (exchange); Time complexity; Mathematics; Combinatorics; Mathematical optimization; Computer science; Tree (set theory); Algorithm","score_opus":0.31706850734061026,"score_gpt":0.4308538352548084,"score_spread":0.11378532791419815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W104314163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6126227,0.0023276377,0.18642215,0.008453355,0.0003229359,0.0021974258,0.000042713422,0.00068653043,0.18692456],"genre_scores_gemma":[0.98167664,0.0004886012,0.015682481,0.000042149502,0.000069343616,0.00006960019,0.000009835118,0.00003281801,0.0019285367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848366,0.00020540763,0.00029757098,0.00016312294,0.00055431575,0.00029590065],"domain_scores_gemma":[0.99841857,0.00016790297,0.000010753546,0.00031406092,0.001014542,0.000074171745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016275024,0.00009112819,0.00012217741,0.00029357141,0.00017701784,0.00007422885,0.0001879121,0.00007625607,0.00026502163],"category_scores_gemma":[0.00061088294,0.000094081915,0.00003181607,0.0008994789,0.00006284735,0.00017068091,0.00002370264,0.00027095363,0.0001723501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021474461,0.000062335544,0.000042032967,0.000050568146,0.00001831699,6.5315385e-7,0.00087996334,0.9753057,0.005289101,0.0011767541,0.0058970507,0.011275407],"study_design_scores_gemma":[0.00013634711,0.000095267074,0.00040829112,0.00007637763,0.0000017711425,0.0000014075899,0.00009826066,0.9787734,0.018764632,0.00004154825,0.0015079384,0.00009476833],"about_ca_topic_score_codex":0.00003022619,"about_ca_topic_score_gemma":0.00004310748,"teacher_disagreement_score":0.36905396,"about_ca_system_score_codex":0.000038903432,"about_ca_system_score_gemma":0.000028463595,"threshold_uncertainty_score":0.38365492},"labels":[],"label_agreement":null},{"id":"W105217302","doi":"10.1023/a:1020901719463","title":"Minisum Location with Closest Euclidean Distances","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; University of Prince Edward Island; McMaster University; HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Facility location problem; Euclidean geometry; Mathematical optimization; 1-center problem; Computer science; Distribution (mathematics); Mathematics; Mathematical economics; Algorithm","score_opus":0.34600776729537713,"score_gpt":0.39895245613588604,"score_spread":0.0529446888405089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W105217302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78920025,0.0007261243,0.0024259433,0.061028007,0.00019967557,0.0010469989,0.000010157108,0.00011459378,0.14524826],"genre_scores_gemma":[0.99336815,0.00017388766,0.00017748965,0.00052018726,0.00017525995,0.000064126325,0.00003850041,0.000010496998,0.0054719164],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861765,0.000032037835,0.00026345198,0.00022500209,0.00059985614,0.00026202164],"domain_scores_gemma":[0.9980724,0.000019907238,0.000016338947,0.00033597974,0.0015387766,0.000016600447],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008235763,0.000088820925,0.000105730476,0.00036629767,0.00037584762,0.00023076507,0.00025686173,0.00003096468,0.0017210792],"category_scores_gemma":[0.00023392438,0.00007402091,0.000028671631,0.0013110342,0.00016376583,0.0009811322,0.000074559524,0.00012253906,0.0010062318],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013358053,0.0020211963,0.009534546,0.0010932256,0.00017136859,0.00001154611,0.0011104873,0.09130819,0.0006390902,0.53307307,0.32106522,0.03983846],"study_design_scores_gemma":[0.000795906,0.00019673185,0.025866086,0.00019889046,0.000028462919,0.0000013027324,0.003972198,0.38521644,0.0011807702,0.0009700375,0.5809971,0.0005760535],"about_ca_topic_score_codex":0.002260274,"about_ca_topic_score_gemma":0.0058704093,"teacher_disagreement_score":0.53210306,"about_ca_system_score_codex":0.000009142439,"about_ca_system_score_gemma":0.000019347279,"threshold_uncertainty_score":0.9997716},"labels":[],"label_agreement":null},{"id":"W107574902","doi":"10.1023/a:1026190322164","title":"Location Among Regions with Varying Norms","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Computer science; Facility location problem; Mathematical optimization; Variation (astronomy); Plane (geometry); Boundary (topology); Line (geometry); Mathematics; Algorithm; Geometry; Physics","score_opus":0.22963071883579314,"score_gpt":0.3838593657387171,"score_spread":0.15422864690292395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W107574902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.807492,0.0002024952,0.013552115,0.0122804055,0.00015522413,0.0011003372,0.0000019307067,0.00009885843,0.16511662],"genre_scores_gemma":[0.9961244,0.000052648666,0.00030457746,0.00038269276,0.000072630406,0.00009128357,0.000028668355,0.000012150337,0.0029309886],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866635,0.00004523914,0.00025248242,0.00022541484,0.00052592217,0.00028457292],"domain_scores_gemma":[0.9977326,0.000018615508,0.000016557,0.00037715008,0.0018358773,0.000019201061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013347344,0.000089483234,0.00010317645,0.00050231075,0.0004952343,0.00019276554,0.00019881669,0.000034594766,0.0004929935],"category_scores_gemma":[0.000452867,0.00007441941,0.000031399883,0.0017025933,0.00016005045,0.0011950803,0.000055982968,0.00014282505,0.00033817987],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036058897,0.00045883888,0.0094354795,0.00037350736,0.00007446069,0.0000034298535,0.00031371688,0.2224463,0.00037800687,0.74400014,0.021171989,0.001308063],"study_design_scores_gemma":[0.003140078,0.0004045152,0.14447951,0.00093278056,0.00011312576,0.0000072755092,0.010069359,0.4811646,0.011969842,0.014046619,0.33161065,0.0020616567],"about_ca_topic_score_codex":0.004097696,"about_ca_topic_score_gemma":0.0033711789,"teacher_disagreement_score":0.7299535,"about_ca_system_score_codex":0.0000121276635,"about_ca_system_score_gemma":0.00006801734,"threshold_uncertainty_score":0.61945176},"labels":[],"label_agreement":null},{"id":"W109459921","doi":"10.1023/a:1026134121255","title":"A Probabilistic Minimax Location Problem on the Plane","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solver; Theory of computation; Minimax; Computer science; Mathematical optimization; Regular polygon; Software; Applied mathematics; Function (biology); Mathematics; Algorithm; Geometry","score_opus":0.28902068766505673,"score_gpt":0.3925561140424441,"score_spread":0.10353542637738739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W109459921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6394487,0.00016236465,0.0005574719,0.079307795,0.00021196132,0.0028538308,0.000008112066,0.000080464895,0.2773693],"genre_scores_gemma":[0.9951833,0.000028047636,0.000079303085,0.0011480448,0.00007674283,0.00022082381,0.000028731907,0.000008581111,0.0032264076],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986382,0.00009435267,0.0002715139,0.00020566488,0.00054137333,0.00024887847],"domain_scores_gemma":[0.9982688,0.000066879365,0.000014784939,0.0003895798,0.0012482855,0.000011697431],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0025010868,0.000083808554,0.000085280946,0.00027539718,0.00043723834,0.00018967009,0.00025520028,0.000029803065,0.0011381912],"category_scores_gemma":[0.0015207151,0.00005914747,0.00003293851,0.0010989195,0.00012217285,0.00033075685,0.000054453267,0.0001467487,0.0011142945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016225915,0.00026598686,0.00009621229,0.00014095928,0.000017272567,4.4411095e-7,0.000106420164,0.036700282,0.00012197479,0.9138632,0.047882684,0.00078838074],"study_design_scores_gemma":[0.00078141195,0.00027615446,0.009586168,0.00028638061,0.000031785046,0.0000016664344,0.004251079,0.16094339,0.003199055,0.034001607,0.7859957,0.0006455913],"about_ca_topic_score_codex":0.0010995596,"about_ca_topic_score_gemma":0.00116454,"teacher_disagreement_score":0.87986153,"about_ca_system_score_codex":0.00001275126,"about_ca_system_score_gemma":0.00006645654,"threshold_uncertainty_score":0.99977493},"labels":[],"label_agreement":null},{"id":"W1182730838","doi":"10.1007/s10479-015-1969-3","title":"Goal programming model for management accounting and auditing: a new typology","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Typology; Audit; Compromise; Accounting; Computer science; Field (mathematics); Management accounting; Theory of computation; Guideline; Management science; Aggregate (composite); Business; Economics; Sociology; Political science; Mathematics; Algorithm","score_opus":0.3251146592553192,"score_gpt":0.4538097761543216,"score_spread":0.12869511689900243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1182730838","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023938216,0.00039495953,0.96172094,0.0021700782,0.00005231986,0.0011264894,0.0000053621375,0.00014009509,0.010451558],"genre_scores_gemma":[0.70372754,0.00006432742,0.29449776,0.000038206097,0.000051871102,0.00012670862,0.00001134873,0.000020998556,0.0014612193],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992808,0.000016727794,0.00017643595,0.0001025628,0.00016956183,0.00025388476],"domain_scores_gemma":[0.9994015,0.00005332992,0.000007236359,0.00010328682,0.00031878025,0.00011585407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007613829,0.000057314694,0.00009654744,0.00014681452,0.00009557869,0.00009279381,0.00008605721,0.000039806215,0.000007834354],"category_scores_gemma":[0.00026076802,0.00005583333,0.000019908854,0.00018674532,0.000051542727,0.00015266427,0.00005713939,0.00008608386,0.000005798211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015693877,0.00007136279,0.00002526471,0.0003485528,0.000069291724,0.0000012391281,0.001897109,0.7347684,0.00016385353,0.15064907,0.015231176,0.096759014],"study_design_scores_gemma":[0.00021729333,0.000042420997,0.0000038425287,0.000022066153,0.0000038197386,0.0000011305126,0.0006561408,0.9917578,0.00024545376,0.0027179227,0.0042741573,0.000057966605],"about_ca_topic_score_codex":0.000010467253,"about_ca_topic_score_gemma":0.000016980059,"teacher_disagreement_score":0.67978936,"about_ca_system_score_codex":0.0000099808985,"about_ca_system_score_gemma":0.000039840408,"threshold_uncertainty_score":0.22768171},"labels":[],"label_agreement":null},{"id":"W122108692","doi":"10.1023/a:1020767501233","title":"Location of Preventive Health Care Facilities","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":161,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; McGill University","funders":"U.S. Food and Drug Administration","keywords":"Theory of computation; Facility location problem; Health care; Quality (philosophy); Computer science; Preventive care; Operations research; Mathematics; Economic growth; Economics","score_opus":0.2750182544631937,"score_gpt":0.4196383342786208,"score_spread":0.14462007981542707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W122108692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83420146,0.011080653,0.0026074322,0.051018808,0.00038319032,0.0026771573,0.00006361291,0.0001117671,0.09785595],"genre_scores_gemma":[0.99381685,0.00029073216,0.0000914888,0.00023468959,0.00006905884,0.000048144615,0.000046940062,0.0000058128294,0.0053963],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986859,0.000057470836,0.00037305267,0.00016707154,0.00049891707,0.00021757685],"domain_scores_gemma":[0.9968223,0.000014793018,0.000025230227,0.00028550474,0.0028392652,0.00001288853],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00082578947,0.00006919607,0.00013474791,0.00044345862,0.00024992268,0.000058994327,0.00020524544,0.000025683574,0.0012889182],"category_scores_gemma":[0.00033723502,0.000068045956,0.0000428246,0.0010870639,0.00012496414,0.0006186073,0.00010362888,0.000087425564,0.00030348825],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007619741,0.0017672055,0.002354677,0.012258977,0.00022529428,0.0000012107249,0.025414685,0.127308,0.00050559477,0.4373107,0.2969342,0.09584328],"study_design_scores_gemma":[0.0015737094,0.00057299965,0.032146145,0.00092366996,0.00003073113,6.822684e-7,0.12499815,0.30224332,0.005039588,0.0019186233,0.52964556,0.00090684043],"about_ca_topic_score_codex":0.00919828,"about_ca_topic_score_gemma":0.0035675266,"teacher_disagreement_score":0.43539205,"about_ca_system_score_codex":0.000018137476,"about_ca_system_score_gemma":0.000046289057,"threshold_uncertainty_score":0.999624},"labels":[],"label_agreement":null},{"id":"W12382059","doi":"10.1023/a:1026130003508","title":"An Efficient Genetic Algorithm for the p-Median Problem","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":337,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Mathematical optimization; Computer science; Algorithm; Greedy algorithm; Simple (philosophy); Coding (social sciences); Genetic algorithm; Heuristic; Upper and lower bounds; Mathematics","score_opus":0.2023695766391125,"score_gpt":0.414880243875167,"score_spread":0.21251066723605447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W12382059","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3029082,0.0014762142,0.56512684,0.08236072,0.0012595422,0.010871323,0.000074510324,0.00020377537,0.035718855],"genre_scores_gemma":[0.98705894,0.000105155945,0.009645154,0.00084472814,0.00026935173,0.0005380302,0.000042206535,0.000017038174,0.0014793982],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987591,0.000049269962,0.00025065104,0.00020742761,0.0004291285,0.0003044329],"domain_scores_gemma":[0.9982983,0.000042655436,0.000011230559,0.00039094093,0.0012384874,0.00001841107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021417963,0.00007598058,0.000080883336,0.00024723407,0.00062954956,0.00023027004,0.00031973002,0.000028142154,0.00047285482],"category_scores_gemma":[0.00024628825,0.000055875003,0.000051568455,0.0006656569,0.00011036393,0.00024566313,0.00004675583,0.000089722394,0.0001694525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000123139225,0.0007096007,0.00017188072,0.00015787905,0.000062037405,8.191973e-7,0.0003443938,0.64499754,0.00027325554,0.19259086,0.02936873,0.1313107],"study_design_scores_gemma":[0.00016445035,0.00003397513,0.001354481,0.0000074127347,0.000007207519,1.8331312e-7,0.00081128057,0.8947982,0.00027584814,0.0008640887,0.10159892,0.00008395153],"about_ca_topic_score_codex":0.0014686058,"about_ca_topic_score_gemma":0.0008800224,"teacher_disagreement_score":0.6841507,"about_ca_system_score_codex":0.000007686761,"about_ca_system_score_gemma":0.00005582249,"threshold_uncertainty_score":0.5177429},"labels":[],"label_agreement":null},{"id":"W131616201","doi":"10.1023/a:1026183515320","title":"Multi-Service Facility Location Models","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Japan Society for the Promotion of Science","keywords":"Service (business); Variety (cybernetics); Business; Computer science; Scale (ratio); Operations management; Environmental economics; Operations research; Marketing; Geography; Economics; Mathematics; Cartography","score_opus":0.5144915647261461,"score_gpt":0.405426362218811,"score_spread":0.10906520250733509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W131616201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18418983,0.0022362042,0.7860084,0.000584273,0.00014563001,0.00064323813,0.00021562188,0.00017316209,0.025803657],"genre_scores_gemma":[0.9953344,0.0002758923,0.0039176806,0.000034285713,0.000009461404,0.000026731688,0.000046524186,0.000008409195,0.00034664053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991581,0.00006757054,0.00019833799,0.000111942994,0.00024506124,0.00021902642],"domain_scores_gemma":[0.99863094,0.000037126767,0.0000032408393,0.00026829581,0.000990304,0.000070076574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005805488,0.00006572352,0.000091051596,0.000119677265,0.00010530143,0.000027519327,0.0001244281,0.000060559298,0.00011981402],"category_scores_gemma":[0.00009097198,0.000065131746,0.00002252445,0.0005421332,0.00006375381,0.00018662242,0.0000064891888,0.0001832732,0.00009540959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024800886,0.00008636428,0.00013540426,0.0000774107,0.000018406063,0.0000010799276,0.00042984323,0.9814587,0.0031172284,0.013187478,0.0011987003,0.0002868939],"study_design_scores_gemma":[0.00015811845,0.000025599056,0.0009849824,0.000012827585,0.0000025662694,7.976923e-7,0.00014058777,0.9744918,0.019609127,0.0005726985,0.003895752,0.00010517629],"about_ca_topic_score_codex":0.00017605918,"about_ca_topic_score_gemma":0.0005601873,"teacher_disagreement_score":0.81114453,"about_ca_system_score_codex":0.00001312333,"about_ca_system_score_gemma":0.00006780762,"threshold_uncertainty_score":0.26559955},"labels":[],"label_agreement":null},{"id":"W141986059","doi":"10.1023/a:1010917903065","title":"Stability in Linear Programming Models: An Index Set Approach","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Theory of computation; Linear programming; Parametric programming; Mathematical optimization; Stability (learning theory); Applied mathematics; Parametric statistics; Set (abstract data type); Computer science; Algorithm; Statistics","score_opus":0.4544589079224721,"score_gpt":0.47320677683012763,"score_spread":0.018747868907655507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W141986059","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08327162,0.000045817396,0.9107879,0.0034260014,0.0000145519125,0.00031251085,0.0000055857167,0.000033749802,0.0021022523],"genre_scores_gemma":[0.92572093,0.00007717767,0.07381324,0.00007772037,0.000023432944,0.00005734067,0.00004362043,0.0000044556155,0.00018209795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980196,0.00043871722,0.00031210936,0.0003302277,0.0006276844,0.00027167256],"domain_scores_gemma":[0.9980378,0.00006588512,0.000018703782,0.0004990317,0.0012754304,0.00010312568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025509147,0.00006803338,0.00012894961,0.0004624635,0.00019981907,0.00019300009,0.00059736974,0.000055652876,0.00005309318],"category_scores_gemma":[0.00018237179,0.00006236794,0.000041509273,0.0023904655,0.00006808184,0.0014204163,0.00015684767,0.00020429872,0.000007669876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010374975,0.0006481687,0.0037226938,0.000008220189,0.000012504073,0.0000015700535,0.0017850829,0.91288084,0.000037631908,0.076309495,0.000057882713,0.00452552],"study_design_scores_gemma":[0.00011450279,0.000057931415,0.0019543555,0.000003793553,5.89936e-7,0.0000010936058,0.0002934305,0.9957323,0.00009707004,0.0014165518,0.0002635378,0.0000648379],"about_ca_topic_score_codex":0.0009304816,"about_ca_topic_score_gemma":0.00049885124,"teacher_disagreement_score":0.8424493,"about_ca_system_score_codex":0.000020885489,"about_ca_system_score_gemma":0.00022598456,"threshold_uncertainty_score":0.2543291},"labels":[],"label_agreement":null},{"id":"W14474499","doi":"10.1023/a:1020992910050","title":"Recent Developments in the Theory and Applications of Location Models: A Preview","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.36558002536392603,"score_gpt":0.4124520385444206,"score_spread":0.046872013180494554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W14474499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44712546,0.07318389,0.035055112,0.10103086,0.00021548712,0.016187547,0.000029815466,0.00011826267,0.32705358],"genre_scores_gemma":[0.98592883,0.0124890115,0.00010352546,0.00059011596,0.00003090755,0.00038687285,0.00001829867,0.000004419375,0.00044803426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892414,0.00011787839,0.0003280428,0.00014272747,0.0003509868,0.00013621092],"domain_scores_gemma":[0.9988061,0.000049135386,0.000018806886,0.00026111954,0.0008581799,0.0000066635025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033587678,0.00005652274,0.00009132772,0.0003216066,0.00015793323,0.00006109163,0.00024908312,0.000021962796,0.0002547505],"category_scores_gemma":[0.00027920722,0.000043190732,0.00001618372,0.001390053,0.00009499334,0.0004956106,0.00009170597,0.000086045875,0.00006455698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014529272,0.0004426625,0.00029457817,0.0004778272,0.000018966874,1.5765914e-7,0.00097199867,0.012974653,0.00002156766,0.759079,0.004180637,0.22152343],"study_design_scores_gemma":[0.0006927813,0.000052870346,0.02287879,0.00037017802,0.00003205451,0.0000010751409,0.007725616,0.33778903,0.00015513596,0.037938476,0.59198207,0.0003819083],"about_ca_topic_score_codex":0.00035760656,"about_ca_topic_score_gemma":0.00065795926,"teacher_disagreement_score":0.7211405,"about_ca_system_score_codex":0.0000067647916,"about_ca_system_score_gemma":0.000017894663,"threshold_uncertainty_score":0.27893394},"labels":[],"label_agreement":null},{"id":"W1493792108","doi":"10.1023/a:1023370211456","title":"Uncertainty and Investment in Electricity Generation with an Application to the Case of Hydro-Québec","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Electric Power System Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Energy; University of Alberta","funders":"","keywords":"Competition (biology); Restructuring; Theory of computation; Computer science; Operations research; Linear programming; Investment (military); Duration (music); Process (computing); Mathematical optimization; Face (sociological concept); Simple (philosophy); Economics; Mathematics; Finance","score_opus":0.06937511628807928,"score_gpt":0.35677123309641456,"score_spread":0.28739611680833527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493792108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96642816,0.00035308086,0.031052677,0.00040652492,0.000007032286,0.0007644831,0.0000043847567,0.000012079523,0.000971585],"genre_scores_gemma":[0.9985651,0.00006627071,0.0010696352,0.00003814892,0.000011568375,0.00019131484,0.000010593135,0.000009982046,0.000037379526],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909306,0.00023923776,0.00021277503,0.00013045428,0.00016694074,0.0001575326],"domain_scores_gemma":[0.9992781,0.00005399006,0.000011815926,0.00024793026,0.0003538389,0.00005432436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010974307,0.000060929884,0.00009390129,0.00024294693,0.000099977195,0.000028677394,0.00007492744,0.00003364071,0.000004805453],"category_scores_gemma":[0.00013261804,0.000046224497,0.0000074604754,0.0009249546,0.000033518005,0.0001439899,0.000008222484,0.00010535032,0.0000017701303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070629417,0.000046192654,0.00016466323,0.000015514612,0.000010287981,0.000003050177,0.0007683654,0.9813432,0.008242927,0.007704344,0.00021164383,0.0014827546],"study_design_scores_gemma":[0.00012976256,0.00027669314,0.00015998712,0.000009385171,0.0000022719166,0.000037778813,0.00014695265,0.9505844,0.048236925,0.00005379045,0.0002998077,0.00006225749],"about_ca_topic_score_codex":0.0074646883,"about_ca_topic_score_gemma":0.05832695,"teacher_disagreement_score":0.05086226,"about_ca_system_score_codex":0.000055865992,"about_ca_system_score_gemma":0.00014077894,"threshold_uncertainty_score":0.9991447},"labels":[],"label_agreement":null},{"id":"W1502837695","doi":"10.1023/a:1022942825680","title":"An Optimization-Based Approach to the Multiple Static Delivery Technique in Radiation Therapy","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Tekes; Varian Medical Systems","keywords":"Mathematical optimization; Lipschitz continuity; Computer science; Nonlinear programming; Theory of computation; Global optimization; Nonlinear system; Inverse problem; Mathematics; Applied mathematics; Algorithm","score_opus":0.10552793079532134,"score_gpt":0.428280240282475,"score_spread":0.32275230948715367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1502837695","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024229094,0.00010193141,0.97212845,0.00054510334,0.000007907386,0.0015910493,0.000028062244,0.000021843978,0.0013465346],"genre_scores_gemma":[0.8412296,0.0000680868,0.15731649,0.00015581331,0.000025379411,0.0010858327,0.000060399812,0.000018651492,0.000039725826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847573,0.00058228004,0.00022950352,0.00020733838,0.0002669374,0.00023822622],"domain_scores_gemma":[0.9988946,0.00017069699,0.000021721129,0.00041472164,0.00044013275,0.000058140846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012647584,0.00009073686,0.00011522803,0.00030779818,0.00021882525,0.00006721954,0.00025973524,0.000033560325,0.00012359906],"category_scores_gemma":[0.00006890345,0.00007058942,0.000033742854,0.00081687706,0.00006815187,0.0002455981,0.000008749377,0.0001962199,0.000001589619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019136267,0.00042751146,0.0031714828,0.0000025998042,0.000010024641,9.245587e-8,0.0004050094,0.9801373,0.0040757884,0.006125003,0.00031375999,0.005312311],"study_design_scores_gemma":[0.00048191615,0.00031023604,0.0005122056,0.00001655133,9.944806e-7,2.0833659e-7,0.00041798595,0.8054569,0.18734103,0.00048368075,0.004802931,0.00017537863],"about_ca_topic_score_codex":0.00052013405,"about_ca_topic_score_gemma":0.000019453859,"teacher_disagreement_score":0.8170005,"about_ca_system_score_codex":0.000023435741,"about_ca_system_score_gemma":0.00020896559,"threshold_uncertainty_score":0.2878553},"labels":[],"label_agreement":null},{"id":"W1505327332","doi":"10.1023/a:1018925302021","title":"The management of high seas fisheries","year":2000,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fish stock; Exclusive economic zone; Fisheries management; Stock (firearms); Negotiation; Fishery; Fishing; United Nations Convention on the Law of the Sea; Geography; International waters; Herring; Territorial waters; Business; International law; Political science; Fish <Actinopterygii>; Law","score_opus":0.1135251018553638,"score_gpt":0.3874397394850085,"score_spread":0.2739146376296447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1505327332","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45926094,0.000027601807,0.000008235394,0.0074432585,0.000010456094,0.00025681395,0.000007898613,0.000005024391,0.5329798],"genre_scores_gemma":[0.89168775,0.003350896,0.0004886165,0.00005142399,0.00001596025,0.000073045274,0.000007540091,0.000007689163,0.10431707],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99834466,0.00015453466,0.00020582875,0.00015310473,0.00082755496,0.00031432984],"domain_scores_gemma":[0.99931395,0.00008063476,0.000008614073,0.0004380914,0.00009479005,0.000063909465],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001108471,0.000054144355,0.00008272373,0.000031861447,0.0004484512,0.00006821547,0.0004916294,0.000027254953,0.037775908],"category_scores_gemma":[0.000032097934,0.000037431586,0.000036892252,0.0005625743,0.00076906005,0.0001878037,0.00030297445,0.00014566144,0.00025406922],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019490407,0.00030431643,0.010084315,0.000057107096,0.0001097685,0.000012738734,0.0004927715,0.0023596506,0.00039870184,0.018739808,0.086691126,0.8805548],"study_design_scores_gemma":[0.00021249177,0.00031004782,0.0673278,0.0000132428395,0.0000033880008,0.000001627092,0.0006690837,0.0016843135,0.0052265255,0.0018531115,0.92258835,0.00011002414],"about_ca_topic_score_codex":0.0032338856,"about_ca_topic_score_gemma":0.0005223978,"teacher_disagreement_score":0.88044477,"about_ca_system_score_codex":0.000013068841,"about_ca_system_score_gemma":0.00001826599,"threshold_uncertainty_score":0.9631037},"labels":[],"label_agreement":null},{"id":"W151704277","doi":"10.1023/a:1026135632158","title":"Bioenergy Systems Planning Using Location–Allocation and Landscape Ecology Design Principles","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; International Institute for Sustainable Development","funders":"","keywords":"Nexus (standard); Bioenergy; Landscape ecology; Landscape planning; Biomass (ecology); Environmental resource management; Sustainable development; Sustainable energy; Energy planning; Environmental planning; Production (economics); Natural resource economics; Ecology; Geography; Business; Environmental economics; Computer science; Renewable energy; Environmental science; Economics; Habitat","score_opus":0.3659092363170485,"score_gpt":0.41803546647218814,"score_spread":0.05212623015513962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W151704277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.979909,0.00047765463,0.015375552,0.00029222324,0.00003564925,0.00019811404,0.0000013015267,0.000009085104,0.0037014005],"genre_scores_gemma":[0.9967201,0.00021748041,0.0025722343,0.00003806248,0.000014516374,0.000025969804,0.000004618991,0.00000848737,0.00039852792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856937,0.00044076733,0.00018930795,0.00018957035,0.00035136618,0.0002596098],"domain_scores_gemma":[0.9995319,0.00010417833,0.000023806388,0.00018301027,0.0000647472,0.000092304304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018112125,0.000071765244,0.00009324519,0.00010804414,0.00035560533,0.00005353901,0.000101056205,0.0000685008,0.0002025484],"category_scores_gemma":[0.00039467102,0.000065356755,0.000010787591,0.00033204712,0.00021169774,0.00026770367,0.00006188188,0.00009245015,0.00003294686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005214311,0.000051642568,0.008793224,0.000007479179,0.000008831522,0.0000013423164,0.0001954706,0.9750363,0.0093892785,0.006101694,0.00027538845,0.00013408769],"study_design_scores_gemma":[0.00060975103,0.0005914594,0.18157424,0.00014331499,0.00001653077,0.0000666741,0.0018981344,0.74040526,0.061038673,0.00051355624,0.012660475,0.00048194514],"about_ca_topic_score_codex":0.0004094745,"about_ca_topic_score_gemma":0.00006898306,"teacher_disagreement_score":0.23463109,"about_ca_system_score_codex":0.000043008557,"about_ca_system_score_gemma":0.00005626559,"threshold_uncertainty_score":0.27350646},"labels":[],"label_agreement":null},{"id":"W1541052538","doi":"10.1007/s10479-008-0477-0","title":"Malmquist indexes with quasi-fixed inputs: an application to school districts in Québec","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke; Université du Québec à Montréal","funders":"","keywords":"Inefficiency; Productivity; Competitor analysis; Flexibility (engineering); Malmquist index; Generalization; Index (typography); Econometrics; Measure (data warehouse); Economics; Business; Computer science; Microeconomics; Total factor productivity; Mathematics; Marketing; Economic growth","score_opus":0.3357396875096175,"score_gpt":0.5215650930073835,"score_spread":0.185825405497766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1541052538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9716274,0.00007988837,0.015382015,0.011222622,0.00001094792,0.00045577894,0.000017213833,0.00001676185,0.0011873338],"genre_scores_gemma":[0.99681324,0.000027365215,0.0014467866,0.00032951118,0.000043261127,0.000115323994,0.000016306503,0.0000113718625,0.0011968312],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9947785,0.000737913,0.0007444189,0.0006210642,0.002711849,0.00040622594],"domain_scores_gemma":[0.9948222,0.00063485175,0.000060575963,0.0011870104,0.003002178,0.00029315334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005870279,0.000119074226,0.00028813662,0.0018172286,0.000598766,0.00026157062,0.0011693727,0.00007231357,0.0001825554],"category_scores_gemma":[0.006840412,0.00008803917,0.000050688228,0.007260526,0.0004009923,0.0007107724,0.00015522084,0.00031812798,0.00054651225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005160508,0.00435284,0.55446774,0.000017603681,0.000060352522,0.00006976255,0.009816993,0.3495228,0.022487504,0.0091093015,0.0240203,0.02555874],"study_design_scores_gemma":[0.00097569503,0.0027387373,0.7981681,0.000104480285,0.000009700531,0.00003539008,0.0033533894,0.14426072,0.024149537,0.001061936,0.02440323,0.0007390668],"about_ca_topic_score_codex":0.026325272,"about_ca_topic_score_gemma":0.118365176,"teacher_disagreement_score":0.24370034,"about_ca_system_score_codex":0.00007643344,"about_ca_system_score_gemma":0.0012647285,"threshold_uncertainty_score":0.9801585},"labels":[],"label_agreement":null},{"id":"W1552630275","doi":"10.1023/a:1023307319633","title":"An Oligopolistic Investment Model of the Finnish Electricity Market","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Electric Power System Optimization","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Oligopoly; Economics; Microeconomics; Investment (military); Electricity market; Mixed complementarity problem; Production (economics); Stochastic programming; Market power; Complementarity (molecular biology); Industrial organization; Electricity; Mathematical optimization; Cournot competition; Mathematics; Engineering","score_opus":0.12556702748705448,"score_gpt":0.37780454528509755,"score_spread":0.25223751779804304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552630275","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74611694,0.0013952677,0.093455285,0.0005384859,0.00017246,0.0016313222,0.0000890156,0.000109816625,0.1564914],"genre_scores_gemma":[0.9975349,0.00017459894,0.001437196,0.00004586382,0.000010451645,0.000044623535,0.0000043493346,0.00001678867,0.00073123956],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985654,0.00034039625,0.00028018156,0.000114506154,0.0004298906,0.00026964926],"domain_scores_gemma":[0.9988033,0.00007013919,0.0000149621055,0.00045113682,0.00059735694,0.00006311165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011273263,0.00007492432,0.00012490306,0.00019493402,0.00013034519,0.000032652948,0.0002754274,0.00005793477,0.0000670331],"category_scores_gemma":[0.00046718415,0.00006177615,0.000037329784,0.00087442744,0.000067804925,0.00016240007,0.00001683147,0.00017832333,0.0000038232165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027726162,0.00007340722,0.00011496417,0.000036336638,0.000020936552,1.3676582e-7,0.00018079359,0.955979,0.010194805,0.023842005,0.009482115,0.00007276621],"study_design_scores_gemma":[0.00007192756,0.000055185486,0.00025667873,0.00001572469,0.0000028183258,0.0000010848025,0.000020327107,0.8998146,0.098860174,0.000682366,0.00016301834,0.00005606518],"about_ca_topic_score_codex":0.000086918604,"about_ca_topic_score_gemma":0.000056100675,"teacher_disagreement_score":0.25141793,"about_ca_system_score_codex":0.000040014515,"about_ca_system_score_gemma":0.00021118687,"threshold_uncertainty_score":0.2519158},"labels":[],"label_agreement":null},{"id":"W16475425","doi":"10.1023/a:1020933122382","title":"An Eigenvalue Approach to Analyzing a Finite Source Priority Queueing Model","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.23955351761846697,"score_gpt":0.41077361102134624,"score_spread":0.17122009340287928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W16475425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6117095,0.0001943095,0.35712534,0.0024865554,0.000022600729,0.00053759996,0.0000090432995,0.00012768421,0.027787369],"genre_scores_gemma":[0.9885694,0.00003851523,0.007826497,0.000646764,0.00029055582,0.00005467236,0.000021357859,0.00003190436,0.0025203663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799037,0.000119854616,0.0003581315,0.00043510116,0.0006101628,0.00048639963],"domain_scores_gemma":[0.99791795,0.00009317424,0.000045831363,0.00066701544,0.0012237713,0.000052285162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026592754,0.0001438421,0.00024159889,0.001130851,0.00079090375,0.00044383414,0.0005698017,0.00006656977,0.00016293782],"category_scores_gemma":[0.001167768,0.00014320259,0.00010279704,0.0020949112,0.000109304034,0.0018716158,0.00023663245,0.00031887146,0.0002241255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015772272,0.00026902484,0.00028347914,0.000037939553,0.000034013567,0.0000010617468,0.00052737334,0.95891756,0.0026498784,0.031810306,0.0005156077,0.0049379626],"study_design_scores_gemma":[0.00008918422,0.000016882153,0.00005851714,0.000021343238,0.000014434544,2.7299018e-7,0.00041473104,0.99482834,0.0005140654,0.0018380329,0.0020424686,0.00016174169],"about_ca_topic_score_codex":0.00063026446,"about_ca_topic_score_gemma":0.00012379397,"teacher_disagreement_score":0.37685987,"about_ca_system_score_codex":0.000020809193,"about_ca_system_score_gemma":0.000025700705,"threshold_uncertainty_score":0.60830724},"labels":[],"label_agreement":null},{"id":"W170489151","doi":"10.1023/a:1020771702141","title":"Data Surrogation Error in p-Median Models","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Theory of computation; Population; Computer science; Ideal (ethics); Service (business); Variable (mathematics); Operations research; Algorithm; Mathematics; Demography; Sociology; Economics; Political science; Economy","score_opus":0.752284831608935,"score_gpt":0.4726998005954861,"score_spread":0.2795850310134489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W170489151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75235295,0.0006511026,0.0023837036,0.11820823,0.00039800434,0.0016492634,0.000102072874,0.00010595595,0.124148734],"genre_scores_gemma":[0.99680835,0.0002307193,0.0001607759,0.0004898473,0.00013123007,0.000038388076,0.0002744347,0.0000083531095,0.0018578972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985572,0.000043829474,0.0003292794,0.00027181956,0.0005299907,0.00026787457],"domain_scores_gemma":[0.99865943,0.000020485664,0.000011238485,0.000669845,0.00062499434,0.000014032772],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0019273376,0.000070776194,0.00010230176,0.00068734464,0.00017151923,0.00014394437,0.0005623963,0.000037203354,0.001796312],"category_scores_gemma":[0.00045313258,0.00007114136,0.00002178943,0.0012049691,0.00007592624,0.002461327,0.00034167187,0.00014349839,0.0008273726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002814506,0.0012232027,0.0020997787,0.0003473539,0.000041905485,0.0000074212026,0.00081539905,0.52338356,0.00027054505,0.15633781,0.28532004,0.030124828],"study_design_scores_gemma":[0.00014008547,0.000006225146,0.0015240787,0.000018101913,0.0000017170291,7.306764e-8,0.00042479768,0.97399104,0.000021011152,0.0010598603,0.022741104,0.000071909664],"about_ca_topic_score_codex":0.0068299524,"about_ca_topic_score_gemma":0.025728177,"teacher_disagreement_score":0.45060748,"about_ca_system_score_codex":0.000010618418,"about_ca_system_score_gemma":0.000017275359,"threshold_uncertainty_score":0.9999506},"labels":[],"label_agreement":null},{"id":"W175209279","doi":"10.1023/a:1021153305410","title":"A General Approach to the Physician Rostering Problem","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Computer science; Flexibility (engineering); Theory of computation; Mathematical optimization; Context (archaeology); Genetic algorithm; Constraint (computer-aided design); Constraint programming; Personalization; Operations research; Algorithm; Mathematics; Machine learning; Stochastic programming","score_opus":0.710463223401453,"score_gpt":0.5447390887290039,"score_spread":0.16572413467244906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W175209279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64636683,0.001133833,0.026182285,0.10239196,0.00021437922,0.0014739155,0.000074163865,0.00007020686,0.22209245],"genre_scores_gemma":[0.96752226,0.000028551,0.01317305,0.00062737596,0.00021498784,0.00011596701,0.0000030787735,0.0000093917015,0.018305354],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967026,0.0004983289,0.00039593343,0.00034313856,0.0016278354,0.00043215873],"domain_scores_gemma":[0.99702215,0.00039366708,0.000023030523,0.0008006614,0.0016319815,0.00012849573],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0064030867,0.00007600397,0.0001523457,0.0004444477,0.0009457579,0.00057574926,0.0010044993,0.000037295235,0.00015741446],"category_scores_gemma":[0.0022176497,0.000046073415,0.00009142129,0.0027399403,0.0001498418,0.00025731119,0.00023364373,0.00025743764,0.0011593903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016031301,0.0007952433,0.00023297087,0.0000073755045,0.00006087266,0.0000013727465,0.00834316,0.57974267,0.0061451634,0.06517621,0.26707414,0.0724048],"study_design_scores_gemma":[0.00020940998,0.00022755635,0.0022598077,0.000028121707,0.0000053643084,0.0000069919483,0.0021030724,0.8385104,0.005655509,0.0043297266,0.14644557,0.0002184578],"about_ca_topic_score_codex":0.00021632489,"about_ca_topic_score_gemma":0.0000673682,"teacher_disagreement_score":0.32115543,"about_ca_system_score_codex":0.000009151213,"about_ca_system_score_gemma":0.000057891986,"threshold_uncertainty_score":0.99961835},"labels":[],"label_agreement":null},{"id":"W176226554","doi":"10.1023/a:1013107507150","title":"Globally Optimized Spherical Point Arrangements: Model Variants and Illustrative Results","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Theoretical and Applied Studies in Material Sciences and Geometry","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Research Institute for Mathematical Sciences; Centrum Wiskunde and Informatica","keywords":"Solver; Mathematical optimization; Variety (cybernetics); Theory of computation; Representation (politics); Computer science; Point (geometry); Optimization problem; Mathematics; Algorithm; Artificial intelligence","score_opus":0.1169280639765363,"score_gpt":0.40098781025693014,"score_spread":0.2840597462803939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W176226554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44345227,0.00068567146,0.28888527,0.007093067,0.00017364314,0.0007407741,0.00022295877,0.00010679929,0.25863957],"genre_scores_gemma":[0.9780002,0.0023180868,0.019139407,0.000056501955,0.00004225359,0.000021859676,0.000005503805,0.0000055476144,0.00041058697],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999066,0.000033776952,0.00020031614,0.00015141463,0.00027527404,0.00027322938],"domain_scores_gemma":[0.9995431,0.000053988104,0.0000060262732,0.000119064665,0.00019241023,0.00008544475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060991873,0.00007239342,0.00012823504,0.00003964626,0.00019461465,0.00005762633,0.00014015962,0.00003560996,0.00010114332],"category_scores_gemma":[0.00013469665,0.000055697856,0.00001885738,0.00037414272,0.00031195837,0.00013401223,0.00009633603,0.0001067589,0.000010119646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016935193,0.000065914035,0.000003779412,0.000014131171,0.000035744095,0.000004833893,0.00043573076,0.91951054,0.005241392,0.06684762,0.0021588386,0.005512136],"study_design_scores_gemma":[0.00073668314,0.00021294884,0.00016390273,0.000037163136,0.0000037278746,0.00000309855,0.001263379,0.95209074,0.0031357894,0.03961045,0.0025487915,0.00019330755],"about_ca_topic_score_codex":0.000019403273,"about_ca_topic_score_gemma":0.000009811641,"teacher_disagreement_score":0.534548,"about_ca_system_score_codex":0.000008293879,"about_ca_system_score_gemma":0.000012088886,"threshold_uncertainty_score":0.22712927},"labels":[],"label_agreement":null},{"id":"W182049128","doi":"10.1023/a:1026138205325","title":"Properties of Three-Dimensional Median Line Location Models","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Theory of computation; Heuristic; Mathematical optimization; Euclidean distance; Computer science; Norm (philosophy); Line (geometry); Mathematics; Euclidean space; Combinatorics; Algorithm; Artificial intelligence; Geometry","score_opus":0.38426250755579067,"score_gpt":0.41592130949951817,"score_spread":0.0316588019437275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W182049128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2917351,0.0014781295,0.7005483,0.0046197437,0.00011802739,0.00038476824,0.0000047942335,0.000022046639,0.0010891078],"genre_scores_gemma":[0.97706103,0.000041834326,0.02240772,0.000074570504,0.00003300732,0.000031625714,0.000010849876,0.000004608005,0.0003347302],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982552,0.0002367264,0.00033170293,0.00021712795,0.00076891494,0.00019035398],"domain_scores_gemma":[0.99617493,0.000090291855,0.000030823787,0.0003375013,0.0032947294,0.0000717223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016293904,0.00006951086,0.00012040563,0.00040878484,0.00020459668,0.00005799856,0.00032360322,0.000046519173,0.000024633258],"category_scores_gemma":[0.00046582372,0.000060235463,0.000037699338,0.001287522,0.00011399275,0.0006900007,0.0000831051,0.00012082593,0.000016715732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069779794,0.00015836606,0.000013712464,0.000023182689,0.000014216268,4.6276415e-7,0.00027783023,0.7405154,0.015947763,0.23872387,0.0004233408,0.003894846],"study_design_scores_gemma":[0.00010902309,0.00012525203,0.00009323925,0.00003478485,9.639194e-7,0.000002972937,0.000018271921,0.7591062,0.22801739,0.012260567,0.00017407107,0.000057270023],"about_ca_topic_score_codex":0.00012692285,"about_ca_topic_score_gemma":0.00016863094,"teacher_disagreement_score":0.6853259,"about_ca_system_score_codex":0.00001053275,"about_ca_system_score_gemma":0.00061766355,"threshold_uncertainty_score":0.24563308},"labels":[],"label_agreement":null},{"id":"W1857100370","doi":"10.1007/s10479-015-2006-2","title":"Modeling efficiency in the presence of multiple partial input to output processes","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data envelopment analysis; Measure (data warehouse); Set (abstract data type); Bundle; Computer science; Production (economics); Extension (predicate logic); Theory of computation; Mathematical optimization; Efficiency; Mathematics; Algorithm; Data mining; Statistics; Economics","score_opus":0.6131739241068642,"score_gpt":0.5556689324244583,"score_spread":0.05750499168240597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1857100370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.964122,0.00028399832,0.026629167,0.007376436,0.00003778566,0.00042969067,0.000011978668,0.0000058715877,0.0011030665],"genre_scores_gemma":[0.9986568,0.000017767035,0.00082855724,0.000113469025,0.000036138612,0.00004849844,0.000001927949,0.000005343557,0.00029148578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930472,0.0011777552,0.00090717163,0.00042368256,0.004045543,0.00039867935],"domain_scores_gemma":[0.9892455,0.0024871468,0.000048751943,0.0009312089,0.0071569164,0.00013048033],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.023887642,0.00008877472,0.00025699876,0.0010722774,0.00023281616,0.0002613751,0.0019718534,0.000051572748,0.000020610196],"category_scores_gemma":[0.09241823,0.000054741136,0.000061459265,0.006923972,0.00027844234,0.00041917668,0.00028860263,0.00023583352,0.000090371606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003367376,0.00031046613,0.001910723,0.0000068728555,0.0000035382134,0.0000018224868,0.011064862,0.9826524,0.00067450583,0.00062782574,0.0016199562,0.0010933249],"study_design_scores_gemma":[0.00013608226,0.00021675827,0.00027387397,0.000039331157,0.000001898964,0.0000010124894,0.00635141,0.98333335,0.008036985,0.00091600884,0.0006223269,0.00007095054],"about_ca_topic_score_codex":0.0016419904,"about_ca_topic_score_gemma":0.002293987,"teacher_disagreement_score":0.06853059,"about_ca_system_score_codex":0.000013066274,"about_ca_system_score_gemma":0.0009558255,"threshold_uncertainty_score":0.9152267},"labels":[],"label_agreement":null},{"id":"W1882825307","doi":"10.1007/s10479-015-2007-1","title":"Supply chain management through the stochastic goal programming model","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Goal programming; Stochastic programming; Supply chain; Theory of computation; Computer science; Supply chain management; Mathematical optimization; Function (biology); Operations research; Programming paradigm; Mathematics; Algorithm; Business; Marketing","score_opus":0.23925848199437783,"score_gpt":0.42602666382515814,"score_spread":0.1867681818307803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1882825307","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005439249,0.0004632303,0.9652766,0.0034211345,0.00006082211,0.0011502432,0.0000075049397,0.00014906151,0.024032142],"genre_scores_gemma":[0.94223386,0.00006424331,0.05592829,0.000062824525,0.00003589099,0.00025812179,0.000013550855,0.000024498067,0.0013787062],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882525,0.000055087665,0.00021857875,0.00010948318,0.00047558895,0.00031603582],"domain_scores_gemma":[0.99920815,0.000050606417,0.000006409994,0.00026445743,0.00038259753,0.000087767454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009370104,0.000079343954,0.00009943442,0.000095311254,0.0001617926,0.00012540654,0.00023690939,0.00003580472,0.000025716061],"category_scores_gemma":[0.00014707206,0.000058380567,0.000035306028,0.00042759892,0.00011780562,0.00019525157,0.000090380134,0.00018422412,0.00004962585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003224822,0.000051348514,4.554633e-7,0.000040562445,0.000025281883,8.568858e-7,0.0015184479,0.9055613,0.00002041559,0.08245277,0.0032457607,0.0070795673],"study_design_scores_gemma":[0.00013356423,0.000039882667,0.0000015159777,0.000027388694,0.0000040464424,0.0000012060938,0.0014927267,0.9911557,0.00024166143,0.00408156,0.0027535001,0.00006728286],"about_ca_topic_score_codex":0.000017949944,"about_ca_topic_score_gemma":0.000013056521,"teacher_disagreement_score":0.93679464,"about_ca_system_score_codex":0.000018442486,"about_ca_system_score_gemma":0.000034971035,"threshold_uncertainty_score":0.23806904},"labels":[],"label_agreement":null},{"id":"W194305686","doi":"10.1023/a:1019288220413","title":"Maximization of Manufacturing Yield of Systems with Arbitrary Distributions of Component Values","year":2000,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Theory of computation; Bounded function; Hypercube; Monte Carlo method; Mathematical optimization; Probability density function; Nonlinear system; Mathematics; Applied mathematics; Function (biology); Random variable; Yield (engineering); Computer science; Algorithm; Discrete mathematics; Statistics; Mathematical analysis","score_opus":0.4890581218960466,"score_gpt":0.5390253233917611,"score_spread":0.04996720149571454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W194305686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9783577,0.0004966091,0.013918187,0.00030987026,0.000027242615,0.00048096644,0.00021282624,0.0000061378223,0.006190505],"genre_scores_gemma":[0.9845866,0.00013555822,0.014345731,0.0000051610846,0.000012525236,0.00002269939,0.000021489417,0.0000078088415,0.00086243666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99589133,0.0008344238,0.0009583235,0.00024699958,0.001863795,0.00020510351],"domain_scores_gemma":[0.9963526,0.0012152918,0.00012656809,0.00059613906,0.0016314313,0.00007797206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043354747,0.00009099196,0.0003809317,0.00044887426,0.00014366585,0.000056359087,0.0005394144,0.000060196002,0.00081309985],"category_scores_gemma":[0.00081984495,0.00006642669,0.00008376158,0.0009299661,0.00053563406,0.00037097864,0.000079270336,0.00014262382,0.000012004197],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009829028,0.0021348146,0.0031148938,0.00023873898,0.00023185997,0.0000069942894,0.0030329232,0.5470456,0.40130678,0.02345353,0.0032290728,0.015221922],"study_design_scores_gemma":[0.0001676814,0.00055305666,0.0069087828,0.00015905336,0.0000050990457,0.0000037512905,0.0011871379,0.016955722,0.9730361,0.0008245536,0.00012846795,0.000070605296],"about_ca_topic_score_codex":0.00091066724,"about_ca_topic_score_gemma":0.000012649123,"teacher_disagreement_score":0.5717293,"about_ca_system_score_codex":0.000013372856,"about_ca_system_score_gemma":0.00015622926,"threshold_uncertainty_score":0.89028734},"labels":[],"label_agreement":null},{"id":"W1964397332","doi":"10.1007/s10479-005-2061-1","title":"Evaluation of Plant Focus Strategies: A Continuous Approximation Framework","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Focus (optics); Computer science; Complement (music); Theory of computation; Product (mathematics); Mathematical optimization; Industrial engineering; Operations research; Limiting; Production (economics); Mathematics; Economics; Algorithm; Engineering; Microeconomics","score_opus":0.27547123801982365,"score_gpt":0.4301385263247739,"score_spread":0.15466728830495025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964397332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8145446,0.0010055931,0.0076103173,0.013787647,0.00020922223,0.002595465,0.000032425934,0.000073722986,0.16014098],"genre_scores_gemma":[0.9981856,0.00004807109,0.0007072019,0.00019928538,0.00047647938,0.00013394843,0.000063284584,0.000012075286,0.00017407227],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99749976,0.0001203714,0.00039908075,0.00019283342,0.0015388599,0.00024907308],"domain_scores_gemma":[0.99662364,0.00007050519,0.00007691932,0.00031510956,0.0029010556,0.000012788557],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006143212,0.00009126915,0.00016166833,0.0005809913,0.00018119508,0.00024225899,0.00026150313,0.0000644958,0.0011196643],"category_scores_gemma":[0.0008337622,0.00008435419,0.00005884233,0.00068511564,0.00011098856,0.0013289152,0.00010940963,0.00015648163,0.00013036306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006364279,0.0007119598,0.0002798507,0.00022126874,0.00013016311,0.0000010137452,0.0009191196,0.06443309,0.0017469873,0.8269573,0.030989049,0.07354659],"study_design_scores_gemma":[0.0008678237,0.00010751978,0.0016965868,0.00025858893,0.0000765336,5.8180945e-7,0.007880484,0.8829699,0.0060320506,0.043957386,0.05589254,0.00026001284],"about_ca_topic_score_codex":0.000694269,"about_ca_topic_score_gemma":0.00039609455,"teacher_disagreement_score":0.8185368,"about_ca_system_score_codex":0.00002774978,"about_ca_system_score_gemma":0.00013021014,"threshold_uncertainty_score":0.99979347},"labels":[],"label_agreement":null},{"id":"W1965275731","doi":"10.1007/s10479-005-2043-3","title":"Heuristic Procedures for Solving the Discrete Ordered Median Problem","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"Heuristics; Heuristic; Mathematical optimization; Variable neighborhood search; Theory of computation; Metaheuristic; Mathematics; Center (category theory); Genetic algorithm; Algorithm; Computer science","score_opus":0.19078021922988012,"score_gpt":0.41572418865821054,"score_spread":0.22494396942833042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965275731","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21100973,0.0009920098,0.012354876,0.7181651,0.0003445648,0.0070080957,0.000048864396,0.00019324494,0.049883526],"genre_scores_gemma":[0.99339145,0.0001050913,0.0007809726,0.0011869407,0.0005102881,0.00044323993,0.000060018912,0.000013493556,0.003508473],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986734,0.000021739601,0.00031551186,0.000207552,0.00044433444,0.0003374752],"domain_scores_gemma":[0.99834377,0.000058746333,0.000017495659,0.00029110812,0.0012734837,0.000015407271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001764596,0.000088434936,0.00010192793,0.0002537969,0.0007422351,0.00029351798,0.00039126264,0.000029385046,0.0004186114],"category_scores_gemma":[0.0012507801,0.000062684536,0.000059293692,0.0005932417,0.000128161,0.00067805365,0.00014753464,0.00011597064,0.00019821638],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001074165,0.00045687126,0.0005372577,0.0014062974,0.00013492725,6.626158e-7,0.0012772199,0.13721193,0.0013113109,0.4061611,0.42193052,0.029464496],"study_design_scores_gemma":[0.00045088437,0.000050336454,0.0023922313,0.00009156534,0.000021283919,4.0454006e-7,0.0019230841,0.57898176,0.0006939191,0.0053860024,0.40975395,0.0002545669],"about_ca_topic_score_codex":0.001400139,"about_ca_topic_score_gemma":0.01452556,"teacher_disagreement_score":0.7823818,"about_ca_system_score_codex":0.000009847021,"about_ca_system_score_gemma":0.00008129421,"threshold_uncertainty_score":0.81056035},"labels":[],"label_agreement":null},{"id":"W1966942146","doi":"10.1007/s10479-014-1614-6","title":"The practice and theory of automated timetabling","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":208,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council","keywords":"Operations research; Computer science; Library science; Annals; History; Engineering","score_opus":0.46213127535202697,"score_gpt":0.5843200294400972,"score_spread":0.12218875408807023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966942146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85600317,0.006363909,0.02516305,0.06186296,0.00030369277,0.0006772426,0.000035782057,0.00013577378,0.049454413],"genre_scores_gemma":[0.9918921,0.00025997998,0.005277226,0.0000861486,0.000036855687,0.000010487862,0.0000013460485,0.0000054439747,0.0024303945],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952851,0.0023893907,0.00051268126,0.00021416506,0.0013358027,0.00026284374],"domain_scores_gemma":[0.97248256,0.021816771,0.00008113558,0.00069183,0.0048405672,0.00008711739],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04875991,0.00005474465,0.00015743767,0.00036542158,0.00093510223,0.00032657152,0.000521877,0.00004551227,0.000060273967],"category_scores_gemma":[0.11818548,0.00003204013,0.00004989374,0.0014394613,0.0005854965,0.0003569231,0.00015404905,0.00021025099,0.000085671214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012136886,0.00023540875,0.00028694933,0.0000072140706,0.000115409595,6.8755975e-7,0.0015460479,0.014760665,0.0074197995,0.85637236,0.013943176,0.10519094],"study_design_scores_gemma":[0.00045572838,0.00044489594,0.009492444,0.000057092067,0.000029108342,0.000021776994,0.007121614,0.74844545,0.022822905,0.09521177,0.11571142,0.00018581486],"about_ca_topic_score_codex":0.00013404989,"about_ca_topic_score_gemma":0.000034034965,"teacher_disagreement_score":0.76116055,"about_ca_system_score_codex":0.0000028331742,"about_ca_system_score_gemma":0.00017088768,"threshold_uncertainty_score":0.97950184},"labels":[],"label_agreement":null},{"id":"W1970535376","doi":"10.1007/s10479-008-0419-x","title":"An XML-based schema for stochastic programs","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Schema (genetic algorithms); XML; Theory of computation; XML Schema (W3C); Programming language; XML Schema Editor; Document Structure Description; Theoretical computer science; Document type definition; Information retrieval; World Wide Web","score_opus":0.3896662908511025,"score_gpt":0.46968170142637294,"score_spread":0.08001541057527045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970535376","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.102881715,0.00014310678,0.8939166,0.000716781,0.000035373334,0.0011364513,0.0000119882725,0.00020069028,0.0009573149],"genre_scores_gemma":[0.9426778,0.00001582262,0.056708653,0.000022763415,0.000034059518,0.00029498094,0.00005124522,0.000022740529,0.00017191053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916023,0.000031766383,0.0001892205,0.00010671091,0.00024940775,0.00026265156],"domain_scores_gemma":[0.9989449,0.00008934853,0.0000050262843,0.00021252898,0.00063763774,0.00011059793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000450055,0.00006529947,0.00010821335,0.00015400552,0.00020880086,0.00004899219,0.00013618135,0.00004826057,0.000052337662],"category_scores_gemma":[0.00024101349,0.00006141965,0.000042526157,0.00032644594,0.00009817407,0.00015882848,0.000009457076,0.00010627709,0.00001719855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000128999945,0.00037347098,0.000011348659,0.00015290976,0.000021883727,0.000001133832,0.00040791,0.9766981,0.0026451147,0.008456768,0.0013272584,0.00989123],"study_design_scores_gemma":[0.00018742894,0.00021655265,0.00000958826,0.000024624735,0.0000016678904,0.0000013254491,0.00007415874,0.98863804,0.009761803,0.00017102867,0.00083947234,0.000074297335],"about_ca_topic_score_codex":0.000010222441,"about_ca_topic_score_gemma":0.000016245269,"teacher_disagreement_score":0.8397961,"about_ca_system_score_codex":0.000009881555,"about_ca_system_score_gemma":0.000067726294,"threshold_uncertainty_score":0.25046206},"labels":[],"label_agreement":null},{"id":"W1970735573","doi":"10.1007/s10479-008-0421-3","title":"Context-dependent performance standards in DEA","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Computer science; Context (archaeology); Set (abstract data type); Sample (material); A priori and a posteriori; Operations research; Efficiency; Database transaction; Service (business); Theory of computation; Performance measurement; Econometrics; Mathematical optimization; Mathematics; Statistics; Algorithm; Business; Marketing; Database","score_opus":0.5598467004218818,"score_gpt":0.5734204418366126,"score_spread":0.013573741414730778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970735573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9880011,0.00069025095,0.0006949313,0.0027034383,0.000040931096,0.00018026713,0.0000305859,0.000008005762,0.007650474],"genre_scores_gemma":[0.9952761,0.0004935497,0.00018063557,0.00011512624,0.000025983201,0.000018188117,0.000002402685,0.000006481626,0.0038815099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99228966,0.0007310789,0.00079316704,0.00040934145,0.0053603416,0.00041639525],"domain_scores_gemma":[0.99318606,0.00082244724,0.000037825852,0.000810838,0.005044732,0.000098114106],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.019666249,0.000084610336,0.0002907049,0.0013839231,0.0005706476,0.00014907167,0.0009344516,0.00006247186,0.0007368365],"category_scores_gemma":[0.00899596,0.00006486297,0.00010207443,0.0031449017,0.0005094753,0.0005467326,0.00018130428,0.00033729651,0.0002943337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033265183,0.0017947105,0.1764054,0.000027877211,0.00011701391,0.00015944254,0.013518269,0.5562835,0.005989801,0.014705583,0.070223205,0.16044255],"study_design_scores_gemma":[0.001975087,0.0016786616,0.26540038,0.00020476898,0.000010854351,0.000077739205,0.007451244,0.48967972,0.12015769,0.0030982734,0.1094442,0.00082136726],"about_ca_topic_score_codex":0.0007931123,"about_ca_topic_score_gemma":0.001720198,"teacher_disagreement_score":0.15962118,"about_ca_system_score_codex":0.00005173254,"about_ca_system_score_gemma":0.0008888206,"threshold_uncertainty_score":0.9993517},"labels":[],"label_agreement":null},{"id":"W1971063635","doi":"10.1007/s10479-011-0991-3","title":"A dynamic vehicle routing problem with multiple delivery routes","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":182,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Université du Québec à Montréal","funders":"","keywords":"Vehicle routing problem; Computer science; Heuristic; Theory of computation; Routing (electronic design automation); Operations research; Service (business); Mathematical optimization; Computer network; Artificial intelligence","score_opus":0.1498618087874064,"score_gpt":0.3781981942429519,"score_spread":0.22833638545554552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971063635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9380337,0.00020000417,0.0535023,0.00017652259,0.00002535252,0.00044507338,0.000016451726,0.00020396753,0.0073966426],"genre_scores_gemma":[0.82378006,0.00009028037,0.17577183,0.000014303019,0.000011251141,0.00005218336,0.000009643157,0.000036064645,0.00023440563],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985647,0.00020626701,0.00028779104,0.00018897082,0.00035264244,0.0003996003],"domain_scores_gemma":[0.9985849,0.00016942549,0.000015025203,0.0003145337,0.00082554936,0.00009052547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013089542,0.000111050314,0.00015279955,0.00026510644,0.00022964002,0.0000615829,0.00024085051,0.000067564884,0.00009800335],"category_scores_gemma":[0.0002220907,0.00010124648,0.000035010882,0.0007264388,0.00011034035,0.00034680686,0.00006638523,0.00029000806,0.000033959714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042137563,0.00013225165,0.010110918,0.00008675145,0.0000990384,0.00000765259,0.0040483293,0.957653,0.018490013,0.0012430453,0.00022948375,0.007857374],"study_design_scores_gemma":[0.00023581611,0.00012472457,0.005924395,0.000068912836,0.0000038434123,0.0000034444856,0.00043636214,0.96013814,0.032820333,0.000050453466,0.00006094195,0.00013261843],"about_ca_topic_score_codex":0.00034773332,"about_ca_topic_score_gemma":0.0003078342,"teacher_disagreement_score":0.122269526,"about_ca_system_score_codex":0.000026853693,"about_ca_system_score_gemma":0.00007843526,"threshold_uncertainty_score":0.41287115},"labels":[],"label_agreement":null},{"id":"W1972280695","doi":"10.1007/s10479-011-0876-5","title":"The Robust Set Covering Problem with interval data","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Regret; Benders' decomposition; Mathematical optimization; Interval (graph theory); Theory of computation; Mathematics; Heuristic; Set (abstract data type); Genetic algorithm; Minimax; Context (archaeology); Algorithm; Heuristics; Computer science; Statistics; Combinatorics","score_opus":0.5469561555470586,"score_gpt":0.4569992869582814,"score_spread":0.08995686858877716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972280695","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2545023,0.0011312796,0.6657859,0.0028262064,0.00021871037,0.0017181361,0.00024512003,0.0004511564,0.07312116],"genre_scores_gemma":[0.81155455,0.00045525565,0.1871365,0.000020322339,0.000049656017,0.00004776836,0.00004832796,0.000042464802,0.0006451794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988598,0.0001980241,0.00021070291,0.00014989606,0.00030823256,0.00027333188],"domain_scores_gemma":[0.99855244,0.00015643265,0.000009747456,0.00074040215,0.00048611747,0.000054833705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025697132,0.00006989946,0.000088887806,0.00009566716,0.00028882222,0.00011169267,0.0006727024,0.00003421288,0.0000758285],"category_scores_gemma":[0.0002557077,0.00004868869,0.000013566605,0.00044138625,0.00013394946,0.00036146492,0.00022955047,0.0002595482,0.000019238094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025399753,0.00003036002,0.00045682542,0.000044545974,0.00008317834,0.000002704811,0.0015929029,0.98225653,0.0005344023,0.0026291306,0.005917246,0.006426791],"study_design_scores_gemma":[0.00012069097,0.00010083589,0.0006922479,0.00005853547,0.0000035450128,0.0000056217077,0.000532489,0.98575693,0.009023359,0.000059707774,0.0035471043,0.00009895168],"about_ca_topic_score_codex":0.00014090067,"about_ca_topic_score_gemma":0.00026284816,"teacher_disagreement_score":0.5570522,"about_ca_system_score_codex":0.00001038187,"about_ca_system_score_gemma":0.000067806395,"threshold_uncertainty_score":0.22214162},"labels":[],"label_agreement":null},{"id":"W1972419530","doi":"10.1007/s10479-008-0309-2","title":"The erlangization method for Markovian fluid flows","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Laplace transform; Computer science; Fluid dynamics; Probabilistic logic; Erlang (programming language); Theory of computation; Erlang distribution; Markov process; Mathematical optimization; Applied mathematics; Algorithm; Statistical physics; Mathematics; Theoretical computer science; Mechanics; Mathematical analysis; Statistics; Exponential distribution; Physics; Artificial intelligence","score_opus":0.1957516228569016,"score_gpt":0.4483064527574165,"score_spread":0.2525548299005149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972419530","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25889182,0.0011087264,0.647467,0.056944106,0.00033977462,0.0027527446,0.00003717838,0.00019408388,0.032264575],"genre_scores_gemma":[0.96960497,0.0003343168,0.018288776,0.0010068499,0.0010528151,0.00031927752,0.00013136528,0.000043991873,0.009217665],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988942,0.00009146145,0.00023662178,0.00017091807,0.00033619424,0.00027056813],"domain_scores_gemma":[0.997472,0.00045912666,0.00003332124,0.000331171,0.0016935536,0.000010853431],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030082157,0.000070127106,0.00011384006,0.00029718026,0.0016046276,0.00014152758,0.00031076896,0.00003552831,0.00009738073],"category_scores_gemma":[0.0021647112,0.000051571642,0.00008816349,0.0009327495,0.000113935654,0.00064831524,0.000095576994,0.00010110236,0.0000687249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029177053,0.00019135425,0.000400852,0.00010383056,0.00018755492,0.000005006768,0.00032096487,0.16753988,0.014661849,0.71208346,0.06769104,0.036522437],"study_design_scores_gemma":[0.00022779306,0.000027961187,0.00035203286,0.00001781374,0.000016084776,0.0000015703575,0.0003771864,0.77358574,0.0033992182,0.01719788,0.20466284,0.00013386579],"about_ca_topic_score_codex":0.00022454414,"about_ca_topic_score_gemma":0.00038898096,"teacher_disagreement_score":0.71071315,"about_ca_system_score_codex":0.000008533303,"about_ca_system_score_gemma":0.000043167405,"threshold_uncertainty_score":0.9996951},"labels":[],"label_agreement":null},{"id":"W1973085655","doi":"10.1007/s10479-011-1038-5","title":"Impacts of earmarked private donations for disaster fundraising","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"York University","keywords":"Liberian dollar; Agency (philosophy); Finance; Business; Donation; Work (physics); Economics; Economic growth","score_opus":0.4694540937713886,"score_gpt":0.43921712005506436,"score_spread":0.030236973716324222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973085655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651965,0.00006406266,0.0058321673,0.004078072,0.00013772091,0.0009297166,0.000022216615,0.000026714,0.023712821],"genre_scores_gemma":[0.9977038,0.000037306196,0.0011166198,0.0002270639,0.000083819185,0.00007344596,0.000049146412,0.000010894758,0.000697906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988289,0.00002813276,0.0003725776,0.00016221621,0.00035062825,0.00025754745],"domain_scores_gemma":[0.9980681,0.0000341865,0.000026495296,0.00028829114,0.0015660301,0.00001691715],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001508798,0.000075238204,0.00012387722,0.0005254782,0.00024490376,0.000072808056,0.00025321182,0.000031689757,0.00091420906],"category_scores_gemma":[0.00061562244,0.00006961824,0.00007613859,0.00068258535,0.00012185553,0.00090081897,0.00014046057,0.00007100244,0.00008066924],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003507716,0.0014296137,0.008400944,0.0015147157,0.00024465876,9.5347895e-7,0.002924147,0.0054875603,0.011943208,0.924239,0.032592274,0.010872189],"study_design_scores_gemma":[0.0037479077,0.0005421905,0.3086039,0.00058738847,0.00014555657,0.0000012221827,0.0090760365,0.3488958,0.04587635,0.029359397,0.2518025,0.0013617236],"about_ca_topic_score_codex":0.0030892687,"about_ca_topic_score_gemma":0.0017339595,"teacher_disagreement_score":0.8948796,"about_ca_system_score_codex":0.000006708303,"about_ca_system_score_gemma":0.000035318026,"threshold_uncertainty_score":0.9999991},"labels":[],"label_agreement":null},{"id":"W1973383868","doi":"10.1007/s10479-014-1725-0","title":"A general rapid network design, line planning and fleet investment integrated model","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Ministerio de Economía y Competitividad","keywords":"Network planning and design; Operations research; Computer science; Transportation planning; Theory of computation; Flow network; Profit (economics); Public transport; Integrated business planning; Strategic planning; Process (computing); Operational planning; Transport engineering; Mathematical optimization; Engineering; Economics","score_opus":0.3250954444193009,"score_gpt":0.46765132002324783,"score_spread":0.14255587560394695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973383868","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24134654,0.0010428728,0.73757577,0.007839502,0.000082697115,0.0006975891,0.000022807519,0.0000880463,0.011304182],"genre_scores_gemma":[0.92552125,0.0004450356,0.07105301,0.00053635944,0.00015433948,0.000043560292,0.00009733432,0.00001000994,0.0021390961],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998407,0.00057646824,0.00020504236,0.00015688936,0.0003811517,0.0002734669],"domain_scores_gemma":[0.9989209,0.00016467983,0.000020365624,0.00010479836,0.0006694928,0.00011975708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003065678,0.00006132454,0.00010645445,0.00014729501,0.00076284265,0.00011139766,0.00011612216,0.000070848466,0.000040785322],"category_scores_gemma":[0.0004075908,0.000056611858,0.000018772073,0.00047204734,0.00022160994,0.00020312732,0.000012107765,0.00015001462,0.0000037939467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021010512,0.000025307521,0.00045875067,0.0000035598239,0.00000982708,4.2720959e-7,0.0054376754,0.94943523,0.000117726144,0.038246784,0.0051410883,0.0011026365],"study_design_scores_gemma":[0.00015194243,0.00013089912,0.0006798216,0.00004253663,0.0000034204218,1.3038675e-7,0.00061817036,0.99132127,0.00037702944,0.0017322194,0.004865628,0.00007693858],"about_ca_topic_score_codex":0.00073702703,"about_ca_topic_score_gemma":0.00031456642,"teacher_disagreement_score":0.6841747,"about_ca_system_score_codex":0.000010356454,"about_ca_system_score_gemma":0.0002646543,"threshold_uncertainty_score":0.5867246},"labels":[],"label_agreement":null},{"id":"W1974179675","doi":"10.1023/b:anor.0000019101.29692.2c","title":"Using Benders Decomposition to Implicitly Model Tour Scheduling","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Computer science; Correctness; Scheduling (production processes); Mathematical optimization; Benders' decomposition; Job shop scheduling; Fair-share scheduling; Algorithm; Mathematics; Schedule","score_opus":0.7910546258868351,"score_gpt":0.6473067551021794,"score_spread":0.14374787078465567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974179675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67239547,0.00007562595,0.3192404,0.007052083,0.00005110439,0.00020034568,0.000021196951,0.000019066843,0.00094472006],"genre_scores_gemma":[0.8423582,0.000012045471,0.15697049,0.00029269466,0.000067205525,0.000016920108,0.000005438509,0.000011827034,0.00026521023],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964086,0.00022269365,0.00061030244,0.00045048166,0.0017651698,0.0005427523],"domain_scores_gemma":[0.99544495,0.000364481,0.000037409154,0.0006504758,0.0032309757,0.0002717135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006244564,0.00010659804,0.00021886859,0.0012821709,0.001030118,0.0004509245,0.0006662147,0.00008441778,0.00009896809],"category_scores_gemma":[0.0043516974,0.00009361802,0.00012416646,0.0025725004,0.00012856435,0.000531127,0.00018767113,0.0002940376,0.00030459824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001479589,0.00009692363,0.000069489106,0.0000014698529,0.000013399751,0.0000010843428,0.00060342933,0.9481431,0.030311564,0.019530669,0.00035296148,0.0008611192],"study_design_scores_gemma":[0.00027079726,0.00012605007,0.0004973335,0.00005492832,0.0000057894636,0.000008230406,0.001292204,0.90586704,0.040830296,0.050783448,0.00010534393,0.00015852839],"about_ca_topic_score_codex":0.00084519223,"about_ca_topic_score_gemma":0.00035187736,"teacher_disagreement_score":0.1699627,"about_ca_system_score_codex":0.000060041064,"about_ca_system_score_gemma":0.0007583489,"threshold_uncertainty_score":0.79229385},"labels":[],"label_agreement":null},{"id":"W1978587158","doi":"10.1007/s10479-013-1522-1","title":"Supply chain scheduling to minimize holding costs with outsourcing","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Outsourcing; Theory of computation; Shortest path problem; Scheduling (production processes); Job shop scheduling; Mathematical optimization; Supply chain; Bounded function; Holding cost; Polynomial-time approximation scheme; Computer science; Time complexity; Longest path problem; Mathematics; Approximation algorithm; Combinatorics; Algorithm; Business; Computer network","score_opus":0.08653777754906168,"score_gpt":0.3666433294800415,"score_spread":0.28010555193097986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978587158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5441038,0.00012495107,0.44992584,0.0024157448,0.000086501765,0.00030659526,0.000010158078,0.00014275056,0.0028836546],"genre_scores_gemma":[0.8107948,0.00003731957,0.18864477,0.000105299354,0.00011042932,0.000047180285,0.000012859117,0.00003324047,0.00021411349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986122,0.00010901421,0.00024089986,0.00019738586,0.0004504424,0.00039001816],"domain_scores_gemma":[0.99864346,0.00018396198,0.0000086690125,0.0002980843,0.0006812001,0.00018461351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013717695,0.00011158403,0.00017138578,0.0004601431,0.00024005078,0.00015394812,0.00021769076,0.000060400504,0.00007070326],"category_scores_gemma":[0.0005660083,0.00010304898,0.000031105483,0.0008206545,0.00005166147,0.00016126863,0.00004548886,0.0002612834,0.0000713392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011088791,0.000019416251,0.0003123173,0.000018716708,0.000020682342,0.0000010282001,0.00061303756,0.99130833,0.0023279975,0.001000042,0.00022843276,0.004138913],"study_design_scores_gemma":[0.0002472543,0.000094919815,0.0004822538,0.00014373811,0.0000025035094,0.0000025662578,0.00059249107,0.9685674,0.029297628,0.000008683363,0.0004162871,0.000144275],"about_ca_topic_score_codex":0.00008396775,"about_ca_topic_score_gemma":0.000044083554,"teacher_disagreement_score":0.266691,"about_ca_system_score_codex":0.000027422107,"about_ca_system_score_gemma":0.00004620859,"threshold_uncertainty_score":0.42022154},"labels":[],"label_agreement":null},{"id":"W1979353897","doi":"10.1007/s10479-011-0850-2","title":"A new column generation algorithm for Logical Analysis of Data","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Theory of computation; Computer science; Column (typography); Column generation; Algorithm; Mathematics; Mathematical optimization","score_opus":0.6416303804554536,"score_gpt":0.5226771941018385,"score_spread":0.11895318635361507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979353897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004018353,0.00012407184,0.9939835,0.0010262637,0.0000355263,0.00020532815,0.00007746031,0.000015558539,0.0005139393],"genre_scores_gemma":[0.14505295,0.00007265533,0.8528661,0.00006706941,0.0001241598,0.000024504647,0.00023654758,0.000005524254,0.0015504493],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984807,0.00022085897,0.0002948197,0.00034817687,0.0004396226,0.00021584287],"domain_scores_gemma":[0.99786216,0.00013449501,0.000034750778,0.00095134974,0.00092241133,0.0000948354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020720463,0.0000610124,0.00019929968,0.0004921495,0.00018713118,0.000090562105,0.0013058598,0.000048283426,0.00015715136],"category_scores_gemma":[0.0003039996,0.000053101845,0.000076214244,0.0016823097,0.00006205515,0.0004963355,0.00039342654,0.00013016835,0.000006596459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005726578,0.00030331934,0.000244702,0.000009732712,0.00044274423,0.000002177899,0.001326913,0.004214157,0.0014420684,0.03280756,0.017082172,0.9421187],"study_design_scores_gemma":[0.000107482345,0.00024740436,0.0013716038,0.00000366569,0.000020934944,5.6403434e-7,0.000022908003,0.99319065,0.0032878874,0.0002484871,0.0014423489,0.000056075314],"about_ca_topic_score_codex":0.0020050453,"about_ca_topic_score_gemma":0.00031026846,"teacher_disagreement_score":0.9889765,"about_ca_system_score_codex":0.0000043338696,"about_ca_system_score_gemma":0.00022877532,"threshold_uncertainty_score":0.3031042},"labels":[],"label_agreement":null},{"id":"W1979700544","doi":"10.1023/b:anor.0000032576.73681.29","title":"Solving VRPTWs with Constraint Programming Based Column Generation","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Column generation; Constraint programming; Theory of computation; Mathematical optimization; Computer science; Scheduling (production processes); Concurrent constraint logic programming; Constraint logic programming; Constraint satisfaction; Constraint (computer-aided design); Directed graph; Directed acyclic graph; Mathematics; Stochastic programming; Algorithm; Artificial intelligence","score_opus":0.20972328302259866,"score_gpt":0.42493952686567527,"score_spread":0.2152162438430766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979700544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31630823,0.00013227118,0.6797941,0.0013160574,0.00004732997,0.0006200702,0.000011072517,0.00017123153,0.0015996575],"genre_scores_gemma":[0.7111902,0.000023043674,0.28853273,0.0000337927,0.000053256626,0.00007373083,0.00002825917,0.000024698207,0.000040281],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985859,0.00015547745,0.00027742537,0.00017703413,0.00045459843,0.0003495979],"domain_scores_gemma":[0.9985893,0.000084487365,0.00001357812,0.0002611583,0.000956889,0.00009463444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015617257,0.00010029714,0.0001370393,0.00027906758,0.00029740424,0.00017655684,0.00014197483,0.00006926497,0.000071206465],"category_scores_gemma":[0.0003063041,0.00009834172,0.000032108117,0.000752272,0.00016598625,0.00023414928,0.000020561454,0.00025717905,0.0000120431905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042674574,0.00004753126,0.00010309322,0.000032797587,0.000020144204,0.0000032262642,0.00027976098,0.97234726,0.01806441,0.0018921056,0.00012410463,0.00708131],"study_design_scores_gemma":[0.00043117293,0.00016751865,0.00017128728,0.00007829342,0.0000037411392,0.000004969437,0.00019579261,0.86998034,0.12828623,0.00002406838,0.0005169489,0.00013961621],"about_ca_topic_score_codex":0.000109012,"about_ca_topic_score_gemma":0.00026819896,"teacher_disagreement_score":0.39488196,"about_ca_system_score_codex":0.000052072122,"about_ca_system_score_gemma":0.00028943617,"threshold_uncertainty_score":0.4010259},"labels":[],"label_agreement":null},{"id":"W1980402561","doi":"10.1007/s10479-007-0170-8","title":"The dial-a-ride problem: models and algorithms","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":866,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Theory of computation; Computer science; Pickup; Set (abstract data type); Algorithm; Plan (archaeology); Operations research; Mathematical optimization; Artificial intelligence; Mathematics; Image (mathematics); Programming language","score_opus":0.22324015215530751,"score_gpt":0.43758322828918544,"score_spread":0.21434307613387793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980402561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.846376,0.0014620381,0.11100854,0.0079277335,0.00012912626,0.0010689584,0.00006878083,0.00015760149,0.031801242],"genre_scores_gemma":[0.99651915,0.000890446,0.0019648317,0.000029952591,0.000029384724,0.00004436231,0.00001535586,0.000009463059,0.00049706054],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916613,0.000024331623,0.00025550954,0.00008196009,0.00024804036,0.00022403453],"domain_scores_gemma":[0.9990133,0.00017888233,0.0000046998225,0.00016936942,0.0005796226,0.000054138414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018277531,0.000048564598,0.0000605294,0.00013741101,0.00031622552,0.00006231108,0.00009963238,0.000035415087,0.000014115974],"category_scores_gemma":[0.000055795,0.000037805177,0.000017961955,0.00044875426,0.00014723354,0.00018778224,0.000010636169,0.00017246038,0.0000061787155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030003424,0.00015520907,0.00042880664,0.000108475426,0.00014023553,0.0000057572825,0.00469288,0.4373589,0.018317614,0.39985633,0.018865589,0.1200402],"study_design_scores_gemma":[0.0009681208,0.00030069874,0.045928847,0.00010063554,0.000015626003,0.000013630645,0.004031778,0.7143519,0.11097565,0.024578683,0.09814661,0.0005878328],"about_ca_topic_score_codex":0.00011724643,"about_ca_topic_score_gemma":0.00093801605,"teacher_disagreement_score":0.37527767,"about_ca_system_score_codex":0.000006568681,"about_ca_system_score_gemma":0.0000385552,"threshold_uncertainty_score":0.2432183},"labels":[],"label_agreement":null},{"id":"W1980455964","doi":"10.1007/s10479-013-1412-6","title":"Scheduling policies for a repair shop problem","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Magna International (Canada)","funders":"","keywords":"Theory of computation; Computer science; Job shop scheduling; Scheduling (production processes); Operations research; Flow shop scheduling; Mathematical optimization; Mathematics; Algorithm; Schedule; Operating system","score_opus":0.1616624709572598,"score_gpt":0.41351088715963524,"score_spread":0.2518484162023754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980455964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7809931,0.00221571,0.1824211,0.012291483,0.00026065786,0.0034363382,0.00007221262,0.0011059259,0.017203452],"genre_scores_gemma":[0.561687,0.00027769382,0.43540928,0.00008098269,0.00015221353,0.0006376771,0.000031923522,0.00003729027,0.0016859514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990648,0.000038004262,0.00023948899,0.00012036684,0.00022968125,0.00030763992],"domain_scores_gemma":[0.9983344,0.00012198086,0.000006138444,0.00021158677,0.0012443047,0.000081581886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061114825,0.00007271525,0.000111106405,0.0002666125,0.00019841734,0.000113022405,0.00014405917,0.00006116785,0.00015297494],"category_scores_gemma":[0.00031015402,0.000068824425,0.00006599217,0.00044015955,0.000063661486,0.0002481191,0.000027951224,0.00014558576,0.00007595816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023799562,0.000034798537,0.00006109907,0.00007152107,0.00003974218,1.3544404e-7,0.0005763918,0.9829555,0.0022318743,0.0050751837,0.0069081266,0.002043224],"study_design_scores_gemma":[0.000115669776,0.000058012196,0.00009712883,0.000030816893,0.000001632689,8.0730615e-7,0.0005404417,0.98678315,0.0109477565,0.0003280137,0.0010149518,0.00008160047],"about_ca_topic_score_codex":0.0001396061,"about_ca_topic_score_gemma":0.000021606511,"teacher_disagreement_score":0.2529882,"about_ca_system_score_codex":0.000011298518,"about_ca_system_score_gemma":0.000057203728,"threshold_uncertainty_score":0.28065786},"labels":[],"label_agreement":null},{"id":"W1982514240","doi":"10.1007/s10479-014-1784-2","title":"Close integration of pricing and supply chain decisions has strategic as well as operations level benefits","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Business; Supply chain management; Revenue; Industrial organization; Strategic sourcing; Production (economics); Revenue management; Marketing; Quality (philosophy); Strategic planning; Process management; Strategic financial management; Microeconomics; Economics","score_opus":0.5014485031989758,"score_gpt":0.42329310173989737,"score_spread":0.07815540145907846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982514240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9368028,0.00039427337,0.00038019897,0.0095207915,0.00012343471,0.0008008064,0.000021029931,0.000027765844,0.05192888],"genre_scores_gemma":[0.99442923,0.00027829592,0.0005959146,0.0006107134,0.00023583778,0.000078229685,0.00015207118,0.000023160264,0.0035965526],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978182,0.000095431904,0.0005427295,0.00034044377,0.0008588404,0.00034441028],"domain_scores_gemma":[0.9970092,0.00011855256,0.00005695984,0.00041198815,0.0023372083,0.00006605327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024543903,0.00016567581,0.00024278696,0.001000578,0.00052893616,0.00065073185,0.00034823923,0.00008376413,0.00071295694],"category_scores_gemma":[0.0012584395,0.0001477503,0.00006364577,0.0010797397,0.00025274197,0.0013838101,0.00032243773,0.00022966505,0.0004435286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105805586,0.000574898,0.0007538172,0.00008188978,0.00007128244,0.000007667257,0.0011385042,0.023057397,0.0050307363,0.9335969,0.029790767,0.0057903333],"study_design_scores_gemma":[0.005696991,0.0018805055,0.015036215,0.0017220291,0.00016428804,0.000022758291,0.07850865,0.6154509,0.04634751,0.097395696,0.13600084,0.0017736133],"about_ca_topic_score_codex":0.007858339,"about_ca_topic_score_gemma":0.0035876064,"teacher_disagreement_score":0.8362012,"about_ca_system_score_codex":0.000026002383,"about_ca_system_score_gemma":0.00026134966,"threshold_uncertainty_score":0.9987484},"labels":[],"label_agreement":null},{"id":"W1982561848","doi":"10.1007/s10479-013-1391-7","title":"Smoothing and parametric rules for stochastic mean-CVaR optimal execution strategy","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"CVAR; Mathematical optimization; Computer science; Downside risk; Expected shortfall; Smoothing; Parametric statistics; Theory of computation; Portfolio; Discretization; Representation (politics); Algorithm; Mathematics","score_opus":0.4890830016918179,"score_gpt":0.5419786120347316,"score_spread":0.052895610342913735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982561848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8493201,0.00055594527,0.14611486,0.0020239514,0.000051160376,0.00093030836,0.000040652383,0.000013760427,0.0009492269],"genre_scores_gemma":[0.9879525,0.00047963575,0.009708359,0.00004072269,0.00005958908,0.0001560927,0.00003004229,0.000010134005,0.0015629767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99735004,0.0002900662,0.00055073225,0.00035226735,0.0011215399,0.00033537616],"domain_scores_gemma":[0.99440795,0.0015336969,0.000059888047,0.00035462232,0.0035020674,0.0001417919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046193902,0.00009389618,0.00020029896,0.0010371867,0.0005347556,0.0008143689,0.00034175825,0.000089061934,0.00026726574],"category_scores_gemma":[0.0049101813,0.00007216943,0.000059128066,0.0012826062,0.00021062684,0.0010378701,0.00008475811,0.00015647018,0.00012378077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048701466,0.00014666529,0.00030443686,0.000009127015,0.000028038889,7.05883e-7,0.0011454904,0.8342672,0.0011504533,0.029561529,0.019092053,0.11424562],"study_design_scores_gemma":[0.00028559848,0.00044213442,0.00587924,0.000017264148,0.0000051045995,0.000003833332,0.0021939552,0.97007656,0.0014950002,0.018361233,0.0011000097,0.0001400887],"about_ca_topic_score_codex":0.0006484455,"about_ca_topic_score_gemma":0.0000487982,"teacher_disagreement_score":0.13863231,"about_ca_system_score_codex":0.000009597955,"about_ca_system_score_gemma":0.0001669727,"threshold_uncertainty_score":0.7852978},"labels":[],"label_agreement":null},{"id":"W1982713086","doi":"10.1007/s10479-014-1652-0","title":"Decentralized stochastic control","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Theory of computation; Decentralization; Decentralised system; Computer science; Control (management); State (computer science); Stochastic control; Mathematical optimization; Optimal control; Distributed computing; Mathematics; Artificial intelligence; Economics; Algorithm","score_opus":0.5710642858031221,"score_gpt":0.6010051164305524,"score_spread":0.02994083062743036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982713086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73066705,0.000100628444,0.23416477,0.021984963,0.000061479885,0.00057739636,0.000045801808,0.00002533155,0.012372546],"genre_scores_gemma":[0.99665,0.000011593327,0.0003672505,0.000276579,0.000048141308,0.00007152533,0.000003862972,0.0000057177986,0.0025653262],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966328,0.0010754432,0.00045567384,0.00026501963,0.0012651195,0.00030590442],"domain_scores_gemma":[0.9941508,0.0027081915,0.000031865922,0.0007392295,0.0022211745,0.00014872743],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.010934685,0.00006237349,0.00018533497,0.0003315338,0.00041522126,0.00020261966,0.00077327766,0.000043237294,0.0013631426],"category_scores_gemma":[0.011848693,0.000045870624,0.00007334144,0.0010363335,0.0003350599,0.00019784193,0.00007003214,0.00016793919,0.0013221387],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007443925,0.00022366339,0.00019892152,0.000002320405,0.000020514319,3.307569e-7,0.00047271044,0.04926249,0.0125593925,0.8915936,0.018829579,0.026762046],"study_design_scores_gemma":[0.001876273,0.00054855517,0.013766354,0.000037256093,0.000011798717,0.0000072084254,0.001126312,0.28386194,0.022460975,0.58595204,0.0900095,0.00034181622],"about_ca_topic_score_codex":0.000045119225,"about_ca_topic_score_gemma":0.000041427495,"teacher_disagreement_score":0.30564156,"about_ca_system_score_codex":0.0000046248756,"about_ca_system_score_gemma":0.000099657766,"threshold_uncertainty_score":0.99954975},"labels":[],"label_agreement":null},{"id":"W1983758874","doi":"10.1007/s10479-011-0895-2","title":"The orienteering problem with stochastic travel and service times","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Orienteering; Heuristics; Theory of computation; Computer science; Variety (cybernetics); Service (business); Mathematical optimization; Operations research; Stochastic programming; Mathematics; Marketing; Artificial intelligence; Algorithm; Business","score_opus":0.17549393651751152,"score_gpt":0.38041133706969343,"score_spread":0.2049174005521819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983758874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5011655,0.0012366676,0.46362054,0.0032695695,0.000079091944,0.0013924734,0.000021336919,0.00021653133,0.028998306],"genre_scores_gemma":[0.9536431,0.00011669154,0.045740765,0.000021154485,0.000017012862,0.000058585865,0.0000022092433,0.00002406962,0.00037640258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992293,0.00009121944,0.00014533108,0.00009788669,0.00021669714,0.00021954493],"domain_scores_gemma":[0.9990437,0.00013646732,0.0000065468016,0.00018693671,0.00057028,0.000056081062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010280021,0.00006299858,0.000075493495,0.000090323774,0.00028149263,0.00006238904,0.0001406003,0.000028401186,0.00003212049],"category_scores_gemma":[0.00009214088,0.000043902346,0.000008764245,0.00044680707,0.00008898552,0.00013674708,0.000040543215,0.00016572105,0.0000070118754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030066385,0.000034590903,0.00010887721,0.00008409882,0.000074010226,0.0000013435068,0.0068366244,0.9686763,0.0023810484,0.016235514,0.00030176903,0.005235742],"study_design_scores_gemma":[0.0001656429,0.000118278454,0.0016873062,0.00006368992,0.000004502732,0.000007796644,0.0011639349,0.984895,0.011381926,0.0002595223,0.00014636006,0.00010602667],"about_ca_topic_score_codex":0.00009867478,"about_ca_topic_score_gemma":0.000121992154,"teacher_disagreement_score":0.45247763,"about_ca_system_score_codex":0.0000058645696,"about_ca_system_score_gemma":0.000039664013,"threshold_uncertainty_score":0.21650422},"labels":[],"label_agreement":null},{"id":"W1985128506","doi":"10.1007/s10479-013-1326-3","title":"The impact of customer returns on supply chain decisions under various channel interactions","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Winnipeg","funders":"","keywords":"Stackelberg competition; Supply chain; Business; Channel (broadcasting); Microeconomics; Information sharing; Industrial organization; Product (mathematics); Marketing; Economics; Computer science; Telecommunications; Mathematics","score_opus":0.20288464210705257,"score_gpt":0.4248238100277004,"score_spread":0.22193916792064786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985128506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8539178,0.0001723933,0.00031124896,0.033674836,0.00040285566,0.0017620405,0.000025277577,0.00004908713,0.10968447],"genre_scores_gemma":[0.9929359,0.00020505975,0.000022505601,0.0005187412,0.00029044205,0.00018849301,0.000035489942,0.000021975506,0.005781393],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819934,0.00009092646,0.00041083788,0.00022465005,0.0006388108,0.00043543678],"domain_scores_gemma":[0.9972603,0.00043715752,0.00007084398,0.0005817436,0.0016157388,0.000034256227],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013640642,0.00013948636,0.0001745899,0.00080135604,0.0007416461,0.00044559597,0.0005219882,0.000047118912,0.0022853722],"category_scores_gemma":[0.00073388545,0.000089471316,0.00018430839,0.0010629483,0.00022391882,0.0008818992,0.00027680138,0.00031469905,0.0010976543],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011413656,0.00085420697,0.00050908065,0.000029919222,0.0002791596,0.0000023860707,0.00042843362,0.042108018,0.002328744,0.13419206,0.81372863,0.0054252422],"study_design_scores_gemma":[0.0024679936,0.0010798306,0.20505801,0.00082163775,0.00007654491,0.0000066777175,0.021620585,0.48571357,0.0047422675,0.061414555,0.21569999,0.0012983597],"about_ca_topic_score_codex":0.008585154,"about_ca_topic_score_gemma":0.0008732942,"teacher_disagreement_score":0.5980286,"about_ca_system_score_codex":0.000040790976,"about_ca_system_score_gemma":0.00007320156,"threshold_uncertainty_score":0.9996801},"labels":[],"label_agreement":null},{"id":"W1985987363","doi":"10.1007/s10479-010-0753-7","title":"Introduction to the special issue on Advances in Manufacturing Systems","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Theory of computation; Operations research; Head (geology); Library science; Volume (thermodynamics); Engineering management; Management; Computer science; Engineering; Economics; Physics","score_opus":0.050480596408346456,"score_gpt":0.3776737893975814,"score_spread":0.32719319298923494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985987363","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89954704,0.00082822924,0.0048284675,0.052410062,0.007727953,0.0016115209,0.000035071782,0.00016741829,0.032844234],"genre_scores_gemma":[0.9717814,0.00069308106,0.0038395661,0.00006799381,0.021470161,0.00013355668,0.000016221578,0.00002655173,0.001971482],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992447,0.000053811364,0.00015662458,0.00011286575,0.00026329746,0.00016868643],"domain_scores_gemma":[0.9994942,0.000058250287,0.0000041711282,0.00022709866,0.00017439849,0.00004186361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079322583,0.000051780145,0.00007079731,0.00026477105,0.000119979144,0.00008662126,0.00015422708,0.000038199127,0.00025048605],"category_scores_gemma":[0.00022120091,0.000039808026,0.0000137860925,0.00032911293,0.000028550527,0.00015300399,0.000017226306,0.000358118,0.00021611075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055133382,0.000015131568,0.000006418229,0.000009026357,0.000002731139,4.014889e-7,0.00029077,0.9759446,0.0003901792,0.00088887266,0.010018353,0.012428041],"study_design_scores_gemma":[0.000119516146,0.00008187402,0.0004718988,0.000029555704,7.9033003e-7,0.0000025228076,0.000758058,0.36605683,0.07867415,0.000025257865,0.5536672,0.00011235774],"about_ca_topic_score_codex":0.00004348474,"about_ca_topic_score_gemma":0.00037030474,"teacher_disagreement_score":0.6098877,"about_ca_system_score_codex":0.0000101504465,"about_ca_system_score_gemma":0.000015209382,"threshold_uncertainty_score":0.27777386},"labels":[],"label_agreement":null},{"id":"W1986520459","doi":"10.1007/s10479-005-3445-y","title":"Depth-Optimized Convexity Cuts","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Science Foundation","keywords":"Convexity; Theory of computation; Intersection (aeronautics); Mathematics; Set (abstract data type); Computation; Mathematical optimization; Integer programming; Regular polygon; Function (biology); Order (exchange); Convex function; Integer (computer science); Linear programming; Algorithm; Computer science; Geometry","score_opus":0.24676143754847643,"score_gpt":0.4702200630803455,"score_spread":0.22345862553186904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986520459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45872465,0.0015864435,0.39849108,0.010976616,0.0002505415,0.0011460008,0.000053022985,0.00070285157,0.12806877],"genre_scores_gemma":[0.80894274,0.00045026574,0.1888357,0.00008727252,0.000116872056,0.000039473915,0.000015010478,0.000029699306,0.0014829533],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998519,0.00028125523,0.00031315308,0.00014608778,0.00040187375,0.00033860822],"domain_scores_gemma":[0.99857986,0.0001966521,0.000008697627,0.00034030247,0.000765957,0.000108541215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001926734,0.0000884436,0.00016170285,0.00027552983,0.00017279157,0.00007132868,0.00023377102,0.00008253978,0.00052223494],"category_scores_gemma":[0.0005568069,0.00009139159,0.0000515685,0.0005923336,0.00011147838,0.00027981945,0.000053294974,0.00030158155,0.0001720903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069999414,0.000037954185,0.00009162462,0.000016744336,0.000023986604,6.791924e-7,0.00028339386,0.97880334,0.0033654901,0.0012382627,0.0067693368,0.009362206],"study_design_scores_gemma":[0.0002517535,0.00002705519,0.0005190633,0.000015068828,0.0000019810702,0.0000020304942,0.000057966394,0.92214465,0.0694387,0.00004525501,0.007398505,0.000097946766],"about_ca_topic_score_codex":0.000035756377,"about_ca_topic_score_gemma":0.000051618554,"teacher_disagreement_score":0.3502181,"about_ca_system_score_codex":0.00002482605,"about_ca_system_score_gemma":0.000070998954,"threshold_uncertainty_score":0.57181066},"labels":[],"label_agreement":null},{"id":"W1986972052","doi":"10.1007/s10479-008-0380-8","title":"A hierarchical location-allocation model with travel based on expected referral distances","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Irrationality; Irrational number; Travel time; Theory of computation; Computer science; Travel behavior; Referral; Location-allocation; Facility location problem; Operations research; Mathematics; Microeconomics; Economics; Transport engineering; Rationality; Algorithm; Medicine; Engineering","score_opus":0.2675221041792846,"score_gpt":0.45042250610904716,"score_spread":0.18290040192976253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986972052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6874256,0.00008990064,0.25373954,0.022982903,0.00004509521,0.0008720857,0.00005696194,0.0001107513,0.034677137],"genre_scores_gemma":[0.99111074,0.00011739593,0.0060826996,0.0001413549,0.000043279855,0.00008718571,0.00016910439,0.000010164612,0.0022380769],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979479,0.000310253,0.00022777029,0.000221934,0.0010328381,0.00025935614],"domain_scores_gemma":[0.997773,0.00017447882,0.000026549644,0.0001931924,0.0017171998,0.00011559521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007866934,0.00007553878,0.0001104408,0.00030268112,0.0012396531,0.000051743,0.00018222627,0.00007417089,0.0000651092],"category_scores_gemma":[0.00033898724,0.000066108354,0.00002679706,0.0011150644,0.0005573049,0.00028583637,0.0000033155966,0.00020477013,0.000009821001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016943322,0.00023781268,0.0012976588,0.000008794932,0.000008239717,0.0000023434227,0.012987532,0.9357717,0.00009184793,0.04805233,0.0011256011,0.0002467312],"study_design_scores_gemma":[0.0006259198,0.00042674923,0.03350594,0.00011880079,0.0000055128708,6.823536e-7,0.0043774345,0.95827234,0.001469604,0.00035424728,0.000620769,0.00022197659],"about_ca_topic_score_codex":0.001155394,"about_ca_topic_score_gemma":0.0031006658,"teacher_disagreement_score":0.3036851,"about_ca_system_score_codex":0.000029658568,"about_ca_system_score_gemma":0.001204061,"threshold_uncertainty_score":0.9534535},"labels":[],"label_agreement":null},{"id":"W1987959344","doi":"10.1007/s10479-005-2041-5","title":"A Continuous Location-Allocation Problem with Zone-Dependent Fixed Cost","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada; Group for Research in Decision Analysis","funders":"","keywords":"Theory of computation; Mathematical optimization; Fixed cost; Computer science; Mathematics; Algorithm; Economics; Microeconomics","score_opus":0.14117281700540285,"score_gpt":0.37634040909043937,"score_spread":0.23516759208503651,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987959344","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73560053,0.00053722964,0.04158388,0.1300811,0.0002129024,0.005866981,0.00002093252,0.00032117747,0.085775286],"genre_scores_gemma":[0.9898027,0.000075658354,0.000943409,0.0009332142,0.0002796592,0.00037173415,0.000119177355,0.000018810724,0.007455612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980006,0.00004921934,0.00042931293,0.00032285147,0.00083058485,0.0003674233],"domain_scores_gemma":[0.9961222,0.000023406179,0.000032468808,0.00044040778,0.0033539727,0.00002755638],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016445675,0.00013246799,0.00016040633,0.0005435829,0.00042793233,0.00031240642,0.00034377078,0.00004974118,0.0008243616],"category_scores_gemma":[0.00019547303,0.0001161936,0.00003642674,0.0012761375,0.00013513176,0.0013668243,0.00012771637,0.0001770503,0.0011951161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020965867,0.001507555,0.0025484853,0.00051631156,0.00015639134,0.0000033496492,0.000729771,0.6468929,0.0018773766,0.2158452,0.056620326,0.07309265],"study_design_scores_gemma":[0.002113947,0.00022630756,0.015310325,0.00028234153,0.000053886524,0.0000039179113,0.0042065387,0.44690496,0.0056305435,0.00040460608,0.52403474,0.00082788337],"about_ca_topic_score_codex":0.0050674537,"about_ca_topic_score_gemma":0.016965613,"teacher_disagreement_score":0.4674144,"about_ca_system_score_codex":0.000035207566,"about_ca_system_score_gemma":0.00011751941,"threshold_uncertainty_score":0.9995826},"labels":[],"label_agreement":null},{"id":"W1994221629","doi":"10.1007/s10479-013-1450-0","title":"Using mixed integer programming models to synchronously determine production levels and market prices in an integrated market for roundwood and forest biomass","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Procurement; Supply chain; Theory of computation; Computer science; Production (economics); Mathematical optimization; Market price; Linear programming; Integer programming; Operations research; Economics; Microeconomics; Mathematics; Business; Marketing; Algorithm","score_opus":0.24368799431871346,"score_gpt":0.4142678343128243,"score_spread":0.17057983999411086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994221629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99350953,0.00003290287,0.0027253425,0.0012612464,0.00001990598,0.0018376342,0.000009175518,0.00001022063,0.0005940492],"genre_scores_gemma":[0.97853386,0.000019551728,0.019647632,0.0000311299,0.000026721495,0.00032388177,0.00001029594,0.000013984452,0.0013929126],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987288,0.000117188916,0.00023816711,0.00033228754,0.00022550477,0.00035803134],"domain_scores_gemma":[0.99946696,0.000061987725,0.000022210079,0.00019868177,0.00013574745,0.000114443465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013011112,0.00010782938,0.00013030959,0.0003216336,0.00021420611,0.00027238193,0.00015776443,0.000048038997,0.00029213235],"category_scores_gemma":[0.00018255082,0.000092559894,0.000015952151,0.00056882825,0.00021624501,0.0014137189,0.00020034259,0.00008850523,0.000008086339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077246025,0.002001623,0.17721955,0.00094869995,0.00016891332,0.000010465893,0.014555677,0.092856355,0.07550398,0.0030650687,0.054405145,0.57849205],"study_design_scores_gemma":[0.00027628298,0.00055539724,0.06430864,0.00008471067,0.0000056742238,0.000004230117,0.00065243285,0.9297851,0.0014004491,0.0007042372,0.0020149685,0.00020790705],"about_ca_topic_score_codex":0.008565261,"about_ca_topic_score_gemma":0.013280199,"teacher_disagreement_score":0.8369287,"about_ca_system_score_codex":0.000049446448,"about_ca_system_score_gemma":0.000025719082,"threshold_uncertainty_score":0.9980368},"labels":[],"label_agreement":null},{"id":"W1994932713","doi":"10.1007/s10479-008-0481-4","title":"A branch-and-cut algorithm based on semidefinite programming for the minimum k-partition problem","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Direktion für Entwicklung und Zusammenarbeit","keywords":"Mathematics; Semidefinite programming; Rounding; Partition (number theory); Combinatorics; Hyperplane; Disjoint sets; Algorithm; Graph partition; Maximum cut; Partition problem; Branch and cut; Integer programming; Graph; Computer science; Mathematical optimization","score_opus":0.2635310348025377,"score_gpt":0.4164277997338451,"score_spread":0.15289676493130738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994932713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009432294,0.00037071217,0.96744525,0.020450886,0.000080825506,0.0014546106,0.000037387086,0.00006633398,0.0006616978],"genre_scores_gemma":[0.7092479,0.00036158285,0.28784022,0.0007837821,0.00015003241,0.0009945646,0.000025099382,0.000016399903,0.0005804499],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984079,0.0001695961,0.00023519294,0.0002954118,0.0005387861,0.0003531069],"domain_scores_gemma":[0.99779344,0.00089820515,0.000023120276,0.00045757883,0.0007529793,0.000074709795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015700344,0.00009129822,0.00012072003,0.0002531313,0.0012319576,0.00019507536,0.00051854196,0.00004361048,0.000012572668],"category_scores_gemma":[0.00021609092,0.00006807773,0.00007936538,0.00078037457,0.0003335291,0.0002964442,0.0001257256,0.00021598897,0.000008513151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056673805,0.00081311696,0.00013452746,0.00009810632,0.00006794909,0.000010300878,0.002769313,0.011679036,0.00069147005,0.18447098,0.010291485,0.78891706],"study_design_scores_gemma":[0.00031580296,0.00060579675,0.00048576598,0.000055551667,0.0000021493017,0.000010166887,0.000044392356,0.97446805,0.004618851,0.0054339455,0.01385271,0.00010683623],"about_ca_topic_score_codex":0.000096488475,"about_ca_topic_score_gemma":0.000043603213,"teacher_disagreement_score":0.962789,"about_ca_system_score_codex":0.000008076656,"about_ca_system_score_gemma":0.00017814657,"threshold_uncertainty_score":0.9475346},"labels":[],"label_agreement":null},{"id":"W1996637843","doi":"10.1007/s10479-006-0067-y","title":"Multiobjective design of survivable IP networks","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"Vetenskapsrådet","keywords":"Computer network; Private Network-to-Network Interface; Computer science; Open Shortest Path First; Constrained Shortest Path First; Shortest path problem; Routing protocol; Survivability; Distributed computing; IP forwarding; Routing (electronic design automation); Internet Protocol; The Internet; Link-state routing protocol; K shortest path routing; Graph","score_opus":0.20657839439451176,"score_gpt":0.435748254671344,"score_spread":0.22916986027683223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996637843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011472708,0.0009881775,0.98467064,0.000056584733,0.000017957782,0.00028585872,0.000031912045,0.00012093377,0.0023552477],"genre_scores_gemma":[0.93728304,0.00045549727,0.06194097,0.000004130031,0.000037952897,0.000059866463,0.00003567115,0.000020189738,0.00016265601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990833,0.00010094543,0.00022908468,0.00011116536,0.00024112394,0.0002343969],"domain_scores_gemma":[0.99876314,0.0001754729,0.00001099478,0.00026380405,0.0007611902,0.000025397827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085191376,0.00006742369,0.00012874255,0.00021050176,0.000095385374,0.000026938105,0.00019899262,0.00006093561,0.000028444854],"category_scores_gemma":[0.00016522057,0.000068000394,0.000020580137,0.0005364585,0.000121578334,0.00032566977,0.00004613784,0.00018762035,0.0000047201943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008390451,0.000042962263,0.00004617274,0.000022223123,0.000010242896,7.2198225e-7,0.000033627588,0.9749328,0.014073703,0.0017711649,0.0069680302,0.0020899961],"study_design_scores_gemma":[0.00007695612,0.00007030185,0.00047527102,0.000048313486,0.0000011330203,7.42221e-7,0.00003983225,0.67916274,0.31781232,0.0016470049,0.0005833787,0.00008197942],"about_ca_topic_score_codex":0.00041606324,"about_ca_topic_score_gemma":0.00006078841,"teacher_disagreement_score":0.92581034,"about_ca_system_score_codex":0.00001625896,"about_ca_system_score_gemma":0.00004501786,"threshold_uncertainty_score":0.27729756},"labels":[],"label_agreement":null},{"id":"W1998172110","doi":"10.1007/s10479-005-5732-z","title":"Basis Function Adaptation in Temporal Difference Reinforcement Learning","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":190,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Reinforcement learning; Markov decision process; Bellman equation; Temporal difference learning; Basis function; Function approximation; Mathematical optimization; Basis (linear algebra); Computer science; Theory of computation; Q-learning; Convergence (economics); Markov process; Mathematics; Artificial intelligence; Algorithm; Artificial neural network","score_opus":0.22553966350065155,"score_gpt":0.41189285311802815,"score_spread":0.1863531896173766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998172110","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05995004,0.00007519144,0.9328964,0.0033148674,0.000050758146,0.0002850705,2.2697165e-7,0.00004330525,0.0033841585],"genre_scores_gemma":[0.98458445,0.00016146085,0.010895407,0.00010736886,0.000047183377,0.00004593613,0.000016319875,0.0000070375977,0.0041348375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977658,0.00032180603,0.00043448442,0.00026197176,0.0008473764,0.00036859463],"domain_scores_gemma":[0.9986761,0.00014993684,0.000045106448,0.0003815484,0.000675984,0.00007130287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017954679,0.00009287867,0.0001281759,0.00059908425,0.00027256834,0.00020029761,0.00050489284,0.000059849335,0.00008719236],"category_scores_gemma":[0.0004803068,0.00009155396,0.00003942791,0.0010151046,0.00006737973,0.00087124185,0.00020831902,0.00043671508,0.000104727675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010656557,0.000034828987,0.0014116098,0.000008560532,0.0000071761956,7.9220536e-7,0.001046489,0.95965844,0.0006477443,0.0179498,0.00020573457,0.019018194],"study_design_scores_gemma":[0.00018890043,0.00034062687,0.007907618,0.00003693445,8.063308e-7,6.6718434e-7,0.00021471403,0.98675364,0.0020504624,0.00006248661,0.0023549881,0.00008817683],"about_ca_topic_score_codex":0.00041235387,"about_ca_topic_score_gemma":0.00023016403,"teacher_disagreement_score":0.9246344,"about_ca_system_score_codex":0.00005640941,"about_ca_system_score_gemma":0.00019100327,"threshold_uncertainty_score":0.37334618},"labels":[],"label_agreement":null},{"id":"W1998193115","doi":"10.1007/s10479-010-0715-0","title":"Using local search to speed up filtering algorithms for some NP-hard constraints","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Theory of computation; Local search (optimization); Algorithm; Computer science; Local consistency; Filter (signal processing); Consistency (knowledge bases); Computational complexity theory; Graph; Search tree; Search algorithm; Substructure; Constraint (computer-aided design); Guided Local Search; Mathematical optimization; Mathematics; Constraint satisfaction problem; Theoretical computer science; Artificial intelligence","score_opus":0.40089166799307197,"score_gpt":0.5075783819447462,"score_spread":0.10668671395167428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998193115","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34739488,0.000022972617,0.65055156,0.0006641248,0.00027784257,0.000592547,0.000085884385,0.00007366141,0.00033649954],"genre_scores_gemma":[0.66262835,0.000018626444,0.33666623,0.00006096606,0.0002082636,0.00003343333,0.000018871628,0.00005001391,0.00031525813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981779,0.00014442603,0.00036098587,0.00025209115,0.00047697386,0.00058761565],"domain_scores_gemma":[0.99798614,0.00029945688,0.000008898757,0.00037537672,0.001100267,0.00022988216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029894079,0.00012711177,0.00020871076,0.00050023384,0.0002996888,0.00015882395,0.00032277982,0.000102923164,0.0002443507],"category_scores_gemma":[0.0007633409,0.0001396348,0.000067059846,0.00061050616,0.00024752584,0.0002956628,0.000112151574,0.0004945618,0.000037137346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000886413,0.00001872524,0.00002046934,0.000045593828,0.000024546625,0.0000013972483,0.00031784878,0.7112515,0.26734957,0.0014687419,0.000563349,0.018929392],"study_design_scores_gemma":[0.00017762701,0.00004986934,0.00008467542,0.00002317267,0.000002039705,0.000007821751,0.00016821634,0.736266,0.2625711,0.000042417807,0.0004942075,0.000112811125],"about_ca_topic_score_codex":0.00007749744,"about_ca_topic_score_gemma":0.0000225085,"teacher_disagreement_score":0.31523347,"about_ca_system_score_codex":0.00003137809,"about_ca_system_score_gemma":0.00016090782,"threshold_uncertainty_score":0.5694142},"labels":[],"label_agreement":null},{"id":"W1999858663","doi":"10.1007/s10479-014-1651-1","title":"A stochastic semidefinite programming approach for bounds on option pricing under regime switching","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Semidefinite programming; Upper and lower bounds; Mathematical optimization; Stochastic programming; Mathematics; Theory of computation; Bounded function; Markov chain; Controllability; Dynamic programming; Applied mathematics; Algorithm","score_opus":0.24383301383273573,"score_gpt":0.39031142941572866,"score_spread":0.14647841558299293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999858663","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014212239,0.00026013693,0.9793773,0.0019163209,0.00003822307,0.00078427704,0.00003727911,0.000024885067,0.0033493396],"genre_scores_gemma":[0.9691043,0.0000219177,0.029368144,0.00018612159,0.0001642494,0.0008023979,0.00005871408,0.00002632172,0.0002678564],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855655,0.000016134392,0.00049916824,0.00041388787,0.00011399302,0.00040027744],"domain_scores_gemma":[0.9987675,0.00027978665,0.00009534531,0.0003587832,0.00042040684,0.00007820612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021282248,0.00011185508,0.00026165397,0.00045375398,0.00062547077,0.0001744022,0.0002565211,0.000091477596,0.000007327549],"category_scores_gemma":[0.0010909259,0.00012167873,0.00008702321,0.0006548784,0.00007861533,0.00018581582,0.000055624467,0.00023192422,0.0000592529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021979093,0.00016803975,0.0000150209125,0.00004876699,0.00001680857,2.7460016e-8,0.00028590873,0.03408797,0.00012229652,0.9607994,0.00009642552,0.0043373345],"study_design_scores_gemma":[0.00055229384,0.0006700136,0.00082238135,0.00008340414,0.0000057831685,0.0000023431455,0.00033434667,0.6038819,0.00025924097,0.3877035,0.005376807,0.00030799],"about_ca_topic_score_codex":0.00020497444,"about_ca_topic_score_gemma":0.000016032125,"teacher_disagreement_score":0.95489204,"about_ca_system_score_codex":0.00003764846,"about_ca_system_score_gemma":0.000061247556,"threshold_uncertainty_score":0.49619144},"labels":[],"label_agreement":null},{"id":"W1999987607","doi":"10.1007/s10479-014-1527-4","title":"Flow-based integer linear programs to solve the weekly log-truck scheduling problem","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Truck; Theory of computation; Integer programming; Computer science; Scheduling (production processes); Linear programming; Integer (computer science); Mathematical optimization; Operations research; Mathematics; Algorithm; Engineering","score_opus":0.16754097586295918,"score_gpt":0.4287448416465164,"score_spread":0.2612038657835572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999987607","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06393562,0.00008026179,0.921912,0.01042772,0.000083084706,0.0009214433,0.0000070877145,0.00018193667,0.0024508408],"genre_scores_gemma":[0.4582037,0.000014560749,0.5410337,0.00017547721,0.00012984312,0.00017019396,0.00002003659,0.000041457333,0.00021105824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807215,0.0003374669,0.00037720974,0.00022250159,0.00052253006,0.00046811503],"domain_scores_gemma":[0.9977619,0.00033384864,0.00001354823,0.00052362325,0.0012277581,0.00013933658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043415623,0.00012971545,0.00017664224,0.00027601206,0.0003268251,0.00017640759,0.00044324435,0.000092178314,0.00007406664],"category_scores_gemma":[0.001182636,0.00010100366,0.00006797482,0.0010840389,0.00011860362,0.0001425453,0.00009065086,0.0004840866,0.00012506454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075513085,0.00004105625,0.0001068019,0.000046558333,0.000021404801,3.1355202e-7,0.00046510913,0.9798982,0.0019997684,0.0018205935,0.0008175937,0.014775016],"study_design_scores_gemma":[0.0001337125,0.00014308057,0.000080722864,0.00008196259,0.0000029978903,7.3720366e-7,0.00015062426,0.9790105,0.016296368,0.00009856295,0.0038886403,0.0001120477],"about_ca_topic_score_codex":0.000059761005,"about_ca_topic_score_gemma":0.000062216925,"teacher_disagreement_score":0.39426807,"about_ca_system_score_codex":0.000024367086,"about_ca_system_score_gemma":0.00010821616,"threshold_uncertainty_score":0.41188097},"labels":[],"label_agreement":null},{"id":"W1999993900","doi":"10.1007/s10479-011-0983-3","title":"An efficient memetic algorithm for the graph partitioning problem","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Memetic algorithm; Crossover; Graph partition; Tabu search; Theory of computation; Computer science; Partition (number theory); Mathematical optimization; Vertex (graph theory); Graph; Operator (biology); Algorithm; Mathematics; Local search (optimization); Theoretical computer science; Combinatorics; Artificial intelligence","score_opus":0.2813694063939959,"score_gpt":0.4229850109156691,"score_spread":0.1416156045216732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999993900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018202206,0.0006909059,0.9758065,0.0002322979,0.000044566845,0.0011222358,0.000039542974,0.00017934294,0.0036824094],"genre_scores_gemma":[0.94457376,0.0002558506,0.054366093,0.000018412167,0.000041941516,0.0006407353,0.000010884209,0.000018480921,0.00007381877],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922943,0.00006272864,0.00016567785,0.00010015029,0.00020185397,0.00024018256],"domain_scores_gemma":[0.9991231,0.00008397788,0.000005315881,0.00025531565,0.0004830297,0.000049248178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012029229,0.00005816322,0.000073307725,0.00016216114,0.0002889748,0.00005355705,0.00022042533,0.000038065235,0.00008303539],"category_scores_gemma":[0.00003301184,0.00004283642,0.000042522424,0.00031343524,0.00009213248,0.000105070074,0.000016064037,0.00012649262,0.000008248219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028492364,0.00093616766,0.00010763223,0.00022328859,0.00032172113,0.000005417849,0.011578718,0.35236743,0.05111108,0.09277878,0.027864264,0.462677],"study_design_scores_gemma":[0.00007189998,0.00026856823,0.00023335709,0.00002344878,0.0000051488396,0.0000013025083,0.00028018595,0.8035454,0.19273143,0.0019189008,0.00083934126,0.00008099098],"about_ca_topic_score_codex":0.00010503489,"about_ca_topic_score_gemma":0.00002964633,"teacher_disagreement_score":0.9263716,"about_ca_system_score_codex":0.0000059127055,"about_ca_system_score_gemma":0.00002461622,"threshold_uncertainty_score":0.22225899},"labels":[],"label_agreement":null},{"id":"W2000873366","doi":"10.1007/s10479-009-0550-3","title":"Portfolio selection using λ mean and hybrid entropy","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Portfolio; Efficient frontier; Portfolio optimization; Entropy (arrow of time); Mathematical optimization; Theory of computation; Computer science; Fuzzy logic; Econometrics; Modern portfolio theory; Mathematics; Economics; Artificial intelligence; Algorithm; Financial economics","score_opus":0.3411868796934861,"score_gpt":0.496336729978065,"score_spread":0.1551498502845789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000873366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922946,0.00017808378,0.0047482657,0.00082752376,0.000022352804,0.00032543158,0.000009966168,0.000020558957,0.0015731889],"genre_scores_gemma":[0.9892378,0.00015001009,0.009712435,0.00003828104,0.00008300247,0.0000051209427,0.0000075383728,0.000008610254,0.00075720827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989338,0.00014718487,0.00024447232,0.00014110429,0.00034036447,0.00019305962],"domain_scores_gemma":[0.9988914,0.00006357569,0.00002491333,0.00014335616,0.00081553444,0.00006121391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009931386,0.000060963255,0.00012613411,0.00024854968,0.00026377855,0.000085941385,0.00006466087,0.000035897534,0.00007566628],"category_scores_gemma":[0.00033772862,0.000055336128,0.000026798833,0.0003305747,0.000041993957,0.00022890244,0.000019273926,0.00011451876,0.0000027616463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017230082,0.0013914219,0.001569504,0.00032781216,0.0001929737,0.000025631538,0.0042080358,0.06169933,0.14421712,0.6967528,0.07498079,0.014462313],"study_design_scores_gemma":[0.0007454891,0.00096102926,0.0016637332,0.0002299364,0.000024416544,0.000107815096,0.00075944024,0.8317182,0.11455682,0.04712674,0.001743127,0.00036321743],"about_ca_topic_score_codex":0.00015807833,"about_ca_topic_score_gemma":0.000043192667,"teacher_disagreement_score":0.7700189,"about_ca_system_score_codex":0.000015081467,"about_ca_system_score_gemma":0.00007880213,"threshold_uncertainty_score":0.22565417},"labels":[],"label_agreement":null},{"id":"W2001490112","doi":"10.1007/s10479-010-0813-z","title":"Using size for bounding expressions of graph invariants","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Combinatorics; Mathematics; Bounding overwatch; Vertex (graph theory); Graph; Theory of computation; Upper and lower bounds; Discrete mathematics; Computer science; Algorithm; Mathematical analysis","score_opus":0.41827483331012116,"score_gpt":0.5393114654582573,"score_spread":0.12103663214813609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001490112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6195061,0.00007741426,0.37682724,0.0018009659,0.00015623657,0.0007328679,0.000040280967,0.00002377728,0.0008350998],"genre_scores_gemma":[0.824229,0.00003134038,0.17537324,0.000023847711,0.000037993097,0.000065158136,0.000002029116,0.000010884197,0.00022651996],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978316,0.00028057437,0.0003514289,0.00032141068,0.00070897036,0.00050603715],"domain_scores_gemma":[0.9952387,0.0014858539,0.00004155817,0.0008981952,0.002183466,0.00015220344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035366304,0.00008813807,0.00018830679,0.0006133108,0.0006623736,0.00014200083,0.0013342028,0.000080249585,0.00006140238],"category_scores_gemma":[0.0040844013,0.00007997143,0.0000973805,0.0014794458,0.00045443626,0.00090169656,0.00046545416,0.00042031083,0.0000041364065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016812115,0.00009853287,0.00010081283,0.000021784317,0.000013274647,9.557906e-7,0.00038229994,0.0009587123,0.63688684,0.36031854,0.00017858738,0.0010228523],"study_design_scores_gemma":[0.00043347655,0.0002728823,0.0007098306,0.00009239261,0.0000022964102,0.0000075488615,0.0002532617,0.07859649,0.73775,0.1809734,0.00073581847,0.00017262707],"about_ca_topic_score_codex":0.00009838289,"about_ca_topic_score_gemma":0.00008380177,"teacher_disagreement_score":0.20472287,"about_ca_system_score_codex":0.0000067427286,"about_ca_system_score_gemma":0.00040443472,"threshold_uncertainty_score":0.5094509},"labels":[],"label_agreement":null},{"id":"W2005299742","doi":"10.1007/s10479-012-1059-8","title":"Makespan minimization for parallel machines scheduling with multiple availability constraints","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Job shop scheduling; Lexicographical order; Theory of computation; Mathematical optimization; Enumeration; Computer science; Minification; Integer programming; Scheduling (production processes); Branch and bound; Linear programming; Algorithm; Mathematics; Schedule; Discrete mathematics","score_opus":0.14004727428827127,"score_gpt":0.38869455033310835,"score_spread":0.24864727604483708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005299742","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43518582,0.00060886703,0.56100804,0.00076765975,0.00014282155,0.00090105465,0.00009744685,0.00014487685,0.0011434032],"genre_scores_gemma":[0.72020286,0.00006131093,0.27927172,0.000020671012,0.0000905943,0.000115848634,0.00008193262,0.000021396334,0.00013369787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888504,0.00007930259,0.0002560155,0.00013785702,0.0002686563,0.0003731196],"domain_scores_gemma":[0.9985111,0.00025798514,0.000013058333,0.00022444088,0.00086687616,0.00012657484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096806674,0.00010253411,0.000142963,0.00018284471,0.00021974884,0.000062080086,0.000121317404,0.00007226061,0.00014628046],"category_scores_gemma":[0.0006626957,0.00008986408,0.000038593156,0.0003651747,0.00017388827,0.00030453436,0.000017514678,0.00015361635,0.000019448684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033753713,0.00010388836,0.006517771,0.000068893765,0.000042006075,1.4285335e-7,0.0005700619,0.98710805,0.0005594423,0.0009329978,0.0003032265,0.0037597634],"study_design_scores_gemma":[0.00043232873,0.00006174268,0.0018266382,0.000028268532,0.0000047457393,0.0000022862582,0.00036117376,0.9910266,0.005790422,0.000021439455,0.0003241559,0.00012020181],"about_ca_topic_score_codex":0.000022514825,"about_ca_topic_score_gemma":0.000043987497,"teacher_disagreement_score":0.28501704,"about_ca_system_score_codex":0.00001509945,"about_ca_system_score_gemma":0.00006082889,"threshold_uncertainty_score":0.36645508},"labels":[],"label_agreement":null},{"id":"W2007073703","doi":"10.1007/s10479-011-0885-4","title":"Workforce-constrained maintenance scheduling for military aircraft fleet: a case study","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Schedule; Theory of computation; Integer programming; Operations research; Computer science; Scheduling (production processes); Aircraft maintenance; Job shop scheduling; Constraint (computer-aided design); Workforce; Constraint programming; Fleet management; Mathematical optimization; Engineering; Aeronautics; Operations management; Stochastic programming; Mathematics; Algorithm","score_opus":0.22534984035422112,"score_gpt":0.399505614178517,"score_spread":0.17415577382429587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007073703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9297081,0.0003998582,0.06597085,0.0002496698,0.00009370158,0.0016246937,0.000033154167,0.000086219276,0.0018337332],"genre_scores_gemma":[0.9686473,0.00023330508,0.030377533,0.000022996432,0.000041133877,0.0003811996,0.000008476866,0.00002632289,0.00026174975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986754,0.00009526441,0.0003735178,0.00022562414,0.00021008308,0.00042009007],"domain_scores_gemma":[0.9983152,0.00012259051,0.000008572178,0.000380836,0.0010779093,0.000094872885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001555241,0.00011485956,0.00017709973,0.0002242482,0.00025635966,0.000024113895,0.00018103034,0.000072124545,0.00006706065],"category_scores_gemma":[0.00052886945,0.00010807273,0.00007510464,0.0004257266,0.0001647717,0.00031254528,0.00003748221,0.0002152329,0.000010674491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011034921,0.0005898537,0.000809036,0.00016313,0.0001202892,0.00013889595,0.009702291,0.9752115,0.00090449053,0.0038704325,0.0012264117,0.007153304],"study_design_scores_gemma":[0.00076187064,0.00069799885,0.0004158413,0.00010386935,0.000011910104,0.00006820083,0.017020458,0.9761263,0.0036623976,0.00055078196,0.00034914725,0.00023122672],"about_ca_topic_score_codex":0.0010244265,"about_ca_topic_score_gemma":0.0012207183,"teacher_disagreement_score":0.038939167,"about_ca_system_score_codex":0.000024224493,"about_ca_system_score_gemma":0.00008060028,"threshold_uncertainty_score":0.4407078},"labels":[],"label_agreement":null},{"id":"W2008645045","doi":"10.1023/b:anor.0000030687.72169.c7","title":"Scheduling Three-Operation Jobs in a Two-Machine Flow Shop to Minimize Makespan","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Job shop scheduling; Theory of computation; Computer science; Idle; Mathematical optimization; Flow shop scheduling; Approximation algorithm; Scheduling (production processes); Schedule; Time complexity; Algorithm; Mathematics","score_opus":0.12638373061212133,"score_gpt":0.4156692742237378,"score_spread":0.28928554361161646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008645045","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5818076,0.0006349976,0.4096013,0.005653541,0.00017120269,0.00062781,0.00003358915,0.00013575568,0.0013342081],"genre_scores_gemma":[0.7371928,0.00011455329,0.2622649,0.00009727549,0.000090245914,0.00009021267,0.000044751145,0.000030528314,0.000074696174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984048,0.00007784387,0.00040877124,0.00024063588,0.00046562045,0.000402303],"domain_scores_gemma":[0.9989393,0.000073245574,0.000007717366,0.00031902533,0.00050558994,0.00015513976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010975088,0.00013556377,0.00019813601,0.00069707126,0.00017796145,0.00015107442,0.00023442712,0.00006866281,0.00015950062],"category_scores_gemma":[0.0004297421,0.00013933593,0.000046992336,0.001148723,0.000040457177,0.00027688028,0.000052386935,0.00037240717,0.0001536376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015889977,0.0000704881,0.00031330343,0.000015606634,0.000015162195,0.0000045429406,0.0007950224,0.9920128,0.002569211,0.0010397031,0.000034675137,0.0031135934],"study_design_scores_gemma":[0.0006593779,0.000056056404,0.0007408762,0.00008003171,0.0000018039616,0.0000026466312,0.00023019058,0.9833672,0.014532421,0.000119552824,0.00006145538,0.00014840116],"about_ca_topic_score_codex":0.00048370025,"about_ca_topic_score_gemma":0.004003053,"teacher_disagreement_score":0.15538524,"about_ca_system_score_codex":0.00006343874,"about_ca_system_score_gemma":0.00014020893,"threshold_uncertainty_score":0.56819546},"labels":[],"label_agreement":null},{"id":"W2009545310","doi":"10.1007/s10479-008-0439-6","title":"Introduction to the special volume on constraint programming, artificial intelligence, and operations research","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Theory of computation; Computer science; Volume (thermodynamics); Constraint (computer-aided design); Constraint programming; Operations research; Artificial intelligence; Mathematical optimization; Programming language; Mathematics; Stochastic programming","score_opus":0.28803532810644444,"score_gpt":0.44133032527962474,"score_spread":0.1532949971731803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009545310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10798947,0.000071258786,0.51446325,0.36990672,0.00071811146,0.0025917212,0.000027452326,0.00009888044,0.0041331127],"genre_scores_gemma":[0.9742017,0.00026525167,0.020880824,0.00026546392,0.0022749177,0.00019658978,0.000017481358,0.000011251408,0.0018865428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996904,0.00068215415,0.00041231792,0.00049549574,0.0010576161,0.00044837568],"domain_scores_gemma":[0.9966667,0.00018937187,0.000013991561,0.0006129835,0.0023409463,0.00017600504],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0034728085,0.00010884168,0.00013502578,0.00079526444,0.0020803798,0.0005242902,0.00052835495,0.00007240483,0.00042862093],"category_scores_gemma":[0.001451377,0.00008773209,0.00004290131,0.002108971,0.0008556587,0.0004762155,0.00024242874,0.0005755937,0.00032800916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030176252,0.00024672574,0.00006502847,0.000005469808,0.000019097166,0.0000063643256,0.0045778654,0.1094593,0.00041624423,0.5522716,0.03705291,0.29584923],"study_design_scores_gemma":[0.00023271149,0.0029246737,0.00661258,0.0000698908,0.0000054559673,0.00020062573,0.005030851,0.69472164,0.021606818,0.0034583027,0.26454234,0.00059415365],"about_ca_topic_score_codex":0.00025193163,"about_ca_topic_score_gemma":0.001279264,"teacher_disagreement_score":0.8662122,"about_ca_system_score_codex":0.000042009273,"about_ca_system_score_gemma":0.0004659559,"threshold_uncertainty_score":0.99921876},"labels":[],"label_agreement":null},{"id":"W2013421795","doi":"10.1007/s10479-011-0982-4","title":"Controlling pollution and environmental absorption capacity","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Thermodynamics and Statistical Mechanics","field":"Physics and Astronomy","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Absorption capacity; Pollution; Environmental science; Stock (firearms); Absorption (acoustics); Carrying capacity; Natural resource economics; Economics; Materials science; Engineering; Ecology","score_opus":0.1834047899137453,"score_gpt":0.37707503501676654,"score_spread":0.19367024510302125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013421795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87046415,0.000026012902,0.12654676,0.00014478063,0.000018374983,0.00014107485,0.0002295457,0.0000032539963,0.002426078],"genre_scores_gemma":[0.99745196,0.000029372242,0.0023332774,0.000017373468,0.00003113207,0.000014435966,0.000027373544,0.0000048867328,0.00009018042],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946123,0.000059183847,0.00011287087,0.00010029083,0.00012881774,0.00013761234],"domain_scores_gemma":[0.9997578,0.00002764107,0.000011049575,0.00008874032,0.00006383973,0.000050928214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026963634,0.000043029857,0.00007031787,0.00004982383,0.0001586038,0.000013776673,0.000045435114,0.000017628949,0.00027054583],"category_scores_gemma":[0.000013993107,0.00003996308,0.000018919121,0.000051533665,0.000096891774,0.00010140158,0.000027123502,0.00010365254,0.000005293776],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023634428,0.00013397561,0.00031405242,0.0000031384657,0.000022767053,2.6305202e-7,0.00046851658,0.00031451046,0.034494624,0.95557487,0.00001641005,0.008633224],"study_design_scores_gemma":[0.0008409506,0.00049866823,0.010212579,0.000029730189,0.000013151126,0.0000012256584,0.002606419,0.549957,0.055213083,0.37984455,0.0005016086,0.00028105715],"about_ca_topic_score_codex":0.0003086787,"about_ca_topic_score_gemma":0.000012311483,"teacher_disagreement_score":0.5757303,"about_ca_system_score_codex":0.0000047391904,"about_ca_system_score_gemma":0.0000112480775,"threshold_uncertainty_score":0.29622874},"labels":[],"label_agreement":null},{"id":"W2014129541","doi":"10.1007/s10479-014-1761-9","title":"A new rank dependent utility approach to model risk averse preferences in portfolio optimization","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Portfolio; Portfolio optimization; Risk aversion (psychology); Computer science; Distortion (music); Theory of computation; Mathematical optimization; Rank (graph theory); Econometrics; Parametric statistics; Selection (genetic algorithm); Function (biology); Expected utility hypothesis; Mathematical economics; Economics; Mathematics; Artificial intelligence; Algorithm; Statistics; Financial economics","score_opus":0.5797632174622376,"score_gpt":0.5203476363812555,"score_spread":0.059415581080982105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014129541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14475305,0.00015327823,0.80373126,0.0009199818,0.0000720495,0.00094081945,0.00005887708,0.000020279,0.04935038],"genre_scores_gemma":[0.9156183,0.0007563619,0.07873763,0.00006327885,0.000044620087,0.00006125387,0.00004044857,0.000011038554,0.004667094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99427396,0.0009706881,0.0009204858,0.000606365,0.0028151304,0.0004133954],"domain_scores_gemma":[0.9950723,0.00024565516,0.00008985336,0.0008029335,0.0033061036,0.00048314274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012735449,0.00013736174,0.00030709777,0.0013935796,0.00021052305,0.0003790434,0.00084827025,0.00012936884,0.00021048586],"category_scores_gemma":[0.007028836,0.000109404915,0.00006882538,0.0030847825,0.00008954571,0.000960204,0.00023336301,0.00031035335,0.000117894124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012020598,0.00019059649,0.0056888876,0.0000011465057,0.0000068363674,8.4313655e-7,0.0020608923,0.9522055,0.000005456474,0.0010454472,0.02342075,0.01525347],"study_design_scores_gemma":[0.00039569376,0.000110869245,0.0021665955,0.000007642756,0.000003010231,0.0000012869606,0.0014840652,0.9892449,0.00032555987,0.005501231,0.00064523355,0.0001139079],"about_ca_topic_score_codex":0.0037899858,"about_ca_topic_score_gemma":0.0009818436,"teacher_disagreement_score":0.7708652,"about_ca_system_score_codex":0.000034642035,"about_ca_system_score_gemma":0.0013846352,"threshold_uncertainty_score":0.84146804},"labels":[],"label_agreement":null},{"id":"W2014530950","doi":"10.1007/s10479-008-0339-9","title":"Optimal location with equitable loads","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Theory of computation; Tabu search; Facility location problem; Heuristic; Computer science; Path (computing); Tree (set theory); Mathematics; Algorithm; Combinatorics","score_opus":0.2937564709182184,"score_gpt":0.3996784297114063,"score_spread":0.10592195879318794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014530950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94836426,0.00016856886,0.005568886,0.009128059,0.000069485315,0.0004903739,0.0000024949668,0.00005623693,0.036151644],"genre_scores_gemma":[0.99270594,0.00010228311,0.00051741046,0.00043601714,0.00015588042,0.00006951313,0.00005198074,0.000010640513,0.005950353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856204,0.000024019922,0.00023639634,0.00020961816,0.0006248402,0.0003430992],"domain_scores_gemma":[0.9974495,0.000012645,0.000012142978,0.00032618686,0.002182867,0.000016651538],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001037647,0.000083262676,0.00010672008,0.00043809332,0.00061463343,0.00010514335,0.00024672813,0.000030760242,0.00088520744],"category_scores_gemma":[0.00018815856,0.000071334085,0.000027600741,0.0014053739,0.00018418761,0.0011603842,0.0001487006,0.00011946771,0.0008167947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001235167,0.00061105104,0.0030409144,0.0002789424,0.00006954143,0.00000916577,0.0003897836,0.78959703,0.00075639546,0.10398551,0.09911998,0.0020181402],"study_design_scores_gemma":[0.0015161695,0.00036116742,0.052939296,0.00017395888,0.000031004034,0.00001035121,0.0035430994,0.6741366,0.006029896,0.00041748694,0.26002508,0.00081592076],"about_ca_topic_score_codex":0.0046226433,"about_ca_topic_score_gemma":0.0011984621,"teacher_disagreement_score":0.16090511,"about_ca_system_score_codex":0.00001155295,"about_ca_system_score_gemma":0.00009470937,"threshold_uncertainty_score":0.9999612},"labels":[],"label_agreement":null},{"id":"W2015067034","doi":"10.1007/s10479-010-0806-y","title":"An interior-point Benders based branch-and-cut algorithm for mixed integer programs","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Benders' decomposition; Branch and cut; Mathematics; Theory of computation; Cutting-plane method; Mathematical optimization; Integer programming; Integer (computer science); Branch and bound; Interior point method; Steiner tree problem; Facility location problem; Algorithm; Point (geometry); Linear programming relaxation; Computer science","score_opus":0.13655247256445424,"score_gpt":0.44150555228973304,"score_spread":0.3049530797252788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015067034","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16694309,0.000042906642,0.83047,0.0012674311,0.00016206218,0.0006928781,0.000032971275,0.0001294769,0.00025915887],"genre_scores_gemma":[0.6930179,0.000022223187,0.30648488,0.00003877304,0.00006884748,0.00018847047,0.0000613879,0.000036689034,0.00008084996],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987593,0.0001632411,0.00028270445,0.00021042197,0.00024856688,0.00033573917],"domain_scores_gemma":[0.9984454,0.00017950954,0.000011660943,0.00034951422,0.0008679154,0.0001459795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022244768,0.00011029693,0.00016244223,0.00029178156,0.0001817043,0.00017827321,0.00022215045,0.000110304725,0.00007434417],"category_scores_gemma":[0.00039045396,0.00010852411,0.00005348984,0.00034772925,0.00014359142,0.00029062002,0.00003407482,0.0003919568,0.0000046401938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002424964,0.00018712852,0.00025207028,0.00014855135,0.00008035546,0.0000012853619,0.0012967142,0.14112549,0.124129556,0.0016139908,0.0013665952,0.729774],"study_design_scores_gemma":[0.00024183677,0.0001762105,0.00015017558,0.000023228566,0.0000029215278,0.0000017594406,0.00018193593,0.90785646,0.09031888,0.000099693316,0.00084007264,0.000106841886],"about_ca_topic_score_codex":0.000074138545,"about_ca_topic_score_gemma":0.00031811782,"teacher_disagreement_score":0.76673096,"about_ca_system_score_codex":0.000013092429,"about_ca_system_score_gemma":0.00008121122,"threshold_uncertainty_score":0.44254848},"labels":[],"label_agreement":null},{"id":"W2017280802","doi":"10.1007/s10479-011-0903-6","title":"Estimation of potential gains from mergers in multiple periods: a comparison of stochastic frontier analysis and Data Envelopment Analysis","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Data envelopment analysis; Stochastic frontier analysis; Theory of computation; Frontier; Computation; Envelopment; Computer science; Econometrics; Estimation; Mergers and acquisitions; Panel data; Operations research; Industrial organization; Economics; Statistics; Microeconomics; Finance; Mathematics; Production (economics); Management; Algorithm","score_opus":0.6025119014882832,"score_gpt":0.5591979469723991,"score_spread":0.043313954515884046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017280802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7321337,0.00027821632,0.2670083,0.00016638114,0.000014707306,0.00013948295,0.00020905251,0.000002511311,0.000047664787],"genre_scores_gemma":[0.9809031,0.00003556299,0.018758917,0.000005814562,0.0000052790333,0.000008919561,0.00022553852,0.000005013936,0.000051874744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944494,0.000879012,0.0015585425,0.0006477227,0.0022087097,0.0002566572],"domain_scores_gemma":[0.99574566,0.0009216765,0.000257706,0.0014626975,0.0015157021,0.00009653086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007573871,0.00011718372,0.00086063676,0.004842052,0.00019063058,0.000089797715,0.0011700474,0.000078546764,0.0005144551],"category_scores_gemma":[0.0060456903,0.00009791954,0.00019520438,0.009636066,0.00054005475,0.00048006183,0.00045339967,0.00017315631,0.000007698189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007922216,0.00060843804,0.11163787,0.000004344234,0.0014972596,0.0000011347568,0.008472088,0.8663373,0.0021292197,0.000056557765,0.00018244148,0.008994126],"study_design_scores_gemma":[0.00013133406,0.000047947255,0.19672783,0.000009950587,0.00037576965,3.4042934e-8,0.0030723566,0.7960519,0.0033826744,0.00012988754,0.000003011044,0.00006728696],"about_ca_topic_score_codex":0.016172672,"about_ca_topic_score_gemma":0.015328877,"teacher_disagreement_score":0.24876942,"about_ca_system_score_codex":0.000016874086,"about_ca_system_score_gemma":0.00020845365,"threshold_uncertainty_score":0.99037874},"labels":[],"label_agreement":null},{"id":"W2018608330","doi":"10.1007/s10479-013-1501-6","title":"Special section on behavioral considerations in developing and applying operations research models","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Theory of computation; Section (typography); Special section; Computer science; Management science; Operations research; Economics; Mathematics; Engineering; Algorithm; Engineering physics","score_opus":0.5149315316975448,"score_gpt":0.47738397457240506,"score_spread":0.03754755712513974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018608330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93990684,0.00004348412,0.00087775715,0.027337663,0.00024611462,0.002262512,0.0000072635416,0.000034231052,0.029284168],"genre_scores_gemma":[0.99457645,0.00009388029,0.0008475571,0.00072337355,0.0019970753,0.00091958855,0.000049331073,0.000018975994,0.00077376125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975184,0.0002397422,0.00048742685,0.0003827243,0.00085957936,0.00051212456],"domain_scores_gemma":[0.99761134,0.00019693989,0.000016767413,0.00029734476,0.001847933,0.000029678073],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0034238673,0.00012746955,0.00018844653,0.001723569,0.001379589,0.0013379359,0.00018275667,0.00009398577,0.0007757164],"category_scores_gemma":[0.00043122997,0.00012807881,0.000035495013,0.0012660794,0.00026432736,0.002669321,0.00030635425,0.0005471759,0.00024327093],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018389763,0.0004635983,0.0005977004,0.00009527238,0.000017863573,0.0000071771115,0.00096957444,0.08408958,0.00071688055,0.8668922,0.04310619,0.0030255388],"study_design_scores_gemma":[0.0024351627,0.00049576716,0.03085635,0.00070953486,0.000024089582,0.000007651599,0.023728658,0.7113244,0.002198288,0.14336395,0.08353085,0.0013253241],"about_ca_topic_score_codex":0.01684157,"about_ca_topic_score_gemma":0.017757136,"teacher_disagreement_score":0.72352827,"about_ca_system_score_codex":0.0000560146,"about_ca_system_score_gemma":0.00014556147,"threshold_uncertainty_score":0.9999205},"labels":[],"label_agreement":null},{"id":"W2021293262","doi":"10.1007/s10479-015-1827-3","title":"Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; China Scholarship Council; Tongji University; National Natural Science Foundation of China; Worcester Polytechnic Institute","keywords":"Data envelopment analysis; Bounded function; Likert scale; Theory of computation; Scale (ratio); Computer science; Integer (computer science); Mathematical optimization; Limit (mathematics); Mathematics; Econometrics; Statistics; Algorithm","score_opus":0.49632891875343194,"score_gpt":0.5551049537861926,"score_spread":0.05877603503276069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021293262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92456764,0.0013410382,0.042888585,0.030160837,0.000016443844,0.0003492586,0.00013961659,0.000008059783,0.00052853505],"genre_scores_gemma":[0.9962321,0.0004274396,0.002636353,0.00015721004,0.000017801493,0.000027684433,0.0002934306,0.0000054687125,0.000202547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99485815,0.00075524463,0.0008066187,0.0011040345,0.0021418585,0.00033408828],"domain_scores_gemma":[0.99601966,0.0005971433,0.000057835023,0.0023995533,0.0006996355,0.0002261763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018709932,0.00011041784,0.00034352357,0.0026143254,0.00021886379,0.0004597921,0.0022117337,0.000060966355,0.0000100319685],"category_scores_gemma":[0.0050791595,0.00008760732,0.000021620226,0.0073604817,0.00038025845,0.00081853743,0.002059232,0.00016827107,0.000012515823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057021255,0.0031315493,0.32097945,0.000037393125,0.0005296357,0.000044017084,0.023860367,0.33158427,0.0042205607,0.06042818,0.060108665,0.19450569],"study_design_scores_gemma":[0.00021172375,0.000058614307,0.10413477,0.000019763063,0.000011792323,0.0000019087513,0.0013561561,0.88388646,0.00012763923,0.0029557678,0.007102573,0.00013281326],"about_ca_topic_score_codex":0.0046860287,"about_ca_topic_score_gemma":0.055883892,"teacher_disagreement_score":0.5523022,"about_ca_system_score_codex":0.000029438599,"about_ca_system_score_gemma":0.0003754557,"threshold_uncertainty_score":0.96134377},"labels":[],"label_agreement":null},{"id":"W2021665984","doi":"10.1007/s10479-005-2038-0","title":"Maximizing Trip Coverage in the Location of a Single Rapid Transit Alignment","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Heuristics; Theory of computation; Heuristic; Maximization; Computer science; Greedy algorithm; Mathematical optimization; Extension (predicate logic); Upper and lower bounds; Simple (philosophy); Computational complexity theory; Transit (satellite); Algorithm; Mathematics; Public transport; Transport engineering; Engineering","score_opus":0.2356324665256801,"score_gpt":0.4466647061607565,"score_spread":0.2110322396350764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021665984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9130157,0.0010150435,0.014448226,0.04584089,0.000046707853,0.0009787537,0.000024107685,0.000020892636,0.02460968],"genre_scores_gemma":[0.99821013,0.0005050338,0.0007712635,0.00013341873,0.00004005018,0.000025486046,0.000027408389,0.0000034801838,0.00028371855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99834424,0.0005001883,0.000269539,0.00009798696,0.0006182819,0.00016976173],"domain_scores_gemma":[0.9989729,0.00018904988,0.000024651486,0.00012014056,0.00066487706,0.000028380622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002988445,0.00003833937,0.000080133104,0.00020105076,0.00028239767,0.00004904943,0.00017904393,0.00004486274,0.00010369036],"category_scores_gemma":[0.0002676725,0.000032523196,0.00002529277,0.0010399749,0.00014904574,0.00026981224,0.000003197333,0.000096537246,0.0000053733884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007259577,0.0007509284,0.0010668347,0.000032898417,0.000017881268,0.0000016624365,0.1526456,0.772374,0.003789108,0.040947627,0.0017838385,0.02651705],"study_design_scores_gemma":[0.0072716596,0.0028789241,0.17823961,0.0015717897,0.00007967168,0.000005007806,0.26048285,0.10422957,0.1759715,0.003194711,0.26464936,0.0014253571],"about_ca_topic_score_codex":0.0016733542,"about_ca_topic_score_gemma":0.004664484,"teacher_disagreement_score":0.6681444,"about_ca_system_score_codex":0.000021691969,"about_ca_system_score_gemma":0.00021778149,"threshold_uncertainty_score":0.26028916},"labels":[],"label_agreement":null},{"id":"W2022317074","doi":"10.1007/s10479-010-0736-8","title":"Facility location for large-scale emergencies","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":153,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Node (physics); Facility location problem; Theory of computation; Computer science; Scale (ratio); Center (category theory); Path (computing); Operations research; Location model; Mathematical optimization; Computer network; Geography; Mathematics; Algorithm; Engineering; Cartography","score_opus":0.21629948881006314,"score_gpt":0.4215558370122323,"score_spread":0.20525634820216918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022317074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95771766,0.00007192438,0.014671734,0.014209952,0.00064574194,0.0014198166,0.000082386854,0.000078883895,0.01110193],"genre_scores_gemma":[0.99574655,0.000029088604,0.00047734892,0.00032706503,0.00022650474,0.0002408381,0.0002766914,0.0000073753654,0.0026685558],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986005,0.000026566146,0.0003341946,0.00025784483,0.00043943085,0.00034145563],"domain_scores_gemma":[0.99619514,0.000031597472,0.000014248376,0.0004285939,0.0033111712,0.000019234409],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034597563,0.000088800414,0.00011764497,0.00035662903,0.00054196286,0.00014491756,0.00030595876,0.000058559206,0.0013800614],"category_scores_gemma":[0.0011141744,0.00008518236,0.000070329275,0.000858498,0.000091727554,0.0008235968,0.00013565198,0.00017601276,0.0005087464],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017412033,0.0017108558,0.0054494995,0.0018468949,0.00009616937,4.340394e-7,0.00091310375,0.025460692,0.03137839,0.7113086,0.21162654,0.010034708],"study_design_scores_gemma":[0.00050912035,0.00005097007,0.022142747,0.000022912545,0.000014395973,1.9142196e-7,0.0025725658,0.29725552,0.005762627,0.0035394263,0.6678164,0.00031316534],"about_ca_topic_score_codex":0.0019535597,"about_ca_topic_score_gemma":0.015805855,"teacher_disagreement_score":0.70776916,"about_ca_system_score_codex":0.000005567036,"about_ca_system_score_gemma":0.000059244547,"threshold_uncertainty_score":0.9995328},"labels":[],"label_agreement":null},{"id":"W2024154419","doi":"10.1007/s10479-011-1013-1","title":"A Bayesian model and numerical algorithm for CBM availability maximization","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Theory of computation; Parameterized complexity; Markov decision process; Computer science; Mathematical optimization; Maximization; Partially observable Markov decision process; Bayesian probability; Expectation–maximization algorithm; Algorithm; Multivariate statistics; Markov chain; Markov process; Markov model; Mathematics; Artificial intelligence; Machine learning; Statistics","score_opus":0.1699342649344517,"score_gpt":0.36933101493084397,"score_spread":0.19939674999639226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024154419","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009394794,0.00007906705,0.98801345,0.00022652534,0.00002323339,0.00047774604,0.000046376852,0.000039750455,0.0016990785],"genre_scores_gemma":[0.77075005,0.0003816611,0.22838669,0.000022574646,0.000018984774,0.0001555191,0.000034166962,0.00001750405,0.00023284268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992186,0.000048070953,0.00021196724,0.0001589197,0.00015142889,0.0002110182],"domain_scores_gemma":[0.998989,0.000049347134,0.0000066345715,0.00020107346,0.00068402314,0.000069914844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072894787,0.00006654778,0.000111827925,0.00011235006,0.00012672416,0.000030077104,0.00008797696,0.00006819879,0.00005948866],"category_scores_gemma":[0.00024225636,0.00006381259,0.000030964093,0.00022783942,0.00010704882,0.0002659995,0.000026175216,0.00010489544,0.0000034424415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022341854,0.00012952367,0.000073855015,0.000091294074,0.00002185788,2.490493e-7,0.0012104342,0.96015954,0.00052594626,0.0051969644,0.0020442,0.030523807],"study_design_scores_gemma":[0.00011422527,0.00008038225,0.0002452701,0.000009539098,0.0000022948982,6.306345e-7,0.00006997338,0.99279815,0.0035702875,0.002931377,0.00011407707,0.00006381877],"about_ca_topic_score_codex":0.000058545054,"about_ca_topic_score_gemma":0.000014346103,"teacher_disagreement_score":0.7613553,"about_ca_system_score_codex":0.00001430742,"about_ca_system_score_gemma":0.000045023255,"threshold_uncertainty_score":0.2602202},"labels":[],"label_agreement":null},{"id":"W2024577761","doi":"10.1007/s10479-013-1336-1","title":"Effects of different cut-to-length harvesting structures on the economic value of a wood procurement planning problem","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"FPInnovations","keywords":"Procurement; Computer science; Profit (economics); Operations research; Context (archaeology); Business; Economics; Mathematics; Microeconomics","score_opus":0.13060633776607708,"score_gpt":0.33892325488727193,"score_spread":0.20831691712119485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024577761","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99595517,0.00015746537,0.0010397335,0.00026701967,0.000035885143,0.0009932461,0.000017160273,0.000022814118,0.0015115031],"genre_scores_gemma":[0.998911,0.000041810574,0.00075286435,0.000016664753,0.00003304424,0.0001409893,0.00000477543,0.000020523277,0.00007829888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99898237,0.00007146598,0.0003201042,0.000118087024,0.00027244617,0.000235531],"domain_scores_gemma":[0.99920416,0.00029249938,0.000019835945,0.00021270818,0.00020728812,0.00006348258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030301072,0.00010230735,0.00018386777,0.00017576029,0.000083424275,0.00003429911,0.00023253102,0.000040546962,0.000052138104],"category_scores_gemma":[0.00010929832,0.00006882276,0.000042071162,0.00012956247,0.00008519467,0.00007030326,0.000028172179,0.00021006298,0.0000111876125],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021075155,0.00014133648,0.0013143648,0.0009562895,0.00022070769,0.0000016454388,0.0027514328,0.7970228,0.08854254,0.10412156,0.0036488685,0.001257339],"study_design_scores_gemma":[0.0002944525,0.00069125916,0.03604562,0.0005027135,0.00001563115,6.039523e-7,0.00022409472,0.10574786,0.85421735,0.0018637524,0.00021524164,0.0001814236],"about_ca_topic_score_codex":0.000237081,"about_ca_topic_score_gemma":0.000045356268,"teacher_disagreement_score":0.7656748,"about_ca_system_score_codex":0.000024969459,"about_ca_system_score_gemma":0.00004865333,"threshold_uncertainty_score":0.28065106},"labels":[],"label_agreement":null},{"id":"W2024996305","doi":"10.1007/s10479-012-1286-z","title":"Reformulation of a model for hierarchical divisive graph modularity maximization","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Heuristics; Mathematics; Random graph; Maximization; Quadratic equation; Combinatorics; Graph; Modularity (biology); Theory of computation; Discrete mathematics; Mathematical optimization; Algorithm","score_opus":0.28975513845299045,"score_gpt":0.4873950097450737,"score_spread":0.19763987129208327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024996305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3325456,0.000040524075,0.6658154,0.0003296803,0.0000064341502,0.00039009986,0.00006543227,0.000008768693,0.0007980395],"genre_scores_gemma":[0.98139477,0.000012508812,0.01795131,0.000008822217,0.00009451623,0.0001252415,0.00022173238,0.000009854679,0.00018126279],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887085,0.000119891105,0.00030853666,0.00012440232,0.00031290678,0.0002634402],"domain_scores_gemma":[0.9982953,0.00010038773,0.000041738156,0.00027851848,0.0012171973,0.00006685695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011105471,0.00006815448,0.00016813855,0.00028185657,0.00019222997,0.000022085984,0.00015375273,0.00003626259,0.000063411644],"category_scores_gemma":[0.000058929156,0.00006247751,0.00012771698,0.0004636496,0.00009191436,0.00031268384,0.00007987986,0.00013062867,0.0000012984285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053904274,0.0006616573,0.011918136,0.000030293913,0.00012882157,1.6706057e-8,0.0010069989,0.22315234,0.005474767,0.74405897,0.001548167,0.01196591],"study_design_scores_gemma":[0.00011360957,0.000053541375,0.002782405,0.000013400605,0.000009418774,4.141497e-8,0.00004728855,0.9228483,0.014706944,0.05928583,0.00007645777,0.000062771825],"about_ca_topic_score_codex":0.00023796142,"about_ca_topic_score_gemma":0.000017680104,"teacher_disagreement_score":0.69969594,"about_ca_system_score_codex":0.000008572772,"about_ca_system_score_gemma":0.00006153532,"threshold_uncertainty_score":0.2547759},"labels":[],"label_agreement":null},{"id":"W202756272","doi":"10.1023/a:1020957904442","title":"Locating Multiple Competitive Facilities: Spatial Interaction Models with Variable Expenditures","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":85,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cannibalization; Theory of computation; Key (lock); Constant (computer programming); Computer science; Mathematical optimization; Mathematical economics; Mathematics; Economics; Algorithm; Industrial organization","score_opus":0.2314592520300225,"score_gpt":0.36973260853578677,"score_spread":0.13827335650576428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W202756272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7563323,0.0003103071,0.016526425,0.0019787366,0.00019852446,0.0009433108,0.000043854765,0.00010747176,0.22355911],"genre_scores_gemma":[0.99755186,0.000027037153,0.0004545881,0.00011902748,0.00019575446,0.00007182577,0.000042166906,0.000014691252,0.0015230799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987312,0.000057008074,0.00023898284,0.00022687955,0.00044942097,0.00029652874],"domain_scores_gemma":[0.99856085,0.0002096675,0.00003801614,0.00022823112,0.0009466291,0.00001660442],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006313859,0.00010840291,0.00014474861,0.00039157053,0.00048960414,0.0003599682,0.000184262,0.000041423937,0.0025018947],"category_scores_gemma":[0.00021976612,0.00009431565,0.000033357843,0.00037313026,0.00011442912,0.0016491074,0.0001232851,0.0002602057,0.00009274178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013363684,0.0035164836,0.06391854,0.0020300013,0.00052068365,0.000078114404,0.015729416,0.4007885,0.01992913,0.26882166,0.03719881,0.18613233],"study_design_scores_gemma":[0.00067553995,0.000078143516,0.0019188627,0.00022643436,0.000019465708,0.0000043139325,0.009950535,0.94991624,0.0020319836,0.00050438737,0.03435527,0.000318797],"about_ca_topic_score_codex":0.0186257,"about_ca_topic_score_gemma":0.0035642465,"teacher_disagreement_score":0.54912776,"about_ca_system_score_codex":0.000012618961,"about_ca_system_score_gemma":0.000026129062,"threshold_uncertainty_score":0.9984099},"labels":[],"label_agreement":null},{"id":"W2031002773","doi":"10.1007/s10479-011-0835-1","title":"Single-machine scheduling problems with time and position dependent processing times","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Job shop scheduling; Single-machine scheduling; Theory of computation; Computer science; Scheduling (production processes); Heuristic; Mathematical optimization; Due date; Position (finance); Learning effect; Algorithm; Mathematics; Artificial intelligence; Schedule","score_opus":0.10754502795539035,"score_gpt":0.33211064105787114,"score_spread":0.2245656131024808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031002773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8866403,0.0042446074,0.090946615,0.00080188905,0.000043574404,0.0007705487,0.00003171147,0.00034475056,0.016175965],"genre_scores_gemma":[0.90904266,0.0001229671,0.09041118,0.00001585501,0.000024704637,0.000024622428,0.000027458807,0.000025007645,0.00030554706],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913716,0.000049380542,0.00017827413,0.00014590618,0.00027781364,0.00021148215],"domain_scores_gemma":[0.9992214,0.000024254816,0.000011051733,0.00012604322,0.0005387892,0.00007849979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047714927,0.000087789434,0.00010811566,0.00023287763,0.00019662389,0.00010087666,0.00008961418,0.00005124666,0.00013002405],"category_scores_gemma":[0.00004507127,0.00007509701,0.000013073721,0.00033564764,0.00008649987,0.00032003102,0.000026262494,0.00018006311,0.00002185034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036491663,0.00021311072,0.00023682974,0.00014243434,0.00007032645,0.0000063243583,0.003126031,0.95915854,0.01985391,0.00037152134,0.000046000798,0.016738461],"study_design_scores_gemma":[0.00017852777,0.00018573194,0.00014531071,0.00012729205,0.0000052745672,0.0000148148965,0.00013948488,0.9422455,0.056781113,0.000053871634,0.000014214787,0.00010886474],"about_ca_topic_score_codex":0.000055692984,"about_ca_topic_score_gemma":0.00003274672,"teacher_disagreement_score":0.036927205,"about_ca_system_score_codex":0.000011056121,"about_ca_system_score_gemma":0.000042063,"threshold_uncertainty_score":0.30623668},"labels":[],"label_agreement":null},{"id":"W2031435014","doi":"10.1007/s10479-008-0320-7","title":"Feedback Stackelberg equilibrium strategies when the private label competes with the national brand","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Goodwill; Stackelberg competition; Private label; Advertising; Comparative advertising; Business; Microeconomics; Stock (firearms); Computer science; Economics; Finance","score_opus":0.25022625584714836,"score_gpt":0.39155817141154736,"score_spread":0.141331915564399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031435014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9463558,0.0002204849,0.00004775722,0.02595341,0.000027641767,0.00038614558,0.000008628043,0.000023269466,0.026976842],"genre_scores_gemma":[0.9973407,0.000054624103,0.00009506766,0.0007246841,0.00023091807,0.000049096856,0.000023549124,0.000014763788,0.0014666194],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9983579,0.00009254478,0.00020062311,0.00017532476,0.0008746598,0.0002989391],"domain_scores_gemma":[0.9977205,0.0003361174,0.000038956976,0.00024315053,0.0016493886,0.000011877355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015687965,0.00010733385,0.00011837294,0.00018094576,0.001061887,0.0006359544,0.00048639133,0.000029798031,0.00043885407],"category_scores_gemma":[0.0001650457,0.00005763337,0.000037855178,0.0006782322,0.0005459111,0.0011971937,0.00022260284,0.00027529834,0.000076000186],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010065204,0.0012268551,0.12091754,0.00044994577,0.0006264009,0.000040173134,0.0060477825,0.011836523,0.047064047,0.34831923,0.45263353,0.009831459],"study_design_scores_gemma":[0.0032484299,0.00024677409,0.5438137,0.00027174328,0.00010104934,0.0000456999,0.0076277624,0.035560362,0.0051363097,0.00912399,0.39376694,0.0010571955],"about_ca_topic_score_codex":0.0009399326,"about_ca_topic_score_gemma":0.0009013438,"teacher_disagreement_score":0.4228962,"about_ca_system_score_codex":0.0000061882197,"about_ca_system_score_gemma":0.00018764102,"threshold_uncertainty_score":0.8167284},"labels":[],"label_agreement":null},{"id":"W2036293811","doi":"10.1007/s10479-014-1731-2","title":"$$(Q,r,L)$$ ( Q , r , L ) model for stochastic demand with lead-time dependent partial backlogging","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Reorder point; Lead time; Purchasing; Order (exchange); Function (biology); Theory of computation; Economic order quantity; Holding cost; Total cost; Variable cost; Variable (mathematics); Lost sales; Fixed cost; Random variable; Mathematical optimization; Computer science; Mathematics; Economics; Statistics; Algorithm; Operations management; Microeconomics","score_opus":0.20470277077797733,"score_gpt":0.37786532927974065,"score_spread":0.17316255850176332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036293811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23765083,0.00008710235,0.73277617,0.010512595,0.00011763202,0.0019834843,0.000012030495,0.000098502045,0.016761644],"genre_scores_gemma":[0.9934831,0.0000050922963,0.00080201344,0.000757272,0.00045298185,0.00023007867,0.00005024763,0.000027782426,0.0041914256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983879,0.000042803476,0.0002633552,0.00029873196,0.0005566955,0.0004505611],"domain_scores_gemma":[0.9986537,0.000097402255,0.00003993232,0.00032003713,0.00086414063,0.000024802814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023259132,0.00012676307,0.00018788216,0.000426957,0.00047894212,0.00031829276,0.0003046638,0.000042620213,0.00021087573],"category_scores_gemma":[0.00033264508,0.00010582955,0.00005944354,0.0003187752,0.00013497967,0.0007171858,0.00016029664,0.00012205258,0.00020005731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018417956,0.0002427565,0.00013531171,0.0001975612,0.000079384365,0.0000010894602,0.00016657083,0.8872379,0.0021328956,0.078485586,0.028346261,0.0027904892],"study_design_scores_gemma":[0.0005019883,0.00007052744,0.000040062674,0.000045380144,0.000016466003,2.909374e-7,0.00013584057,0.9927347,0.0006065654,0.001536967,0.0041756774,0.0001355697],"about_ca_topic_score_codex":0.00014956263,"about_ca_topic_score_gemma":0.00021011638,"teacher_disagreement_score":0.75583225,"about_ca_system_score_codex":0.000012913684,"about_ca_system_score_gemma":0.00004555641,"threshold_uncertainty_score":0.4315604},"labels":[],"label_agreement":null},{"id":"W2038544490","doi":"10.1007/s10479-009-0599-z","title":"Pricing swing options with regime switching","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Swing; Gasoline; Flexibility (engineering); Variable (mathematics); Electricity; Markov chain; Process (computing); Computer science; Economics; Wholesale market; Theory of computation; Econometrics; Mathematical optimization; Mathematics; Engineering; Electrical engineering; Algorithm","score_opus":0.24639512695006832,"score_gpt":0.39389053820586967,"score_spread":0.14749541125580135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038544490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94496167,0.008109907,0.002366562,0.013675343,0.000026640431,0.00024835978,0.0000144718,0.000025484156,0.030571543],"genre_scores_gemma":[0.9914883,0.0038584494,0.0019940482,0.00022665718,0.00006014235,0.000011155076,0.0000134980355,0.000008301257,0.002339493],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999012,0.00003777138,0.0003481347,0.00023162135,0.00009970212,0.00027080142],"domain_scores_gemma":[0.999346,0.00006734115,0.000043671764,0.00029487343,0.00017542453,0.00007265424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014927078,0.000072563664,0.00020155196,0.00063722907,0.00040053466,0.00014959341,0.00017525497,0.000041233954,0.00018104559],"category_scores_gemma":[0.00020281435,0.00006648682,0.00007735347,0.0008439313,0.00005286626,0.00042031816,0.0000272303,0.00019751095,0.00015981476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013441734,0.00014343046,0.000939004,0.0000059156346,0.000058057547,0.0000030930885,0.0009631279,0.0059384424,0.0007183767,0.98932713,0.00097248313,0.0009174992],"study_design_scores_gemma":[0.0022927462,0.003637065,0.12302728,0.00044446197,0.000054316228,0.000031326854,0.0050144414,0.41784212,0.026819903,0.36185193,0.057069838,0.0019145776],"about_ca_topic_score_codex":0.0006425983,"about_ca_topic_score_gemma":0.00012137968,"teacher_disagreement_score":0.6274752,"about_ca_system_score_codex":0.000021284974,"about_ca_system_score_gemma":0.000035350982,"threshold_uncertainty_score":0.3080629},"labels":[],"label_agreement":null},{"id":"W2039568841","doi":"10.1007/s10479-005-3971-7","title":"Metaheuristics in Combinatorial Optimization","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":2341,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metaheuristic; Theory of computation; Combinatorial optimization; Vehicle routing problem; Computer science; Scheduling (production processes); Mathematical optimization; Operations research; Job shop scheduling; Parallel metaheuristic; Optimization problem; Management science; Routing (electronic design automation); Mathematics; Artificial intelligence; Algorithm; Engineering; Meta-optimization","score_opus":0.1739552011743806,"score_gpt":0.4498479164768863,"score_spread":0.2758927153025057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039568841","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20500639,0.0011639396,0.7450065,0.0046150605,0.0006410421,0.0011232779,0.000043844535,0.00033617995,0.042063773],"genre_scores_gemma":[0.8192676,0.0003657105,0.18004031,0.000019952997,0.00011095738,0.00002476209,0.000018038127,0.000021691101,0.00013100622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998749,0.00024837576,0.00032357968,0.0001098283,0.00032983866,0.0002393589],"domain_scores_gemma":[0.99901825,0.00015846087,0.000007775972,0.00020810367,0.0005536016,0.000053828135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018060205,0.00006721008,0.00012959944,0.00040750453,0.000078606856,0.00005094167,0.00016065277,0.00007223764,0.00012789667],"category_scores_gemma":[0.00074250123,0.00007442567,0.000024676687,0.0008637326,0.000053927826,0.00022945621,0.00003386732,0.00024517748,0.00002360497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037957236,0.000050952905,0.000113121874,0.000012176415,0.000008325391,5.83909e-7,0.00019896385,0.989912,0.0003328483,0.0061376686,0.00070504297,0.002524525],"study_design_scores_gemma":[0.00020822101,0.000024609239,0.00020935366,0.000012899494,0.0000012362542,5.801477e-7,0.00003546771,0.9876408,0.01052601,0.000093386705,0.0011803018,0.00006712203],"about_ca_topic_score_codex":0.000028992255,"about_ca_topic_score_gemma":0.000025647323,"teacher_disagreement_score":0.6142612,"about_ca_system_score_codex":0.00003257729,"about_ca_system_score_gemma":0.000053824075,"threshold_uncertainty_score":0.30349907},"labels":[],"label_agreement":null},{"id":"W2040412566","doi":"10.1007/s10479-014-1704-5","title":"On agglomeration in competitive location models","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Economies of agglomeration; Theory of computation; Economic geography; Economics; Dispersion (optics); Industrial organization; Computer science; Microeconomics; Physics","score_opus":0.26909883795682826,"score_gpt":0.3785344723005367,"score_spread":0.10943563434370845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040412566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78563744,0.00039964568,0.036894344,0.021457069,0.00007654198,0.0003978482,0.00006105637,0.000010293185,0.15506576],"genre_scores_gemma":[0.99846184,0.0003656662,0.00020895767,0.0002608307,0.000040249935,0.00004139623,0.000045008415,0.00000790989,0.00056811044],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989665,0.000073757416,0.00046272832,0.0002488819,0.00007061707,0.00017752081],"domain_scores_gemma":[0.9992168,0.00013134157,0.000049389415,0.00023280589,0.0003243367,0.000045344237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017447554,0.00006306028,0.00021795822,0.0007066316,0.000117958756,0.00006860385,0.00014946381,0.000052796822,0.00014048185],"category_scores_gemma":[0.00031662386,0.000070878195,0.00005394934,0.0005284782,0.000072802664,0.00027066848,0.000027282636,0.0001402947,0.00027745665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008408113,0.00007734922,0.00030444737,0.000004106131,0.000008851256,1.0927707e-7,0.00013205984,0.2810554,0.000012602691,0.7178252,0.00019684016,0.00037467154],"study_design_scores_gemma":[0.00015897785,0.0001284325,0.003014522,0.000017926783,3.8814403e-7,1.28253e-7,0.00005395875,0.7643637,0.00023327801,0.23052916,0.0014233221,0.00007617502],"about_ca_topic_score_codex":0.0029857534,"about_ca_topic_score_gemma":0.0021903676,"teacher_disagreement_score":0.48729602,"about_ca_system_score_codex":0.00003626816,"about_ca_system_score_gemma":0.000031949938,"threshold_uncertainty_score":0.45135856},"labels":[],"label_agreement":null},{"id":"W2041738053","doi":"10.1007/s10479-006-5301-0","title":"A BMAP/G/1 Retrial Queue with a Server Subject to Breakdowns and Repairs","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Retrial queue; Markov chain; Computer science; Queue; Laplace transform; Censoring (clinical trials); Stationary distribution; Exponential distribution; Theory of computation; Mathematical optimization; Real-time computing; Mathematics; Algorithm; Statistics; Computer network; Queueing system","score_opus":0.08682550280944053,"score_gpt":0.37394237132527347,"score_spread":0.28711686851583296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041738053","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98378116,0.00007291664,0.0005059076,0.007186641,0.00001936595,0.0003873531,0.0000058510973,0.000051470146,0.007989363],"genre_scores_gemma":[0.9959894,0.000010853201,0.0007244501,0.00044046596,0.00049152033,0.000046261717,0.0000260486,0.000020313113,0.0022507107],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856377,0.000074018484,0.00025378808,0.0003100971,0.00048032982,0.00031800856],"domain_scores_gemma":[0.9982649,0.000112923175,0.000034313725,0.00037078632,0.0011954417,0.000021635868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019285948,0.00010786101,0.00019263299,0.0007055624,0.00039110603,0.0002812382,0.00019336508,0.00004481615,0.0001620785],"category_scores_gemma":[0.0006604915,0.0000886549,0.000048627757,0.0018224176,0.00014617178,0.0008855273,0.00017047559,0.00016258306,0.00008354132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027659854,0.0008782126,0.024646081,0.0004085288,0.00037188487,0.00011741638,0.0005647324,0.16123301,0.014825677,0.7217853,0.06707771,0.0053254324],"study_design_scores_gemma":[0.011196126,0.00234131,0.14789054,0.0019979258,0.000553638,0.0000763414,0.00748504,0.18433286,0.044606924,0.13396162,0.46056533,0.0049923505],"about_ca_topic_score_codex":0.00647476,"about_ca_topic_score_gemma":0.007856083,"teacher_disagreement_score":0.5878237,"about_ca_system_score_codex":0.000012958522,"about_ca_system_score_gemma":0.000052524065,"threshold_uncertainty_score":0.97879434},"labels":[],"label_agreement":null},{"id":"W2042547819","doi":"10.1007/s10479-012-1227-x","title":"Contracting with demand uncertainty under supply chain competition","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Supply chain; Stackelberg competition; Revenue sharing; Business; Competition (biology); Industrial organization; Microeconomics; Supply chain management; Product (mathematics); Revenue; Supply and demand; Service management; Economics; Marketing; Finance","score_opus":0.17474198552286524,"score_gpt":0.38150496156347674,"score_spread":0.2067629760406115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042547819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91917926,0.00032905524,0.0019599616,0.014835174,0.00017514375,0.0008097204,0.00000687207,0.000060682647,0.06264411],"genre_scores_gemma":[0.99644905,0.000044039418,0.00012213833,0.0014915033,0.00071569136,0.00006845351,0.00008246021,0.000017916333,0.0010087634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984579,0.00007056389,0.00023240234,0.00017134206,0.00057367556,0.00049410056],"domain_scores_gemma":[0.99883115,0.00009552244,0.00004342907,0.00024013438,0.00075884693,0.000030905874],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002369455,0.00010862159,0.00014595318,0.00042097244,0.00046322824,0.00025516187,0.0001886874,0.000041221654,0.0010533634],"category_scores_gemma":[0.0001550809,0.000088216126,0.000041709864,0.00059025275,0.00015163544,0.0015214627,0.00011991125,0.00018938832,0.00020880181],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013923022,0.00068922894,0.022746434,0.00021559362,0.00012717188,0.000004409788,0.00040099327,0.028912377,0.001774009,0.92046404,0.022262571,0.0022639215],"study_design_scores_gemma":[0.0044461284,0.0004251187,0.15112346,0.0008480815,0.00011908522,0.000012750901,0.032129295,0.1705676,0.0076228813,0.006159177,0.6249754,0.0015709983],"about_ca_topic_score_codex":0.0013511237,"about_ca_topic_score_gemma":0.00052478135,"teacher_disagreement_score":0.9143049,"about_ca_system_score_codex":0.000022014963,"about_ca_system_score_gemma":0.00003224138,"threshold_uncertainty_score":0.9998598},"labels":[],"label_agreement":null},{"id":"W2043020814","doi":"10.1007/s10479-008-0410-6","title":"A confidence voting process for ranking problems based on support vector machines","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Support vector machine; Ranking (information retrieval); Computer science; Ranking SVM; Voting; Machine learning; Rank (graph theory); Artificial intelligence; Process (computing); Theory of computation; Data mining; Task (project management); Algorithm; Mathematics; Engineering","score_opus":0.7667455877346339,"score_gpt":0.6232891373877681,"score_spread":0.14345645034686572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043020814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83909935,0.00012846693,0.14180893,0.011211374,0.00031218724,0.0030302696,0.00019493242,0.00007284631,0.0041416488],"genre_scores_gemma":[0.99376005,0.000009009338,0.003412519,0.0003792796,0.00011210504,0.00027127698,0.000015191834,0.00002377726,0.0020168207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99331486,0.0005856389,0.0010695499,0.0007041112,0.003758021,0.00056779763],"domain_scores_gemma":[0.9869132,0.0052535124,0.00012043472,0.0007464146,0.006806522,0.0001598893],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.013188257,0.00016342498,0.00037940923,0.001185835,0.0011875781,0.0004470467,0.0012705992,0.000088420544,0.0010497158],"category_scores_gemma":[0.031544786,0.00012284373,0.00015350762,0.0017680326,0.00031473426,0.0006028264,0.00012775081,0.0003013835,0.00015101257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014998777,0.0018149345,0.017903829,0.00030923923,0.0000802658,0.0001047611,0.012833447,0.7722752,0.039948948,0.033179764,0.0784903,0.041559447],"study_design_scores_gemma":[0.0007520708,0.0005433632,0.0038752523,0.00017686716,0.0000021554295,0.000014394681,0.00030681706,0.97222805,0.015101579,0.0030143294,0.0037787026,0.00020642676],"about_ca_topic_score_codex":0.00009373255,"about_ca_topic_score_gemma":0.00018662655,"teacher_disagreement_score":0.19995286,"about_ca_system_score_codex":0.000018995168,"about_ca_system_score_gemma":0.00070198206,"threshold_uncertainty_score":0.99986345},"labels":[],"label_agreement":null},{"id":"W2043465029","doi":"10.1007/s10479-008-0511-2","title":"Supply chain DEA: production possibility set and performance evaluation model","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":118,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Supply chain; Benchmarking; Production (economics); Computer science; Set (abstract data type); Supply chain management; Service management; Theory of computation; Supply chain risk management; Operations research; Business; Microeconomics; Economics; Algorithm; Mathematics; Marketing","score_opus":0.555066990663382,"score_gpt":0.5787012297465279,"score_spread":0.02363423908314588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043465029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98105764,0.00028943823,0.0012602005,0.01589147,0.000029887535,0.0004465635,0.000011458805,0.000010793169,0.0010025294],"genre_scores_gemma":[0.99716145,0.00014226083,0.001236169,0.00011824397,0.000043339234,0.000020057461,0.000015238301,0.0000036643696,0.0012595701],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944063,0.0008900674,0.0006092964,0.0005768105,0.0032220373,0.00029548592],"domain_scores_gemma":[0.9930003,0.00023844864,0.00005483465,0.0008120025,0.0058063925,0.00008798461],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.028342733,0.00008801971,0.00019060439,0.00077575044,0.00068481115,0.0002924877,0.0004151054,0.000063133855,0.00011003926],"category_scores_gemma":[0.011254431,0.00006784619,0.00005308203,0.0021494925,0.00028262255,0.00089006027,0.000073657204,0.00022273404,0.00005135652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066957444,0.0002688302,0.0046520615,0.000005620683,0.000010761113,3.4539391e-7,0.0026643374,0.7811005,0.00823515,0.001344864,0.005099271,0.19655128],"study_design_scores_gemma":[0.00008087174,0.00019845527,0.055379342,0.000013254018,0.000004738418,0.0000017248542,0.00029027773,0.9297301,0.007676228,0.0064870897,0.00007135142,0.00006655873],"about_ca_topic_score_codex":0.000077810415,"about_ca_topic_score_gemma":0.0001357743,"teacher_disagreement_score":0.19648471,"about_ca_system_score_codex":0.00003217434,"about_ca_system_score_gemma":0.00041497045,"threshold_uncertainty_score":0.9970742},"labels":[],"label_agreement":null},{"id":"W2044329702","doi":"10.1007/s10479-012-1278-z","title":"Modeling and solving a logging camp location problem","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Montréal; Transport Canada","funders":"Natural Sciences and Engineering Research Council of Canada; FPInnovations","keywords":"Theory of computation; Logging; Computer science; Programming language; Geography","score_opus":0.25929779822221494,"score_gpt":0.4047320163576586,"score_spread":0.14543421813544366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044329702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9609177,0.0009712245,0.018008495,0.007766423,0.0001143462,0.00059229846,0.0000013895124,0.000057352838,0.011570739],"genre_scores_gemma":[0.99815303,0.0001340047,0.00062665984,0.00033449926,0.00023659924,0.000056497924,0.000021891985,0.000009624575,0.00042719257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988493,0.000030541472,0.00025910768,0.00015675186,0.00035850922,0.00034584478],"domain_scores_gemma":[0.99883425,0.000013305347,0.000009490729,0.00019293027,0.0009276111,0.000022397635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023029405,0.00007514365,0.00009155472,0.00042797145,0.0004216626,0.00018301702,0.00012800451,0.00003242963,0.0001759686],"category_scores_gemma":[0.00026937775,0.00007245528,0.000022092989,0.0005859948,0.000057689496,0.0017398386,0.00018297501,0.000119146425,0.00018209928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002557066,0.00040474953,0.0058971127,0.0010621765,0.000057528967,4.4270064e-7,0.0017427482,0.7031778,0.0018200938,0.26611605,0.0060907505,0.013604961],"study_design_scores_gemma":[0.000094432624,0.000006808084,0.0014118784,0.00004820306,0.0000054654806,3.247441e-7,0.0012828311,0.99150896,0.000116926065,0.00047486075,0.004948075,0.00010125002],"about_ca_topic_score_codex":0.004581741,"about_ca_topic_score_gemma":0.00079351873,"teacher_disagreement_score":0.28833112,"about_ca_system_score_codex":0.0000107127125,"about_ca_system_score_gemma":0.00002585302,"threshold_uncertainty_score":0.6926253},"labels":[],"label_agreement":null},{"id":"W2044675809","doi":"10.1007/s10479-013-1311-x","title":"Timing order fulfillment of capital goods under a constrained capacity","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Hong Kong University of Science and Technology; National Natural Science Foundation of China","keywords":"Markov decision process; Order (exchange); Build to order; Computer science; Mathematical optimization; Process (computing); Product (mathematics); Value (mathematics); Theory of computation; Capital good; Work (physics); Production (economics); Markov process; Operations research; Microeconomics; Economics; Mathematics; Public good; Algorithm","score_opus":0.2095976756925073,"score_gpt":0.36842889084022745,"score_spread":0.15883121514772014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044675809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97603285,0.000048849466,0.0005974694,0.006651049,0.00008369352,0.00051039545,0.0000035238095,0.0000207863,0.016051356],"genre_scores_gemma":[0.997616,0.00001977677,0.0009320779,0.00028236126,0.00018651485,0.000057134504,0.000047338817,0.000011077147,0.00084772933],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.998724,0.00003217085,0.0003227418,0.00018104372,0.00047361047,0.00026646993],"domain_scores_gemma":[0.9974229,0.000037201717,0.00004998562,0.00020250176,0.0022717114,0.000015729474],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000895897,0.00008844058,0.00014920454,0.0004020056,0.00022449227,0.00016476656,0.000190915,0.000048859572,0.0015119207],"category_scores_gemma":[0.00038986446,0.00007822308,0.000035780584,0.00086320797,0.0001989403,0.0010781985,0.00012539575,0.00011999371,0.00021983033],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010852144,0.0018621249,0.017207487,0.00097210874,0.00051222934,0.00000413236,0.003548243,0.020950308,0.16586302,0.65126777,0.11298278,0.024721248],"study_design_scores_gemma":[0.0077943993,0.00053693954,0.306899,0.001104199,0.0001578432,0.000015223261,0.03416496,0.20902121,0.30165014,0.08909521,0.04614558,0.0034152698],"about_ca_topic_score_codex":0.0016144969,"about_ca_topic_score_gemma":0.00014441744,"teacher_disagreement_score":0.5621726,"about_ca_system_score_codex":0.000011808648,"about_ca_system_score_gemma":0.000110379064,"threshold_uncertainty_score":0.99940085},"labels":[],"label_agreement":null},{"id":"W2045728330","doi":"10.1007/s10479-014-1581-y","title":"Relief distribution networks: a systematic review","year":2014,"lang":"en","type":"review","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":243,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Variety (cybernetics); Emergency management; Systematic review; Distribution (mathematics); Computer science; Data science; Field (mathematics); Management science; Operations research; Political science; Economics; Artificial intelligence; Engineering","score_opus":0.3010963451300899,"score_gpt":0.46867135395707127,"score_spread":0.16757500882698134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045728330","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1310538e-7,0.990879,0.00150237,0.0012880097,0.00017291815,0.0037954133,0.000024712515,0.00004996775,0.0022874074],"genre_scores_gemma":[0.000038398506,0.9936492,0.0000095408595,0.0006763392,0.00039080033,0.001193874,0.002058785,0.000032041484,0.0019510585],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.99622047,0.00039328943,0.001597264,0.00044221553,0.0008910584,0.00045570594],"domain_scores_gemma":[0.99667096,0.00010620871,0.00013506867,0.0010868411,0.0019728828,0.000028017912],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006973198,0.00030061358,0.0018028278,0.00049358374,0.00038603996,0.00029916523,0.00080828817,0.00015348272,0.00044761578],"category_scores_gemma":[0.0030291283,0.00023290941,0.0004925513,0.0022430734,0.000108102584,0.00049813185,0.00037159937,0.00043841032,0.0021539151],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.307489e-7,0.00007894185,7.8958585e-8,0.8721893,0.00009699269,7.586503e-7,0.0000020082155,0.0006025759,4.3715116e-9,0.019759689,0.091373906,0.015894959],"study_design_scores_gemma":[0.000024617742,0.000009078897,2.389129e-7,0.28176227,0.00032879008,6.671543e-7,0.000008891902,0.008228714,1.969942e-8,0.000021921043,0.7094542,0.00016061573],"about_ca_topic_score_codex":0.0007205729,"about_ca_topic_score_gemma":0.00027246584,"teacher_disagreement_score":0.61808026,"about_ca_system_score_codex":0.000042915228,"about_ca_system_score_gemma":0.000108566615,"threshold_uncertainty_score":0.998623},"labels":[],"label_agreement":null},{"id":"W2046593695","doi":"10.1007/s10479-014-1726-z","title":"Maximizing the minimum cover probability by emergency facilities","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Facility location problem; Theory of computation; Cover (algebra); Computer science; Location model; Mathematical optimization; 1-center problem; Plane (geometry); Operations research; Algorithm; Mathematics; Engineering","score_opus":0.2223166886865235,"score_gpt":0.3784368857011514,"score_spread":0.15612019701462793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046593695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85441154,0.00030691587,0.0027603246,0.054537382,0.00039048653,0.0011388969,0.000032828426,0.00007597219,0.08634567],"genre_scores_gemma":[0.982602,0.00013364562,0.000049917573,0.00059195317,0.00017727503,0.00012898588,0.000056083052,0.000009587267,0.016250553],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981349,0.0001221863,0.00042924355,0.00027439243,0.0006795037,0.00035976557],"domain_scores_gemma":[0.9980978,0.000046117457,0.000019776262,0.00056806405,0.0012510984,0.000017188584],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003464623,0.00011326402,0.00013447425,0.00018420782,0.00067158684,0.00018834558,0.0004898098,0.000041347434,0.0035231176],"category_scores_gemma":[0.0012214306,0.00008386038,0.00008148972,0.0007056882,0.00021013376,0.0007579487,0.00025990792,0.00017719988,0.0009389069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041576353,0.0004167903,0.002134748,0.0005252307,0.00006293267,1.8349127e-7,0.0005812675,0.021399606,0.0013337778,0.18643878,0.7805096,0.0065555354],"study_design_scores_gemma":[0.00017706183,0.000034133653,0.0030372962,0.000015957516,0.000007674814,1.1723794e-7,0.001223724,0.1105132,0.00051925716,0.006254191,0.8780247,0.00019266123],"about_ca_topic_score_codex":0.0050396197,"about_ca_topic_score_gemma":0.0013040999,"teacher_disagreement_score":0.1801846,"about_ca_system_score_codex":0.000011008099,"about_ca_system_score_gemma":0.000027700433,"threshold_uncertainty_score":0.99983895},"labels":[],"label_agreement":null},{"id":"W2048695913","doi":"10.1007/s10479-006-0030-y","title":"Evaluation of Commodity Trading Advisors using fixed and variable and benchmark models","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University; U.S. Department of the Treasury","keywords":"Benchmarking; Futures contract; Benchmark (surveying); Data envelopment analysis; Variable (mathematics); Commodity; Theory of computation; Computer science; Econometrics; Order (exchange); Economics; Class (philosophy); Operations research; Mathematical optimization; Financial economics; Mathematics; Finance; Artificial intelligence; Algorithm","score_opus":0.6627674920073058,"score_gpt":0.5631415581296619,"score_spread":0.09962593387764385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048695913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9811257,0.0008246125,0.012689527,0.0006472285,0.000017619592,0.00023093897,0.000029569268,0.0000035422195,0.0044312724],"genre_scores_gemma":[0.99542874,0.00003354116,0.0043882476,0.00001314082,0.00001991736,0.000006311083,0.000007228827,0.000004852193,0.00009800489],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9942708,0.0015541711,0.00065193034,0.00033910232,0.0029557995,0.00022821948],"domain_scores_gemma":[0.9930843,0.0012133026,0.000081034756,0.00041630695,0.0051460434,0.00005897913],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.035619624,0.00007625959,0.00025571045,0.0007785806,0.00050302304,0.00022657242,0.00027877773,0.0000629576,0.00015054547],"category_scores_gemma":[0.0041547744,0.000063698266,0.000041006686,0.0018273408,0.00040681934,0.00067608774,0.00012295962,0.00013881268,0.0000011307752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011643318,0.00016175813,0.002776336,0.000008944061,0.000022904362,2.5450004e-7,0.00051852915,0.9519259,0.019635107,0.01880884,0.0012113206,0.0049184747],"study_design_scores_gemma":[0.00015150914,0.000045028097,0.004065243,0.000024864741,0.000022146396,0.0000015781832,0.00028462266,0.9194974,0.0032045227,0.072613426,0.000034621033,0.000055058976],"about_ca_topic_score_codex":0.0019595167,"about_ca_topic_score_gemma":0.00036638748,"teacher_disagreement_score":0.053804584,"about_ca_system_score_codex":0.000022418311,"about_ca_system_score_gemma":0.00034554157,"threshold_uncertainty_score":0.9930325},"labels":[],"label_agreement":null},{"id":"W2050895424","doi":"10.1007/s10479-009-0520-9","title":"Using the bootstrap method to detect influential DMUs in data envelopment analysis","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Nonparametric statistics; Computer science; Econometrics; Entropy (arrow of time); Theory of computation; Statistical hypothesis testing; Measure (data warehouse); Statistics; Mathematics; Data mining; Algorithm","score_opus":0.8060750286230988,"score_gpt":0.679957794039324,"score_spread":0.12611723458377477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050895424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64100415,0.00026404246,0.33863926,0.018631041,0.000033647975,0.0004594269,0.00004653717,0.000009872808,0.0009120129],"genre_scores_gemma":[0.9508762,0.000024614445,0.048295,0.0004515772,0.000033922588,0.0000067926835,0.00001140875,0.000004477148,0.00029603342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.992196,0.0023153475,0.0010302976,0.0007338554,0.0032399953,0.0004844869],"domain_scores_gemma":[0.99428266,0.0014645283,0.00006523903,0.0023597113,0.0016963292,0.00013153619],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03642944,0.00011316506,0.00037074444,0.0032781584,0.0005820475,0.0006660976,0.0030592242,0.00006231051,0.00027251669],"category_scores_gemma":[0.007829573,0.000073903684,0.00014208323,0.016044669,0.00014864208,0.0005023452,0.0005809623,0.00032650022,0.00006582032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003135378,0.00012908492,0.00076115463,8.053675e-7,0.00013338219,0.000007002923,0.0012297636,0.89982283,0.014825084,0.000702773,0.0018581512,0.0804986],"study_design_scores_gemma":[0.00015827037,0.00012388373,0.050732937,0.000018315826,0.00007588484,0.000002607581,0.0012761832,0.91651237,0.021041496,0.0022169338,0.0076393844,0.00020174617],"about_ca_topic_score_codex":0.0015707446,"about_ca_topic_score_gemma":0.004096932,"teacher_disagreement_score":0.309872,"about_ca_system_score_codex":0.000034628825,"about_ca_system_score_gemma":0.00043560268,"threshold_uncertainty_score":0.99219865},"labels":[],"label_agreement":null},{"id":"W2051214760","doi":"10.1007/s10479-007-0222-0","title":"Bechtold-Jacobs generalized model for shift scheduling with extraordinary overlap","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Theory of computation; Generalization; Computation; Scheduling (production processes); Constraint (computer-aided design); Mathematics; Set (abstract data type); Flexibility (engineering); Computer science; Mathematical optimization; Mathematical economics; Applied mathematics; Algorithm; Statistics","score_opus":0.6644205714305607,"score_gpt":0.5886680585233595,"score_spread":0.0757525129072012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051214760","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5381215,0.00041765775,0.4545266,0.0050842646,0.000057659476,0.00042854005,0.000051302803,0.000029900637,0.0012825588],"genre_scores_gemma":[0.8569268,0.00003993144,0.13796853,0.00016062926,0.00012326862,0.00006824881,0.000019100968,0.000021393624,0.0046721296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995428,0.00023366555,0.0008020245,0.00057328417,0.00214836,0.00081466173],"domain_scores_gemma":[0.9925229,0.0022737544,0.00007156963,0.0008491664,0.0040102024,0.00027241078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019247152,0.00015180945,0.00033417626,0.0011183814,0.00112312,0.00038459213,0.000833695,0.0001300765,0.00011716156],"category_scores_gemma":[0.0059442567,0.00011215732,0.00017777605,0.0020776629,0.0003473075,0.0005734775,0.00012699305,0.00035232608,0.00007403952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048591555,0.00041838287,0.0017536373,0.000013498625,0.00009120254,0.000006852765,0.0015052251,0.8560443,0.007485126,0.12192159,0.004873767,0.0054004784],"study_design_scores_gemma":[0.0007110577,0.00033473133,0.0015285567,0.00004133175,0.000012299867,0.0000060166044,0.0010231193,0.96106523,0.011446575,0.021980466,0.0016423059,0.00020833118],"about_ca_topic_score_codex":0.0002529607,"about_ca_topic_score_gemma":0.00067190855,"teacher_disagreement_score":0.31880525,"about_ca_system_score_codex":0.000023350392,"about_ca_system_score_gemma":0.00068086135,"threshold_uncertainty_score":0.8638245},"labels":[],"label_agreement":null},{"id":"W2051632436","doi":"10.1007/s10479-015-1797-5","title":"New local searches for solving the multi-source Weber problem","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada; Royal Ottawa Mental Health Centre","funders":"Natural Sciences and Engineering Research Council of Canada; National Research University Higher School of Economics; Russian Science Foundation","keywords":"Heuristics; Delaunay triangulation; Heuristic; Theory of computation; Metaheuristic; Triangulation; Mathematical optimization; Computer science; Constructive; Variety (cybernetics); Decomposition; Quality (philosophy); Mathematics; Algorithm; Artificial intelligence","score_opus":0.513336972344693,"score_gpt":0.4481032581850867,"score_spread":0.06523371415960633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051632436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07769984,0.0009532618,0.659453,0.22829874,0.00043702786,0.005025736,0.000015942913,0.00018964274,0.027926851],"genre_scores_gemma":[0.9594324,0.000041054464,0.004961507,0.0012748779,0.0005283488,0.00022997003,0.000054845943,0.000024959141,0.03345202],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984866,0.00004039541,0.000278453,0.00021989545,0.0006040086,0.0003706506],"domain_scores_gemma":[0.9976887,0.00005621923,0.00001393308,0.0003411658,0.001860136,0.000039836737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035626534,0.000091945454,0.00010958716,0.00026141873,0.00046681563,0.00032976002,0.00044704322,0.00003998482,0.00024124428],"category_scores_gemma":[0.00077139656,0.000067162924,0.00006655079,0.00070288504,0.00014627389,0.00068900955,0.0002853832,0.00016042183,0.00039702054],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008261809,0.00027306823,0.00053474936,0.0002494234,0.0000768616,5.304541e-7,0.0011466156,0.21837278,0.00030975902,0.10039065,0.62712103,0.0514419],"study_design_scores_gemma":[0.000432175,0.000032020715,0.00044943133,0.000025565681,0.000007117783,2.0439846e-7,0.003273589,0.48885557,0.0004999134,0.0010427148,0.5052701,0.00011157969],"about_ca_topic_score_codex":0.012047027,"about_ca_topic_score_gemma":0.0074213916,"teacher_disagreement_score":0.8817326,"about_ca_system_score_codex":0.000018536324,"about_ca_system_score_gemma":0.00017835207,"threshold_uncertainty_score":0.9945318},"labels":[],"label_agreement":null},{"id":"W205201433","doi":"10.1023/a:1014517910427","title":"A Tabu Search Algorithm for Access Network Design","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Institut National de la Recherche Scientifique","funders":"","keywords":"Synchronous optical networking; Computer science; Tabu search; Hierarchy; Set (abstract data type); Transmission (telecommunications); Computer network; Distributed computing; Theory of computation; Population; Tree (set theory); Variety (cybernetics); Telecommunications; Algorithm; Mathematics","score_opus":0.33836952596985304,"score_gpt":0.47513391503803926,"score_spread":0.13676438906818622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W205201433","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038866242,0.001089954,0.9913227,0.0011982307,0.000048930102,0.00083969947,0.000014764673,0.00023593525,0.0013631588],"genre_scores_gemma":[0.13565312,0.005193587,0.85680705,0.00008433171,0.00042768943,0.00079399796,0.000038624352,0.00008042574,0.00092116144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984391,0.000077878714,0.0002401222,0.00018985444,0.0003396709,0.0007134159],"domain_scores_gemma":[0.9983387,0.00056742685,0.0000051819775,0.000358463,0.0006465438,0.00008367822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011651271,0.000104499726,0.00017326532,0.00021258868,0.00026164576,0.00011627363,0.00055545295,0.00011361005,0.00006725286],"category_scores_gemma":[0.00026922338,0.000100140474,0.000048720638,0.0012042824,0.0001922841,0.00036777483,0.00015272382,0.00034799118,0.000024172034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010230061,0.000024516788,0.000015006818,0.000012147111,0.000025578382,0.0000033919491,0.000018583229,0.82739985,0.00020821294,0.003132424,0.01887572,0.15027434],"study_design_scores_gemma":[0.00014078117,0.00015329695,0.00006234974,0.000030420402,0.0000018696046,0.000002930013,0.00006868463,0.9760034,0.005929655,0.0040008104,0.013489079,0.00011669524],"about_ca_topic_score_codex":0.000012532135,"about_ca_topic_score_gemma":0.000019373905,"teacher_disagreement_score":0.15015763,"about_ca_system_score_codex":0.000023741803,"about_ca_system_score_gemma":0.000054089014,"threshold_uncertainty_score":0.40836102},"labels":[],"label_agreement":null},{"id":"W2053855832","doi":"10.1007/s10479-006-0148-y","title":"Coordinating decentralized local schedulers in complex supply chain manufacturing","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Scheduling (production processes); Computer science; Supply chain; Theory of computation; Distributed computing; Schedule; Production schedule; Dynamic priority scheduling; Job shop scheduling; Production planning; Industrial engineering; Production (economics); Operations management; Engineering; Business; Algorithm","score_opus":0.10344290171120704,"score_gpt":0.3753957638955624,"score_spread":0.2719528621843553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053855832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9307402,0.00059329637,0.062228028,0.002118305,0.00007542082,0.00038314244,0.000025166028,0.00013741278,0.0036990289],"genre_scores_gemma":[0.97277266,0.00010047162,0.026759436,0.00002463856,0.00005339305,0.00003150099,0.00008695223,0.000022771883,0.00014817309],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863654,0.000111831665,0.00034152417,0.00015164212,0.00034341315,0.00041503974],"domain_scores_gemma":[0.9994205,0.00009616663,0.000008928759,0.00017076537,0.00023887299,0.00006476313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007917135,0.00009773719,0.00015779675,0.0004384101,0.00013969249,0.00008196556,0.00017229984,0.00006868304,0.00026457358],"category_scores_gemma":[0.00008428449,0.000104623745,0.000038025544,0.0005063272,0.000107332584,0.00016178338,0.00003346199,0.00027613036,0.000027214988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005505913,0.000044415912,0.0003573353,0.000023929864,0.000008723761,0.0000042237225,0.000119546115,0.992227,0.001103039,0.0010386347,0.00105494,0.0040126666],"study_design_scores_gemma":[0.0003848386,0.000018830739,0.0048849937,0.000036929872,8.7285514e-7,0.0000017603325,0.00040753375,0.94137704,0.052215803,0.00008053275,0.00048403317,0.00010679914],"about_ca_topic_score_codex":0.0007329223,"about_ca_topic_score_gemma":0.00036979665,"teacher_disagreement_score":0.051112764,"about_ca_system_score_codex":0.0000431861,"about_ca_system_score_gemma":0.000041134845,"threshold_uncertainty_score":0.42664325},"labels":[],"label_agreement":null},{"id":"W2055312886","doi":"10.1007/s10479-011-1000-6","title":"Minimizing the weighted number of tardy jobs with due date assignment and capacity-constrained deliveries","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Due date; Theory of computation; Polynomial-time approximation scheme; Mathematical optimization; Scheduling (production processes); Computer science; Job shop scheduling; Time complexity; Approximation algorithm; Scheme (mathematics); Mathematics; Algorithm; Schedule","score_opus":0.16662900496635066,"score_gpt":0.3454053241298946,"score_spread":0.17877631916354395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055312886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9798063,0.00015284709,0.013068095,0.00037976715,0.00002894547,0.00021534855,0.000026568834,0.000029376079,0.0062927394],"genre_scores_gemma":[0.93738663,0.00024560088,0.06218894,0.000014218797,0.00001522097,0.00002647223,0.0000059089853,0.000012175775,0.00010482338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991849,0.00009032388,0.00019643448,0.00010019482,0.00025815063,0.00016999904],"domain_scores_gemma":[0.99916375,0.000084617,0.000013281755,0.00019321384,0.00049216865,0.00005295664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005476919,0.00007356847,0.00012335506,0.000091056936,0.00016054389,0.00003633488,0.00012363419,0.000038299524,0.00020543473],"category_scores_gemma":[0.00006317881,0.000050247945,0.0000184026,0.0002727524,0.0003251507,0.0001469592,0.00003062043,0.00015397827,0.0000054477264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082552846,0.0013349006,0.037709936,0.0009910945,0.003119114,0.000078806115,0.12504327,0.62989265,0.030865094,0.1324858,0.0042278497,0.033425953],"study_design_scores_gemma":[0.00096877053,0.00033636746,0.010208217,0.0002160071,0.00003362641,0.00005212532,0.008204962,0.6043418,0.3743526,0.00027532695,0.0006383908,0.00037181686],"about_ca_topic_score_codex":0.00021259526,"about_ca_topic_score_gemma":0.000059709255,"teacher_disagreement_score":0.3434875,"about_ca_system_score_codex":0.0000041103817,"about_ca_system_score_gemma":0.00004275204,"threshold_uncertainty_score":0.22493662},"labels":[],"label_agreement":null},{"id":"W2056235974","doi":"10.1007/s10479-012-1168-4","title":"A cardinality constrained stochastic goal programming model with satisfaction functions for venture capital investment decision making","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Venture capital; Portfolio; Investment (military); Cardinality (data modeling); Social venture capital; Theory of computation; Business; Capital investment; Resource (disambiguation); Selection (genetic algorithm); Goal programming; Economics; Microeconomics; Computer science; Finance; Industrial organization; Operations research; Mathematics; Artificial intelligence","score_opus":0.12974704198774223,"score_gpt":0.4075030370474891,"score_spread":0.27775599505974685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056235974","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13706331,0.00017439884,0.8612029,0.0001125568,0.000057731326,0.000919852,0.00003217364,0.00007447657,0.00036257738],"genre_scores_gemma":[0.89493376,0.0000069871026,0.104520775,0.00001745816,0.0000516516,0.0003739639,0.000027529733,0.000021983884,0.000045902525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988292,0.00003858864,0.00024943956,0.00012709241,0.00036177906,0.00039391848],"domain_scores_gemma":[0.9990185,0.00016487944,0.000015084974,0.00017436343,0.0004978441,0.00012933364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074468117,0.00010697552,0.00015188902,0.00017472591,0.00028324535,0.00009029763,0.000063972824,0.000067157314,0.000027383792],"category_scores_gemma":[0.0002650134,0.00009158288,0.000058625195,0.0002968309,0.0001076181,0.0003537295,0.000024407622,0.00018146871,0.0000069395483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003499303,0.00010110431,0.00007394383,0.00010783111,0.00006496322,1.9472999e-7,0.00093242695,0.96461916,0.00028560552,0.013664198,0.0003920278,0.019723572],"study_design_scores_gemma":[0.0003182746,0.00016163595,0.00022569425,0.00012968534,0.00002262272,0.0000072754124,0.001123295,0.99659485,0.00024207661,0.00080624,0.00022496932,0.00014340157],"about_ca_topic_score_codex":0.000012534668,"about_ca_topic_score_gemma":0.000050847757,"teacher_disagreement_score":0.75787044,"about_ca_system_score_codex":0.000047978712,"about_ca_system_score_gemma":0.000065860026,"threshold_uncertainty_score":0.37346414},"labels":[],"label_agreement":null},{"id":"W2057126536","doi":"10.1007/s10479-007-0217-x","title":"Towards a practical engineering tool for rostering","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Atomic Energy of Canada Limited; University of Essex","keywords":"Computer science; Constraint programming; Concurrent constraint logic programming; Constraint satisfaction; Backtracking; Mathematical optimization; Constraint satisfaction problem; Constraint logic programming; Scheduling (production processes); Constraint learning; Solver; Artificial intelligence; Algorithm; Mathematics; Programming language; Stochastic programming","score_opus":0.7148603109203584,"score_gpt":0.6397327812247123,"score_spread":0.07512752969564607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057126536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5122179,0.00013321913,0.47458643,0.010750152,0.00018579068,0.00038466247,0.000028390512,0.000032432723,0.001681063],"genre_scores_gemma":[0.91938764,0.000012751317,0.07907131,0.00006619742,0.00015425356,0.00003575851,0.0000042219053,0.0000096732865,0.0012581957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727297,0.000102084734,0.0005465678,0.00027406454,0.0013046667,0.0004996376],"domain_scores_gemma":[0.9931601,0.0032837312,0.000025830755,0.00045303398,0.0029495019,0.00012776782],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.023138763,0.00006818064,0.00016296034,0.00068935985,0.00037195976,0.00032987166,0.00035020345,0.000069380905,0.00012377098],"category_scores_gemma":[0.047116287,0.000055615335,0.000107201755,0.0012979152,0.000088942645,0.0003982256,0.0001203915,0.00023259166,0.00009915904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005002341,0.0010657737,0.0016476227,0.00006815128,0.00022488281,0.00003285061,0.003887956,0.22363366,0.10206939,0.48773938,0.043294016,0.13583608],"study_design_scores_gemma":[0.0008038867,0.00070363306,0.017366443,0.00008783826,0.00001417231,0.000042311836,0.0017739729,0.6597208,0.16980982,0.009299179,0.13994558,0.00043238516],"about_ca_topic_score_codex":0.00007297985,"about_ca_topic_score_gemma":0.00005042401,"teacher_disagreement_score":0.4784402,"about_ca_system_score_codex":0.000014786668,"about_ca_system_score_gemma":0.00030524007,"threshold_uncertainty_score":0.96091026},"labels":[],"label_agreement":null},{"id":"W2057292389","doi":"10.1007/s10479-008-0400-8","title":"ADTreesLogit model for customer churn prediction","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Interpretability; Computer science; Tournament; Predictive modelling; CONTEST; Machine learning; Logistic regression; Artificial intelligence; Predictive analytics; Data mining; Mathematics","score_opus":0.44721775356797716,"score_gpt":0.43697198395609144,"score_spread":0.010245769611885724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057292389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93921506,0.00014066558,0.016944569,0.0062074433,0.00018207393,0.0013372381,0.000070430004,0.0001053123,0.035797205],"genre_scores_gemma":[0.99234414,0.00012516143,0.00053632975,0.0005294043,0.00041908512,0.00013574185,0.00016786545,0.000016784195,0.005725504],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881405,0.000015351441,0.00025800063,0.00019210305,0.00044715425,0.0002733192],"domain_scores_gemma":[0.9982676,0.000042489817,0.000029319914,0.0001911355,0.0014535469,0.000015929356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007331291,0.00007938365,0.00011702968,0.00054234854,0.0006011842,0.00010002178,0.00016716622,0.00005514432,0.00016366818],"category_scores_gemma":[0.00023105711,0.000073873045,0.000072581,0.0005824733,0.00012003436,0.0011483112,0.000064758584,0.000119293145,0.00020078565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003945354,0.0011090164,0.0105969105,0.0003870072,0.0001341038,0.0000065591794,0.0015635104,0.22325146,0.026587596,0.107565194,0.6142335,0.014170634],"study_design_scores_gemma":[0.0005020954,0.000032354357,0.0049259397,0.000018992241,0.000008329276,0.0000016301076,0.0002442741,0.97518396,0.0015548934,0.0007053192,0.016711427,0.00011079131],"about_ca_topic_score_codex":0.00027869825,"about_ca_topic_score_gemma":0.00018614913,"teacher_disagreement_score":0.7519325,"about_ca_system_score_codex":0.0000133048925,"about_ca_system_score_gemma":0.000096037824,"threshold_uncertainty_score":0.46238834},"labels":[],"label_agreement":null},{"id":"W2058073949","doi":"10.1007/s10479-008-0341-2","title":"The multiple server center location problem","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Server; Computer science; Computer network; Heuristic; Node (physics); Theory of computation; Center (category theory); Distributed computing; Algorithm; Artificial intelligence; Engineering","score_opus":0.2903116292438712,"score_gpt":0.3903968923203422,"score_spread":0.10008526307647098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058073949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9220395,0.0003003538,0.00066403527,0.045177612,0.00023131388,0.00117714,0.0000047480494,0.0000712574,0.030334001],"genre_scores_gemma":[0.99291694,0.00030843922,0.000076827,0.00053994654,0.00015976778,0.00010150351,0.00004553384,0.000008370359,0.0058426755],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986948,0.000043661264,0.00028196338,0.00016846087,0.00054082664,0.00027030098],"domain_scores_gemma":[0.99761295,0.000034086068,0.000013449697,0.00036003106,0.0019671954,0.000012300187],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013344364,0.00007014925,0.00007095978,0.00019623677,0.0011547966,0.00014792505,0.000320211,0.000027240674,0.00022844333],"category_scores_gemma":[0.00041002446,0.00005148055,0.000042434734,0.0008731503,0.00017326248,0.0007567776,0.000167086,0.00012110057,0.00087324245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001489551,0.0013308567,0.038200118,0.00049424643,0.00014753338,0.000005079013,0.0009638749,0.12711906,0.00070761185,0.29542175,0.5217038,0.013757135],"study_design_scores_gemma":[0.0005939222,0.000036221187,0.076905146,0.000048375332,0.0000053824256,0.0000014966944,0.000999685,0.19125395,0.0007319782,0.0009363463,0.7282514,0.00023610104],"about_ca_topic_score_codex":0.003993824,"about_ca_topic_score_gemma":0.0062089325,"teacher_disagreement_score":0.29448542,"about_ca_system_score_codex":0.000010308328,"about_ca_system_score_gemma":0.000046908463,"threshold_uncertainty_score":0.9999047},"labels":[],"label_agreement":null},{"id":"W2058302761","doi":"10.1007/s10479-006-7371-4","title":"On the interaction between retailers inventory policies and manufacturer trade deals in response to supply-uncertainty occurrences","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Fredericton; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Interval (graph theory); Point (geometry); Duration (music); Random variable; Operations research; Computer science; Variable (mathematics); Probability distribution; Supply chain; Distribution (mathematics); Mathematical optimization; Econometrics; Industrial organization; Microeconomics; Business; Economics; Mathematics; Statistics; Marketing; Algorithm","score_opus":0.1807015972807431,"score_gpt":0.39512304098745193,"score_spread":0.21442144370670885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058302761","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9326325,0.000054061267,0.000006106193,0.06170886,0.000057675894,0.0005393334,0.000009938228,0.000013787289,0.004977731],"genre_scores_gemma":[0.9968961,0.000025827008,0.000008273745,0.002089862,0.00024235179,0.00009454643,0.000031469226,0.000009681037,0.00060190505],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9984226,0.00021908773,0.00030838556,0.00023665326,0.00048964086,0.0003236154],"domain_scores_gemma":[0.99917626,0.00038504176,0.000035465473,0.0002443275,0.00013933361,0.000019567931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002842625,0.00011668335,0.00014730006,0.0009611188,0.00030749667,0.00034080326,0.00027539095,0.000044736516,0.00026740466],"category_scores_gemma":[0.0005181553,0.00008511353,0.000042510223,0.00069165486,0.00016001132,0.0005008947,0.00014832454,0.0002389276,0.00006327666],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012631145,0.0005308177,0.101795524,0.0002279505,0.0000931926,0.000013184726,0.0023259225,0.039221715,0.0029031078,0.19145316,0.65176064,0.008411672],"study_design_scores_gemma":[0.0007538331,0.00028245614,0.56321514,0.00040364408,0.000016334823,6.406964e-7,0.009906425,0.010422843,0.0033857913,0.01144935,0.39967942,0.00048413442],"about_ca_topic_score_codex":0.005874859,"about_ca_topic_score_gemma":0.002092049,"teacher_disagreement_score":0.4614196,"about_ca_system_score_codex":0.000035584955,"about_ca_system_score_gemma":0.000030168796,"threshold_uncertainty_score":0.8881069},"labels":[],"label_agreement":null},{"id":"W2058354071","doi":"10.1007/s10479-007-0303-0","title":"Stationary tail asymptotics of a tandem queue with feedback","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Queue; Fork–join queue; Bulk queue; Multilevel queue; Computer science; Mathematics; Queue management system; Computer network","score_opus":0.1236258459482162,"score_gpt":0.40466427930456744,"score_spread":0.28103843335635126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058354071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95101625,0.00012903332,0.01874636,0.002419101,0.000025074236,0.00031778438,0.000008359434,0.000031715597,0.027306348],"genre_scores_gemma":[0.9961713,0.000028449183,0.0021601636,0.00022583119,0.00014732266,0.0000082398865,0.000039523075,0.000016938915,0.0012022544],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853563,0.00003967034,0.0003422785,0.00017630548,0.0006224099,0.00028369363],"domain_scores_gemma":[0.996711,0.00022695864,0.00007490746,0.00028778045,0.0026820728,0.000017242519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026567995,0.00008589794,0.00017313095,0.00064872944,0.00024545964,0.00006807953,0.00023685375,0.00004274321,0.0002768552],"category_scores_gemma":[0.00063589343,0.00007279322,0.000048037793,0.0016094293,0.00026547414,0.00084969937,0.000098616416,0.00016808187,0.000057619218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005185115,0.0007589639,0.017942706,0.00027697833,0.00031949632,0.00003103774,0.00048140963,0.20195429,0.010143054,0.7535338,0.004810927,0.009228861],"study_design_scores_gemma":[0.0070156683,0.0016702423,0.16694856,0.0018910487,0.00047343626,0.000025080444,0.031927507,0.32049313,0.1500228,0.21102938,0.10536592,0.003137236],"about_ca_topic_score_codex":0.00034855778,"about_ca_topic_score_gemma":0.00081367214,"teacher_disagreement_score":0.5425044,"about_ca_system_score_codex":0.000012677262,"about_ca_system_score_gemma":0.000079274956,"threshold_uncertainty_score":0.30313703},"labels":[],"label_agreement":null},{"id":"W2060085351","doi":"10.1007/s10479-011-0869-4","title":"A survey of optimization models on cancer chemotherapy treatment planning","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Chemotherapy; Computer science; Colorectal cancer; Theory of computation; Limit (mathematics); Cancer treatment; Cancer chemotherapy; Cancer; Medicine; Mathematics; Surgery; Algorithm; Internal medicine","score_opus":0.7989043348658895,"score_gpt":0.5617408224880779,"score_spread":0.23716351237781164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060085351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96538,0.00019980283,0.016398473,0.0005026894,0.000024235374,0.00083001115,0.00010907522,0.000026794625,0.01652888],"genre_scores_gemma":[0.9860908,0.00024888673,0.012897418,0.000033190612,0.000012520317,0.00012270047,0.000017677297,0.000019113673,0.0005577189],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854517,0.00038406285,0.00036382044,0.00017587945,0.00030447778,0.0002265836],"domain_scores_gemma":[0.9979921,0.00060385134,0.00004901133,0.00034964932,0.0009464535,0.00005895719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014419928,0.000100543584,0.00027300973,0.00021375527,0.00009236707,0.000009801658,0.00018818703,0.00007362526,0.0005926829],"category_scores_gemma":[0.00063158065,0.00007441622,0.0000471241,0.00034445414,0.00015540031,0.00009017154,0.00002925621,0.000102796235,0.0000059130307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016598192,0.009963359,0.008942725,0.00055426906,0.0010988748,0.000014544646,0.03519841,0.22908501,0.003648348,0.69553775,0.0077955895,0.006501293],"study_design_scores_gemma":[0.0015477354,0.003321366,0.008406427,0.00045985126,0.000024113036,0.0000026285559,0.00048638514,0.6658008,0.24549267,0.07405946,0.000025517204,0.00037302182],"about_ca_topic_score_codex":0.0014037555,"about_ca_topic_score_gemma":0.00017215128,"teacher_disagreement_score":0.6214783,"about_ca_system_score_codex":0.000023608029,"about_ca_system_score_gemma":0.00013866597,"threshold_uncertainty_score":0.6489463},"labels":[],"label_agreement":null},{"id":"W2062940315","doi":"10.1007/s10479-015-1839-z","title":"Socially responsible service operations management: an overview","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Service design; Service delivery framework; Service (business); Service provider; Social responsibility; Service product management; Service system; Service level objective; Process management; Business; Service management; Service guarantee; Computer science; Marketing; Public relations; Knowledge management; Supply chain management; Political science; Supply chain","score_opus":0.572818528833708,"score_gpt":0.5040491163382387,"score_spread":0.0687694124954693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062940315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71704185,0.001545314,0.00023234637,0.13460697,0.00034668692,0.0016038759,0.000047990572,0.0002342952,0.1443407],"genre_scores_gemma":[0.96693486,0.0005344984,0.0034415238,0.019621475,0.00138451,0.00024408239,0.0004716755,0.00007162705,0.007295744],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99755263,0.0002303571,0.00043326282,0.0003474633,0.0009819069,0.0004543607],"domain_scores_gemma":[0.9954154,0.000047451616,0.000031408006,0.0006468193,0.0037899232,0.00006903339],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004691205,0.00014579073,0.00021790515,0.00070374744,0.0007225973,0.0007482974,0.0006835,0.0000902108,0.00059412327],"category_scores_gemma":[0.00024812922,0.00014491628,0.00006296721,0.0025907715,0.00009486496,0.0028983725,0.000420791,0.00025921702,0.0014176985],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104519786,0.000526733,0.00025040883,0.0003591124,0.00006351904,0.000010278793,0.0010432679,0.011065669,0.00029542984,0.9619752,0.021397136,0.0029086804],"study_design_scores_gemma":[0.0030317635,0.00030627393,0.019905722,0.0004615838,0.00012433513,0.000006317069,0.02944432,0.14376298,0.0012528575,0.0712984,0.72902757,0.001377908],"about_ca_topic_score_codex":0.010341565,"about_ca_topic_score_gemma":0.03599177,"teacher_disagreement_score":0.89067686,"about_ca_system_score_codex":0.000023613336,"about_ca_system_score_gemma":0.00047451552,"threshold_uncertainty_score":0.9993598},"labels":[],"label_agreement":null},{"id":"W2063786797","doi":"10.1007/s10479-015-1838-0","title":"Joint procurement and demand-side bidding strategies under price volatility","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bidding; Microeconomics; Procurement; Economics","score_opus":0.46616818802446325,"score_gpt":0.4270784907307665,"score_spread":0.03908969729369677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063786797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88444084,0.0006381808,0.00260513,0.012984587,0.00013577919,0.0009797966,0.0000029319867,0.000064100605,0.09814865],"genre_scores_gemma":[0.9979505,0.00005253919,0.00023271238,0.00058628625,0.00023714115,0.000060808106,0.000015915319,0.00001223614,0.0008518394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983991,0.000059257567,0.00029751012,0.00025435167,0.0006682658,0.00032156275],"domain_scores_gemma":[0.99847764,0.000028400294,0.000038076076,0.00025166993,0.0011656019,0.00003861825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003100614,0.000107947286,0.00014939936,0.00042568074,0.00028524862,0.0006257534,0.0001751914,0.000039368544,0.00017952545],"category_scores_gemma":[0.00033433212,0.000093514296,0.00003375579,0.0005393448,0.00014946057,0.0015245074,0.00032662344,0.00015187675,0.00006323432],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012496422,0.00075791957,0.0072169905,0.000941772,0.00019986361,0.000011964656,0.0015839246,0.02034429,0.0036163975,0.85391647,0.10639978,0.004885651],"study_design_scores_gemma":[0.002600088,0.0004069533,0.07311694,0.00044958628,0.000061314124,0.0000037511106,0.05600959,0.51373136,0.0053877626,0.09218985,0.25497565,0.0010671568],"about_ca_topic_score_codex":0.0010497799,"about_ca_topic_score_gemma":0.00037222702,"teacher_disagreement_score":0.7617266,"about_ca_system_score_codex":0.000026154205,"about_ca_system_score_gemma":0.00011393898,"threshold_uncertainty_score":0.6034155},"labels":[],"label_agreement":null},{"id":"W2064783481","doi":"10.1007/s10479-006-0001-3","title":"An integrated model for logistics network design","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":278,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Benders' decomposition; Theory of computation; Mathematical optimization; Computer science; Decomposition; Facility location problem; Selection (genetic algorithm); Linear programming relaxation; Range (aeronautics); Simplex algorithm; Simplex; Product (mathematics); Network planning and design; Relaxation (psychology); Integer programming; Operations research; Linear programming; Algorithm; Mathematics; Engineering; Artificial intelligence","score_opus":0.4520266462281747,"score_gpt":0.4442087261267259,"score_spread":0.007817920101448772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064783481","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007264134,0.000055305747,0.98638415,0.0030580459,0.00007555397,0.0007356792,0.000013700173,0.00004873347,0.0023647207],"genre_scores_gemma":[0.9784358,0.000027555407,0.01704764,0.00052917236,0.0004186762,0.00016873206,0.0003206306,0.00001490035,0.0030368632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988038,0.000040637802,0.00030633935,0.00020621075,0.00031220456,0.00033083232],"domain_scores_gemma":[0.9976596,0.000033700926,0.000013275331,0.00029909456,0.00198179,0.000012508965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021227468,0.00008576616,0.00011124937,0.00025266036,0.0004134923,0.00023147465,0.00028593492,0.000045067107,0.00015443414],"category_scores_gemma":[0.0002675814,0.00007906847,0.00004323807,0.00068710186,0.00009171883,0.0006043634,0.000055451488,0.00009152773,0.00007815023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027146778,0.00013620101,0.000040168175,0.000032813736,0.0000068433,1.6084756e-7,0.000011172691,0.7492351,0.00010922426,0.1562322,0.09326281,0.0009061594],"study_design_scores_gemma":[0.000116420815,0.000026424861,0.00019510514,0.0000092405135,0.0000052653218,3.2685275e-8,0.0000843019,0.97598535,0.00008901799,0.009035615,0.014368374,0.00008483554],"about_ca_topic_score_codex":0.003879403,"about_ca_topic_score_gemma":0.003651422,"teacher_disagreement_score":0.9711717,"about_ca_system_score_codex":0.000010462578,"about_ca_system_score_gemma":0.00006688307,"threshold_uncertainty_score":0.5864523},"labels":[],"label_agreement":null},{"id":"W2065558865","doi":"10.1007/s10479-009-0633-1","title":"Formulating diets for growing pigs: economic and environmental considerations","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Agriculture and Agri-Food Canada; Statistics Canada; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Production (economics); Theory of computation; Phosphorus; Environmental impact assessment; Natural resource economics; Computer science; Environmental science; Economics; Ecology; Biology; Chemistry; Microeconomics; Algorithm","score_opus":0.2383623986761651,"score_gpt":0.4094313781392495,"score_spread":0.17106897946308441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065558865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893631,0.00013075213,0.000005428569,0.00987546,0.000007487328,0.00021770484,0.000112648355,0.000006111011,0.0002813243],"genre_scores_gemma":[0.9988364,0.00013422388,0.00027930143,0.00048684824,0.000084545805,0.000018690851,0.00010288398,3.633285e-7,0.000056758454],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999484,0.000052639716,0.0001329914,0.000121550154,0.000059773683,0.00014901564],"domain_scores_gemma":[0.9995966,0.0002786508,0.000010185736,0.00002473022,0.000044047563,0.000045770143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002474115,0.000041109397,0.00007697815,0.000016069547,0.0004709972,0.000042725045,0.000042969987,0.000034572415,0.00021602328],"category_scores_gemma":[0.000061812345,0.000019988025,0.00003371671,0.00003391525,0.00006731544,0.00019353583,0.000019662626,0.000055364842,0.000005999013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028635934,0.000091300375,0.00033910474,0.0000031871543,0.000007440705,3.0110465e-7,0.000112082605,0.00020346322,0.9475022,0.037493046,0.0020262748,0.0121929655],"study_design_scores_gemma":[0.0013977973,0.009700193,0.6728622,0.000099766214,0.000014986884,0.000029707091,0.0059511852,0.06172984,0.09547378,0.124618925,0.027324611,0.00079702324],"about_ca_topic_score_codex":0.00005336895,"about_ca_topic_score_gemma":0.000102492566,"teacher_disagreement_score":0.8520284,"about_ca_system_score_codex":0.000005227447,"about_ca_system_score_gemma":0.000006677841,"threshold_uncertainty_score":0.36225775},"labels":[],"label_agreement":null},{"id":"W2067761883","doi":"10.1007/s10479-014-1584-8","title":"Optimal VaR-based risk management with reinsurance","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reinsurance; Monotonic function; Piecewise; Actuarial science; Imperfect; Mathematical optimization; Economics; Risk management; Computer science; Mathematical economics; Econometrics; Mathematics; Finance","score_opus":0.2638871786263751,"score_gpt":0.49962539047620635,"score_spread":0.23573821184983124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067761883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6332206,0.00014270002,0.2942692,0.004213472,0.0000711507,0.0006337794,0.000039641025,0.000031303516,0.067378126],"genre_scores_gemma":[0.9571759,0.0006450205,0.037430655,0.000099064564,0.0000432452,0.000048003607,0.000013102035,0.000010349806,0.0045346743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99601734,0.00079353916,0.00043669157,0.00037110376,0.00208208,0.00029923778],"domain_scores_gemma":[0.99608517,0.00059093436,0.00006502187,0.00082339183,0.0023235616,0.00011192831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008234114,0.00008823133,0.00017363885,0.0006195578,0.00048662804,0.00029854014,0.00060347497,0.0000447379,0.00029460614],"category_scores_gemma":[0.0013046755,0.00005939115,0.000053707932,0.001755006,0.0002208139,0.00033534004,0.00007144665,0.00018594967,0.0002481411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000916063,0.00010157632,0.0051475437,0.000003073142,0.000016487676,0.00000283571,0.00012539719,0.93840724,0.000027501002,0.00842286,0.007444868,0.040209003],"study_design_scores_gemma":[0.0007856066,0.00083721796,0.033880975,0.000043932225,0.00000877415,0.0000020755333,0.00040312676,0.85376364,0.006696246,0.0021694938,0.10119194,0.00021695471],"about_ca_topic_score_codex":0.00016702413,"about_ca_topic_score_gemma":0.000109077875,"teacher_disagreement_score":0.32395527,"about_ca_system_score_codex":0.00000687323,"about_ca_system_score_gemma":0.00009962752,"threshold_uncertainty_score":0.37427986},"labels":[],"label_agreement":null},{"id":"W2069326331","doi":"10.1007/s10479-006-0132-6","title":"Coherent multiperiod risk adjusted values and Bellman’s principle","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":426,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Ambiguity; Theory of computation; Measure (data warehouse); Coherent risk measure; Risk measure; Mathematics; Expected shortfall; Stability (learning theory); Value (mathematics); Spectral risk measure; Dynamic risk measure; Mathematical economics; Risk management; Applied mathematics; Statistics; Computer science; Economics; Algorithm; Data mining; Financial economics","score_opus":0.3529172039971666,"score_gpt":0.5307843923733416,"score_spread":0.17786718837617504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069326331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907372,0.0010182359,0.0020048583,0.0011422933,0.000054209424,0.00041329765,0.000058746366,0.000016656377,0.004554508],"genre_scores_gemma":[0.98316616,0.0028123169,0.0025372957,0.00002521866,0.00008167382,0.00003604431,0.000027908762,0.000009312245,0.0113040805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9965962,0.00067560293,0.0006032508,0.00035691363,0.0014831888,0.0002848557],"domain_scores_gemma":[0.9963684,0.0005835591,0.000068955575,0.0005089224,0.0023695237,0.000100656165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049736053,0.00009180224,0.00019659633,0.0005308685,0.00065263425,0.00034438624,0.00034927882,0.000075445845,0.00034297755],"category_scores_gemma":[0.0024229398,0.00006802062,0.000056120683,0.0010363524,0.00026698384,0.00040034237,0.00016180541,0.00019597044,0.000118354976],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017904656,0.000996571,0.29234183,0.000014921788,0.000069570415,0.000013246119,0.0040908335,0.416845,0.0043777856,0.021080839,0.12110585,0.13888451],"study_design_scores_gemma":[0.00074624276,0.00039430987,0.5495698,0.000026758671,0.0000103234825,0.000006334179,0.0016705933,0.35121807,0.01586317,0.011213009,0.069013245,0.00026816648],"about_ca_topic_score_codex":0.00214057,"about_ca_topic_score_gemma":0.0013057679,"teacher_disagreement_score":0.25722793,"about_ca_system_score_codex":0.000009043698,"about_ca_system_score_gemma":0.00012859206,"threshold_uncertainty_score":0.5019601},"labels":[],"label_agreement":null},{"id":"W2070062192","doi":"10.1007/s10479-008-0448-5","title":"On risk minimizing portfolios under a Markovian regime-switching Black-Scholes economy","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Hamilton–Jacobi–Bellman equation; Differential game; Dynamic risk measure; Markov chain; Mathematical economics; Markov process; Mathematical optimization; Risk measure; Mathematics; Measure (data warehouse); Stochastic differential equation; Stochastic control; Theory of computation; Computer science; Applied mathematics; Bellman equation; Economics; Optimal control; Finance; Portfolio","score_opus":0.21003555131041138,"score_gpt":0.3685797505975054,"score_spread":0.15854419928709404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070062192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60985076,0.0014768506,0.28264904,0.0073380657,0.00009910026,0.00078469474,0.0002853122,0.00004545418,0.097470716],"genre_scores_gemma":[0.9957477,0.0008833646,0.0014305704,0.00032476787,0.00014859732,0.00013231227,0.00002135558,0.000025239893,0.0012861054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99841106,0.000022395267,0.00063170126,0.00044233756,0.00009565153,0.00039685567],"domain_scores_gemma":[0.9986756,0.00020237545,0.00013127548,0.0005153531,0.0003516878,0.00012369706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011229059,0.00012826572,0.00029582702,0.00058516423,0.00079543295,0.00008740785,0.0003556042,0.00009958915,0.00021071444],"category_scores_gemma":[0.00067232345,0.00014441622,0.00011006865,0.0006723369,0.00020344702,0.00029680374,0.00008735568,0.00040254282,0.00064554426],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022731887,0.00019378583,0.00064801297,0.000014703334,0.00003820506,0.000003168623,0.00057453057,0.002810655,0.00002502739,0.99122125,0.0036695395,0.0007783702],"study_design_scores_gemma":[0.000964544,0.0005110996,0.021495812,0.00011581898,0.000007581407,0.000021874454,0.00087996904,0.02433606,0.001198519,0.90970284,0.04008377,0.00068211334],"about_ca_topic_score_codex":0.00089841534,"about_ca_topic_score_gemma":0.00006990414,"teacher_disagreement_score":0.38589692,"about_ca_system_score_codex":0.000035081866,"about_ca_system_score_gemma":0.00013883885,"threshold_uncertainty_score":0.8297381},"labels":[],"label_agreement":null},{"id":"W2070341979","doi":"10.1007/s10479-008-0484-1","title":"A new methodology for studying the equity premium","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Equity premium puzzle; Econometrics; Economics; Nonparametric statistics; Volatility (finance); Consumption (sociology); Equity (law); Risk premium; Equity risk; Microeconomics; Computer science; Finance","score_opus":0.924573456473488,"score_gpt":0.5460921382951337,"score_spread":0.3784813181783543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070341979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9037588,0.0028901582,0.043573823,0.027547883,0.00024085212,0.0012003598,0.00024558813,0.000017218352,0.020525282],"genre_scores_gemma":[0.9840579,0.0006039331,0.008290542,0.00042307915,0.00024642763,0.000072213275,0.000010378028,0.000011513984,0.006284001],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876195,0.00011379038,0.0004553007,0.0002257273,0.000043968193,0.00039926867],"domain_scores_gemma":[0.99880594,0.0005840922,0.000050488365,0.0003876476,0.00008547621,0.00008634467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047457106,0.000070330905,0.00025564933,0.00022832453,0.00055925513,0.000044900047,0.00039342587,0.000061001363,0.0004953485],"category_scores_gemma":[0.0011331914,0.000061387036,0.00010548632,0.00020908621,0.00013883424,0.00022205543,0.00013834266,0.00017721012,0.0001746434],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017925986,0.00023517814,0.011013163,0.0000569877,0.00035844414,0.0000021195106,0.011618011,0.03077753,0.0004358328,0.6677403,0.26907513,0.008508045],"study_design_scores_gemma":[0.003069865,0.0023138684,0.11074494,0.000040108145,0.000015878959,0.00006952662,0.0016864035,0.15851058,0.014803204,0.34042814,0.36736116,0.0009563407],"about_ca_topic_score_codex":0.0038847025,"about_ca_topic_score_gemma":0.00017462976,"teacher_disagreement_score":0.32731214,"about_ca_system_score_codex":0.000020260495,"about_ca_system_score_gemma":0.00009361387,"threshold_uncertainty_score":0.5872534},"labels":[],"label_agreement":null},{"id":"W2074707342","doi":"10.1007/s10479-013-1446-9","title":"Scheduling the two-machine open shop problem under resource constraints for setting the jobs","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Job shop scheduling; Theory of computation; Open shop; Computer science; Scheduling (production processes); Schedule; Mathematical optimization; Heuristic; Flow shop scheduling; Job shop; Distributed computing; Operations research; Mathematics; Algorithm; Artificial intelligence","score_opus":0.14985774713197367,"score_gpt":0.4181182125822349,"score_spread":0.2682604654502613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074707342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14922994,0.0032278202,0.5749714,0.19481726,0.00034413228,0.013126442,0.00020533227,0.0004024076,0.063675284],"genre_scores_gemma":[0.889232,0.00008494002,0.1079347,0.00056692946,0.00015382274,0.00060957816,0.000051789106,0.00004651136,0.0013197495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986182,0.0002025237,0.00031633137,0.00016941171,0.00032269448,0.0003708808],"domain_scores_gemma":[0.99797493,0.00070471264,0.000018221594,0.00039151835,0.00083901244,0.000071587194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002804582,0.00010505288,0.00012683615,0.000101855854,0.00079853967,0.00065457786,0.0007631099,0.000051316816,0.00029327648],"category_scores_gemma":[0.0004706795,0.000064331034,0.000051602372,0.00045951747,0.00025508605,0.0002759166,0.00017032417,0.00038921947,0.000055405242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035203238,0.000020439324,0.000030332101,0.000016925556,0.000051692383,1.3137604e-7,0.0006393763,0.9787579,0.000613768,0.007995645,0.0036386335,0.0082316175],"study_design_scores_gemma":[0.00028153334,0.000030999356,0.00007799117,0.000045195844,0.000004145844,0.000003134657,0.0026091316,0.9916266,0.0028592087,0.0007102699,0.0016604045,0.00009136238],"about_ca_topic_score_codex":0.00021162127,"about_ca_topic_score_gemma":0.00008348179,"teacher_disagreement_score":0.74000204,"about_ca_system_score_codex":0.000015043258,"about_ca_system_score_gemma":0.00010155397,"threshold_uncertainty_score":0.6312109},"labels":[],"label_agreement":null},{"id":"W2075525742","doi":"10.1007/s10479-014-1774-4","title":"Value-based argumentation for policy decision analysis: methodology and an exploratory case study of a hydroelectric project in Québec","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval","funders":"","keywords":"Argumentative; Argumentation theory; Commission; Context (archaeology); Process (computing); Computer science; Value (mathematics); Lottery; Management science; Operations research; Political science; Economics; Epistemology; Law; Mathematics; Microeconomics","score_opus":0.6681727687590614,"score_gpt":0.5982211880253314,"score_spread":0.06995158073372998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075525742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.790858,0.00011019327,0.20773557,0.00032967117,0.000012063237,0.0009396685,0.0000033102683,0.0000066417742,0.000004899147],"genre_scores_gemma":[0.98023325,0.000009312264,0.019432705,0.000026409509,0.000021158969,0.00025368706,0.000006616191,0.000004756446,0.000012080926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967346,0.0019169807,0.0004382965,0.0003030457,0.00042215403,0.0001849082],"domain_scores_gemma":[0.99786085,0.000609346,0.00006500446,0.00037856525,0.0010086668,0.00007754241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006331301,0.00007064948,0.00023687058,0.0024713476,0.000121724865,0.00006838429,0.00022877089,0.000043388758,7.0946993e-7],"category_scores_gemma":[0.0010372326,0.00006227399,0.00003589632,0.002895179,0.000036505688,0.0005570588,0.000060359453,0.00007674966,4.997321e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008244091,0.009591576,0.0687915,0.00022447719,0.00075315096,0.00017184216,0.23841989,0.5496032,0.01923976,0.017297424,0.0009434854,0.09413924],"study_design_scores_gemma":[0.0013526259,0.0024092516,0.002524401,0.000011520332,0.000017783786,0.000008061468,0.007814273,0.98128957,0.0042240177,0.0002533752,0.000015902931,0.000079193785],"about_ca_topic_score_codex":0.12350791,"about_ca_topic_score_gemma":0.12281074,"teacher_disagreement_score":0.43168634,"about_ca_system_score_codex":0.000056602552,"about_ca_system_score_gemma":0.0011551826,"threshold_uncertainty_score":0.8931957},"labels":[],"label_agreement":null},{"id":"W2076293072","doi":"10.1007/s10479-006-0080-1","title":"Column generation for IMRT cancer therapy optimization with implementable segments","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Beam (structure); Intensity (physics); Column generation; Intensity modulation; Computer science; Optics; Mathematical optimization; Mathematics; Algorithm; Physics","score_opus":0.1919182538019815,"score_gpt":0.49688641075100853,"score_spread":0.304968156949027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076293072","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.093493804,0.00029812622,0.90253377,0.0009344965,0.000021289981,0.0015009001,0.00023777943,0.000023450562,0.0009563655],"genre_scores_gemma":[0.8083755,0.00041502848,0.18347096,0.00010370347,0.0005847145,0.0025950116,0.0008437947,0.00004800614,0.0035633086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99906254,0.000060009716,0.00019628482,0.00018625666,0.00024426088,0.0002506469],"domain_scores_gemma":[0.99882734,0.000029895498,0.00003179478,0.0001818252,0.0009012547,0.0000279058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033389253,0.00008214768,0.000110820794,0.00011268093,0.00035965902,0.000083520936,0.000107913955,0.000022060001,0.00068010925],"category_scores_gemma":[0.0000025578738,0.000070622606,0.000032751854,0.0002668507,0.0000587403,0.00030860596,0.0000129053215,0.00006762685,4.8732375e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009674834,0.00040507587,0.010392639,0.000009090328,0.00012447442,1.3233236e-7,0.0001350782,0.8202978,0.105150275,0.017090663,0.033356592,0.012941448],"study_design_scores_gemma":[0.0012642106,0.00058820716,0.00031162528,0.000023048719,0.0000051058996,2.1402698e-7,0.000110068024,0.2096735,0.767352,0.00065795064,0.019802772,0.00021129647],"about_ca_topic_score_codex":0.003068058,"about_ca_topic_score_gemma":0.00022522724,"teacher_disagreement_score":0.7190628,"about_ca_system_score_codex":0.000025273703,"about_ca_system_score_gemma":0.00014665534,"threshold_uncertainty_score":0.74467194},"labels":[],"label_agreement":null},{"id":"W2076520672","doi":"10.1023/b:anor.0000039518.73626.a5","title":"GENI Ants for the Traveling Salesman Problem","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Travelling salesman problem; Heuristic; Theory of computation; Benchmark (surveying); Mathematical optimization; Ant colony optimization algorithms; Probabilistic logic; Computer science; Ant colony; Bottleneck traveling salesman problem; Set (abstract data type); Nearest neighbour algorithm; Traveling purchaser problem; 2-opt; Mathematics; Algorithm; Artificial intelligence","score_opus":0.3811311709820421,"score_gpt":0.4971652540370582,"score_spread":0.11603408305501611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076520672","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024083953,0.0003206726,0.9697768,0.02518013,0.00006161031,0.0011710854,0.000016502368,0.0000308751,0.0010339037],"genre_scores_gemma":[0.46863568,0.00079056725,0.52742827,0.00025505244,0.00014272127,0.0004905454,0.000014663899,0.00002319459,0.002219281],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997605,0.00021360305,0.00035612777,0.00033110526,0.00099378,0.0005003716],"domain_scores_gemma":[0.9959151,0.00058527914,0.000024194745,0.00074449653,0.0026094287,0.000121503195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040605944,0.000088990164,0.00013650401,0.00026023723,0.0008548106,0.0004114754,0.0015170428,0.00005155618,0.000042170712],"category_scores_gemma":[0.0010754762,0.00006357532,0.00007263923,0.0012351258,0.00021158563,0.00041449085,0.00027441652,0.00026531715,0.00005838804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020484198,0.00033086172,0.000022079257,0.00006091582,0.000086485656,0.0000056009935,0.0021627448,0.46508673,0.002671116,0.47934797,0.0036981276,0.046506893],"study_design_scores_gemma":[0.00065424276,0.00030763145,0.00045010477,0.00003888165,0.0000031054872,0.000009271831,0.00017174929,0.9559102,0.02640718,0.010693294,0.0052057384,0.00014860497],"about_ca_topic_score_codex":0.00016983916,"about_ca_topic_score_gemma":0.000068506844,"teacher_disagreement_score":0.49082348,"about_ca_system_score_codex":0.000023462717,"about_ca_system_score_gemma":0.0006782581,"threshold_uncertainty_score":0.6574598},"labels":[],"label_agreement":null},{"id":"W2079017824","doi":"10.1007/s10479-010-0722-1","title":"Approximate performance analysis of CONWIP disciplines in unreliable non homogeneous transfer lines","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Block (permutation group theory); Constant (computer programming); Theory of computation; Transfer line; Computer science; Mathematical optimization; Mathematics; Applied mathematics; Algorithm; Combinatorics; Engineering","score_opus":0.09388804598088185,"score_gpt":0.39155705456211143,"score_spread":0.2976690085812296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079017824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963261,0.00004333962,0.00089194305,0.0007256302,0.000044544202,0.00021776109,0.00001338075,0.000014771316,0.0017225118],"genre_scores_gemma":[0.9986501,0.00010344571,0.00033317748,0.000059306334,0.00012229917,0.000048640308,0.0000734961,0.000016101594,0.00059343287],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844635,0.000034955017,0.00050093397,0.00026851223,0.00042247164,0.00032681163],"domain_scores_gemma":[0.9979747,0.00013481714,0.000040884872,0.00046566036,0.0013676337,0.000016310045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020642257,0.000120921155,0.0003850884,0.002112887,0.00022140094,0.00009548054,0.00039829264,0.00007359494,0.00033227776],"category_scores_gemma":[0.0004275872,0.00010494707,0.00014313628,0.004919596,0.00025737818,0.0008748327,0.000120980985,0.00029448207,0.000027488597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016518153,0.0005217632,0.046936274,0.00029781825,0.0004303658,0.000005226445,0.0003363439,0.81709725,0.10570596,0.025464362,0.0001252446,0.0029142012],"study_design_scores_gemma":[0.00025727067,0.000028937477,0.014480458,0.000054932414,0.00016075495,3.3455288e-7,0.00027281448,0.9535978,0.029466776,0.00081496645,0.0006810788,0.00018390203],"about_ca_topic_score_codex":0.0007488293,"about_ca_topic_score_gemma":0.005915078,"teacher_disagreement_score":0.13650052,"about_ca_system_score_codex":0.000004961075,"about_ca_system_score_gemma":0.00004259459,"threshold_uncertainty_score":0.4279617},"labels":[],"label_agreement":null},{"id":"W2080610036","doi":"10.1007/s10479-008-0337-y","title":"Efficient solution approaches for a discrete multi-facility competitive interaction model","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.5969619837764057,"score_gpt":0.47512096968329526,"score_spread":0.12184101409311049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080610036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018500539,0.00004228961,0.9757621,0.0037822463,0.00003248258,0.0007892613,0.00005530624,0.00003639263,0.0009993826],"genre_scores_gemma":[0.8817366,0.00006078245,0.11709501,0.00004468314,0.000012374067,0.00021029772,0.000043950513,0.0000043928753,0.0007919575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983284,0.00025864,0.00027009792,0.0003300263,0.00048448762,0.00032835943],"domain_scores_gemma":[0.9978892,0.00013286616,0.000024473375,0.00036239857,0.0014890924,0.00010194555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012125868,0.00008135835,0.00012686066,0.0002761139,0.0007082225,0.00009876609,0.00040050203,0.00004961136,0.000011575588],"category_scores_gemma":[0.0003671561,0.00007358801,0.00007665064,0.0004857657,0.00022538612,0.00037509282,0.0001934257,0.00019707248,0.00002329158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021439795,0.0002917554,0.000018753597,0.000017676835,0.000011643512,3.796694e-7,0.002359781,0.9434327,0.00073311257,0.05125589,0.00040983257,0.0014470181],"study_design_scores_gemma":[0.00026950106,0.00012621505,0.00018972604,0.000012182749,6.086251e-7,0.0000025145425,0.00017729063,0.9961651,0.0026199196,0.0001409526,0.00022186358,0.00007415681],"about_ca_topic_score_codex":0.00007502993,"about_ca_topic_score_gemma":0.000049665254,"teacher_disagreement_score":0.863236,"about_ca_system_score_codex":0.000034683104,"about_ca_system_score_gemma":0.0002684955,"threshold_uncertainty_score":0.5447146},"labels":[],"label_agreement":null},{"id":"W2080833522","doi":"10.1023/b:anor.0000011190.86293.c1","title":"Unreliable Transfer Lines: Decomposition/Aggregation and Optimization","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; Université de Montréal","funders":"","keywords":"Computer science; Theory of computation; Scalability; Mathematical optimization; Transfer (computing); Obstacle; Line (geometry); Transfer line; Decomposition; Monte Carlo method; Measure (data warehouse); Algorithm; State (computer science); Mathematics; Parallel computing; Data mining; Engineering","score_opus":0.09345254129689068,"score_gpt":0.39678575484226725,"score_spread":0.30333321354537657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080833522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61459064,0.00031512673,0.36820197,0.011794215,0.000061302795,0.00047737526,0.0000069711923,0.00007970591,0.0044726846],"genre_scores_gemma":[0.99381393,0.00019664058,0.005121081,0.00039468802,0.00017551523,0.000028977802,0.00008243681,0.000014798819,0.00017192998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990839,0.000031076303,0.0002288336,0.00018833607,0.00028422783,0.00018365523],"domain_scores_gemma":[0.9985874,0.000057246805,0.000016215028,0.00017361679,0.0011515076,0.000014002415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008540997,0.000076562545,0.00011465877,0.0005110238,0.00043886274,0.00020182527,0.000117052135,0.000045958044,0.00013274756],"category_scores_gemma":[0.00031846517,0.000073991134,0.00003638365,0.0010217099,0.00012494833,0.0015223111,0.000045437842,0.00011586922,0.000043805467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022959704,0.00006856581,0.000055911783,0.00003221234,0.000015568598,9.65425e-7,0.000055401146,0.8770779,0.0010291069,0.12046226,0.00007883556,0.0011003363],"study_design_scores_gemma":[0.0014151294,0.000101702804,0.0003529804,0.0003489234,0.0000625284,0.000004074088,0.0008844282,0.88850516,0.03367082,0.07041243,0.0038131087,0.0004287379],"about_ca_topic_score_codex":0.00049230247,"about_ca_topic_score_gemma":0.00018020906,"teacher_disagreement_score":0.3792233,"about_ca_system_score_codex":0.000013218279,"about_ca_system_score_gemma":0.00003716423,"threshold_uncertainty_score":0.33754218},"labels":[],"label_agreement":null},{"id":"W2081475278","doi":"10.1007/s10479-008-0498-8","title":"Metaheuristic methods based on Tabu search for assigning judges to competitions","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Tabu search; Metaheuristic; Guided Local Search; Theory of computation; Mathematical optimization; Computer science; Parallel metaheuristic; Algorithm; Mathematics","score_opus":0.5076506407332314,"score_gpt":0.5271131455140821,"score_spread":0.019462504780850653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081475278","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12566854,0.0011180128,0.70096445,0.0802061,0.00025283702,0.0022186826,0.001106132,0.00005391335,0.088411346],"genre_scores_gemma":[0.9651252,0.00010043506,0.031675126,0.0012734784,0.00009077141,0.00008059404,0.00006292908,0.000013931646,0.001577502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864376,0.000061095816,0.00046890357,0.00032011367,0.00012412693,0.00038200305],"domain_scores_gemma":[0.9984775,0.00033312105,0.000034072917,0.00042240438,0.00059470604,0.00013819663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045071193,0.00009416006,0.00028942068,0.0009080883,0.0004304849,0.0001494187,0.000270525,0.000053683572,0.000686556],"category_scores_gemma":[0.0006003315,0.000098017146,0.00011147001,0.00076790544,0.000060185554,0.00012515274,0.00002630963,0.00019918446,0.00014685882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050587383,0.0003759363,0.0016510738,0.00002996132,0.000037490725,0.0000013145442,0.00028254106,0.25808996,0.00046846567,0.7239687,0.009944921,0.0050990814],"study_design_scores_gemma":[0.00041480229,0.0014693394,0.0230852,0.000055551576,0.0000050905805,5.759159e-7,0.00013089462,0.86890054,0.009691321,0.0077269026,0.088236846,0.0002829531],"about_ca_topic_score_codex":0.00012805284,"about_ca_topic_score_gemma":0.000024178382,"teacher_disagreement_score":0.8394567,"about_ca_system_score_codex":0.000028267084,"about_ca_system_score_gemma":0.00008219536,"threshold_uncertainty_score":0.7517306},"labels":[],"label_agreement":null},{"id":"W2082595178","doi":"10.1007/s10479-012-1255-6","title":"Lifetime properties of a cumulative shock model with a cluster structure","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Shock (circulatory); Cluster (spacecraft); Poisson distribution; Poisson process; Homogeneous; Theory of computation; Econometrics; Statistical physics; Computer science; Mathematics; Physics; Statistics","score_opus":0.5864984643594849,"score_gpt":0.5290907948433135,"score_spread":0.05740766951617149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082595178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98803353,0.00050589856,0.0057059405,0.0038370825,0.000016142065,0.0004994123,0.00006600131,0.000006431124,0.001329579],"genre_scores_gemma":[0.9932343,0.000026195887,0.0038639063,0.00009260169,0.000036776215,0.00002528369,0.0000025582017,0.000008137565,0.0027102858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996183,0.0006141392,0.00053048413,0.0002563964,0.0020355566,0.00038043092],"domain_scores_gemma":[0.9951664,0.00032295097,0.000052713644,0.00065684627,0.0036592332,0.00014186159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049456717,0.0000978615,0.00026959757,0.00037856228,0.0002615749,0.000096420175,0.0005783447,0.00008611578,0.00016807156],"category_scores_gemma":[0.0021260364,0.000051967978,0.00006567055,0.00089777046,0.00061408227,0.0010885444,0.00023230806,0.00026009168,0.000030297226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005123223,0.00047184684,0.0028038118,0.000038251997,0.000064778746,2.9748847e-7,0.021237217,0.9324833,0.017442714,0.019296093,0.0036752094,0.0019741657],"study_design_scores_gemma":[0.0003336338,0.00031401936,0.0012270161,0.00007786076,0.0000057910793,0.0000038259527,0.0014378282,0.8807692,0.09814364,0.017178293,0.0003605895,0.00014830676],"about_ca_topic_score_codex":0.00018738282,"about_ca_topic_score_gemma":0.00027442884,"teacher_disagreement_score":0.08070092,"about_ca_system_score_codex":0.000011489256,"about_ca_system_score_gemma":0.00038547014,"threshold_uncertainty_score":0.2545218},"labels":[],"label_agreement":null},{"id":"W2083462405","doi":"10.1007/s10479-007-0298-6","title":"Geometric decay in level-expanding QBD models","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Theory of computation; Computer science; Mathematics; Statistical physics; Physics; Algorithm","score_opus":0.36884821049072797,"score_gpt":0.466892429795915,"score_spread":0.09804421930518703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083462405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88534373,0.00029672403,0.06316277,0.0011964036,0.000048233353,0.00028198524,0.000003805276,0.00003631103,0.04963005],"genre_scores_gemma":[0.9977937,0.000061830484,0.0006476911,0.00021196909,0.00020237092,0.000015276975,0.000017581613,0.000017283086,0.0010323207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826235,0.000043173906,0.00039585403,0.00024530033,0.0005642436,0.0004890827],"domain_scores_gemma":[0.9983591,0.00028497927,0.000039528113,0.0003068906,0.0009901233,0.000019403698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063721417,0.0000941531,0.00018418298,0.003734822,0.00029915472,0.00016302709,0.0003392036,0.000059050875,0.00022484614],"category_scores_gemma":[0.00073278736,0.00009124082,0.000065673434,0.005769301,0.000105462095,0.0018049487,0.00020175471,0.00026648716,0.00012963508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009239399,0.00028597174,0.003399606,0.000072707466,0.000046033732,0.000028129522,0.00019047881,0.5099426,0.0041102665,0.46429524,0.0010053092,0.016531268],"study_design_scores_gemma":[0.0021521812,0.00012592324,0.021710336,0.0004730338,0.000053973803,0.000005134859,0.0059892833,0.71093154,0.07434588,0.16130628,0.021507328,0.0013991394],"about_ca_topic_score_codex":0.0014928353,"about_ca_topic_score_gemma":0.0016634212,"teacher_disagreement_score":0.30298895,"about_ca_system_score_codex":0.000029573903,"about_ca_system_score_gemma":0.000034623,"threshold_uncertainty_score":0.37206927},"labels":[],"label_agreement":null},{"id":"W2084750728","doi":"10.1007/s10479-014-1663-x","title":"A short-turning policy for the management of demand disruptions in rapid transit systems","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":89,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Occupancy; Offset (computer science); Operations research; Transit (satellite); Theory of computation; Service (business); Demand management; Service level; Service quality; On demand; Order (exchange); Transport engineering; Business; Public transport; Economics; Engineering; Marketing","score_opus":0.219226179489936,"score_gpt":0.49442628401764077,"score_spread":0.27520010452770477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084750728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4299203,0.0021410834,0.49242046,0.03739635,0.00024447692,0.005834023,0.00017216562,0.00006148942,0.031809665],"genre_scores_gemma":[0.9971639,0.0010483557,0.00082925137,0.000015289646,0.000054206863,0.00022529777,0.000023592609,0.0000046331525,0.0006354903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884874,0.00026802107,0.00024186067,0.00009785339,0.00035258415,0.00019095109],"domain_scores_gemma":[0.9990374,0.0003339403,0.00001594471,0.00012200443,0.00045370695,0.000037038244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031596322,0.000037605434,0.00008876079,0.00023610539,0.0005280259,0.00005737192,0.00016783034,0.000037728525,0.000011645347],"category_scores_gemma":[0.00014090705,0.000030004992,0.000037347087,0.00067676045,0.00016522627,0.0001284915,0.0000054794355,0.00007506933,0.0000011000777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002276105,0.0000694002,0.00095302897,0.000096983575,0.000039037586,2.5427283e-7,0.011824868,0.6141611,0.00009234833,0.36452332,0.00027379597,0.007943112],"study_design_scores_gemma":[0.0017998195,0.0005549037,0.21447322,0.0011475509,0.00008821553,9.155279e-7,0.10698089,0.5625297,0.0012056921,0.0016871211,0.109047525,0.00048444746],"about_ca_topic_score_codex":0.0023129042,"about_ca_topic_score_gemma":0.001897414,"teacher_disagreement_score":0.5672436,"about_ca_system_score_codex":0.000011085826,"about_ca_system_score_gemma":0.00009233962,"threshold_uncertainty_score":0.40612018},"labels":[],"label_agreement":null},{"id":"W2085278007","doi":"10.1007/s10479-006-0149-x","title":"Time-cost trade-off via optimal control theory in Markov PERT networks","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Mathematical optimization; Minification; Erlang (programming language); Markov decision process; Computer science; Optimal control; Control (management); Markov chain; Variance (accounting); Stochastic programming; Function (biology); Markov process; Mathematics; Statistics; Economics; Artificial intelligence; Algorithm","score_opus":0.21522929893561688,"score_gpt":0.49586635955987185,"score_spread":0.280637060624255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085278007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7621028,0.0017015993,0.193898,0.010700349,0.00014498133,0.0021838914,0.00005385333,0.000047817575,0.0291667],"genre_scores_gemma":[0.9945761,0.000074509866,0.0025996845,0.00042604635,0.00017685468,0.000049889084,0.000011280757,0.00002207342,0.0020635657],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9926198,0.002082334,0.0012591988,0.00062033674,0.002403183,0.0010151207],"domain_scores_gemma":[0.9899639,0.007775846,0.00007248481,0.00080951006,0.0011143023,0.0002639667],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.053558987,0.00017801509,0.00042405736,0.0015188145,0.0004322874,0.00038932962,0.001255826,0.00020903679,0.001836507],"category_scores_gemma":[0.009463204,0.00014060737,0.0001670267,0.0026443554,0.00079307694,0.0005246805,0.00016531118,0.0008844687,0.00028267875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013353026,0.00054027856,0.004057089,0.000007260607,0.00008748705,0.00011641418,0.004168569,0.4609464,0.009652186,0.0048927874,0.009842463,0.50435376],"study_design_scores_gemma":[0.0012776697,0.00035435095,0.014633969,0.000059244932,0.0000052388514,0.000038070615,0.0039607934,0.9664142,0.0039481227,0.0011332323,0.007852233,0.00032288898],"about_ca_topic_score_codex":0.00008284338,"about_ca_topic_score_gemma":0.00017016985,"teacher_disagreement_score":0.5054678,"about_ca_system_score_codex":0.00003815317,"about_ca_system_score_gemma":0.00031197822,"threshold_uncertainty_score":0.99907595},"labels":[],"label_agreement":null},{"id":"W2085298416","doi":"10.1007/s10479-005-2036-2","title":"An Improved IP Formulation for the Uncapacitated Facility Location Problem: Capitalizing on Objective Function Structure","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Facility location problem; Curse of dimensionality; Mathematical optimization; Theory of computation; Integer programming; Cover (algebra); 1-center problem; Set cover problem; Function (biology); Set (abstract data type); Mathematics; Computer science; Linear programming; Integer (computer science); Algorithm; Statistics","score_opus":0.16403196814602014,"score_gpt":0.39028646346626944,"score_spread":0.2262544953202493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085298416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9393758,0.00013814936,0.03832719,0.01542132,0.00027284474,0.004614459,0.00009883024,0.00012709481,0.001624319],"genre_scores_gemma":[0.9977852,0.000015024825,0.00022275097,0.0006207485,0.0002995741,0.00026524806,0.0004621908,0.000010528851,0.0003187291],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985505,0.000048020323,0.00035963935,0.00031100938,0.00044397733,0.00028686767],"domain_scores_gemma":[0.9965803,0.00005949079,0.00003568451,0.00041231493,0.0028950954,0.000017089938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017183498,0.00012589776,0.00010976302,0.00035042388,0.00091160636,0.00027630516,0.00023587754,0.00006665601,0.0002652562],"category_scores_gemma":[0.00039426878,0.000095879055,0.00005495929,0.0008405085,0.00006243764,0.001770325,0.000041659212,0.0001701193,0.00006627884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034437215,0.00032843943,0.00019028642,0.00022271312,0.00008795631,3.8324874e-8,0.00083377684,0.84113914,0.008173953,0.10422697,0.00443627,0.040016104],"study_design_scores_gemma":[0.00037304586,0.00015777764,0.010535518,0.000017622524,0.000019973419,7.8723396e-8,0.0016965569,0.97187895,0.00236463,0.002476954,0.010335117,0.0001437844],"about_ca_topic_score_codex":0.0028305913,"about_ca_topic_score_gemma":0.009844227,"teacher_disagreement_score":0.13073982,"about_ca_system_score_codex":0.000049020473,"about_ca_system_score_gemma":0.000057141613,"threshold_uncertainty_score":0.7011431},"labels":[],"label_agreement":null},{"id":"W2086396347","doi":"10.1007/s10479-006-5293-9","title":"Discrete-time analysis of the GI/G/1 system with Bernoulli retrials: An algorithmic approach","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bernoulli's principle; Markov chain; Computer science; Independence (probability theory); Theory of computation; Mathematical optimization; Algorithm; Bernoulli process; Markov chain Monte Carlo; Matrix (chemical analysis); Continuous-time Markov chain; Exploit; Set (abstract data type); Markov process; Discrete time and continuous time; Applied mathematics; Mathematics; Markov property; Markov model; Bayesian probability; Artificial intelligence","score_opus":0.087525396369387,"score_gpt":0.3652298565749086,"score_spread":0.2777044602055216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086396347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96387506,0.00015808914,0.013749614,0.001237097,0.000031845808,0.0008586931,0.000068859,0.0000741448,0.019946594],"genre_scores_gemma":[0.9972384,0.000004345688,0.0008794915,0.00003599134,0.00027874077,0.00004669483,0.00016512911,0.000022854265,0.0013283442],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975974,0.00029337886,0.000510798,0.00034943965,0.000927778,0.0003212336],"domain_scores_gemma":[0.99715865,0.00013323009,0.00016361852,0.0008888459,0.0016397259,0.000015942442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033299858,0.00014204059,0.00045414432,0.0011669111,0.00053375633,0.00021891814,0.0006665051,0.00006520985,0.00011252486],"category_scores_gemma":[0.00029416813,0.000091315065,0.00021245853,0.006518924,0.00035316712,0.0009702739,0.00018436709,0.00019940326,0.000022480954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001192672,0.00031625733,0.0021475153,0.0001337526,0.0008881875,0.0000022277836,0.000084594154,0.8577474,0.0033027038,0.1343406,0.0005062072,0.00041127895],"study_design_scores_gemma":[0.00027742112,0.000041636657,0.004020509,0.000071846596,0.00060187414,7.796562e-7,0.0011041474,0.9908235,0.001683619,0.00064451975,0.000535098,0.00019507018],"about_ca_topic_score_codex":0.0044628144,"about_ca_topic_score_gemma":0.00071568653,"teacher_disagreement_score":0.13369608,"about_ca_system_score_codex":0.000025072894,"about_ca_system_score_gemma":0.000055307923,"threshold_uncertainty_score":0.67464703},"labels":[],"label_agreement":null},{"id":"W2088808478","doi":"10.1007/s10479-014-1623-5","title":"Modeling the impact of donor behavior on humanitarian aid operations","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Cash; Donation; Extant taxon; Quality (philosophy); Computer science; Business; Operations research; Marketing; Finance; Political science; Law; Engineering","score_opus":0.25439708570970443,"score_gpt":0.4529091149931896,"score_spread":0.19851202928348516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088808478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9713479,0.000032983433,0.0008335573,0.006685885,0.000051237483,0.00043683345,0.00001024313,0.000018106943,0.020583244],"genre_scores_gemma":[0.99881464,0.00004003381,0.000118511736,0.00037442887,0.00023166789,0.00007737664,0.000035136905,0.00001376256,0.00029441336],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987061,0.000103630875,0.00032446443,0.00017009792,0.0004946625,0.00020101272],"domain_scores_gemma":[0.9978095,0.00013194511,0.000028012568,0.00035900256,0.0016555425,0.000015992948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019552852,0.00009203729,0.00013308825,0.00044838517,0.0007732715,0.00036324657,0.00034053903,0.000046603116,0.0008275568],"category_scores_gemma":[0.0006133469,0.000060942704,0.0001082745,0.00059561455,0.00010237266,0.001114791,0.00007261867,0.00023456258,0.0001145202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007741519,0.0010694372,0.0013071438,0.00003255222,0.00008076054,8.5762497e-7,0.00036667392,0.5930725,0.0039183777,0.3919336,0.0024724684,0.0056682453],"study_design_scores_gemma":[0.0006086638,0.0002001308,0.006492015,0.000047128124,0.00003647881,0.0000010186942,0.0006741921,0.9852991,0.001323078,0.0010502037,0.004107144,0.0001608475],"about_ca_topic_score_codex":0.009770183,"about_ca_topic_score_gemma":0.003202261,"teacher_disagreement_score":0.3922266,"about_ca_system_score_codex":0.00000663952,"about_ca_system_score_gemma":0.000079398065,"threshold_uncertainty_score":0.99682385},"labels":[],"label_agreement":null},{"id":"W2089233175","doi":"10.1023/b:anor.0000039515.90453.1d","title":"Path Relinking, Cycle-Based Neighbourhoods and Capacitated Multicommodity Network Design","year":2004,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":125,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Tabu search; Theory of computation; Path (computing); Mathematical optimization; Mathematics; Heuristic; Set (abstract data type); Local search (optimization); Network planning and design; Computer science; Algorithm","score_opus":0.18403810617067948,"score_gpt":0.3873745427847574,"score_spread":0.20333643661407794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089233175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062604606,0.00040222422,0.933629,0.0012770935,0.000048251142,0.0005529463,0.0000073634355,0.00016248834,0.0013160805],"genre_scores_gemma":[0.8560601,0.00013558782,0.14363569,0.00005484817,0.00003073171,0.000036061254,0.000011316987,0.000018987404,0.000016676502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989751,0.000112352114,0.00023425526,0.00011897518,0.0002499077,0.00030939656],"domain_scores_gemma":[0.99917066,0.00017913041,0.000008415477,0.00018946934,0.0003361105,0.00011620739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001006236,0.00008611563,0.00013438663,0.00011650598,0.0002255634,0.000101416605,0.0001059553,0.00007022643,0.00005051139],"category_scores_gemma":[0.00032062788,0.00008091242,0.000028400293,0.0003929953,0.000123126,0.00013625206,0.000025285994,0.00023583941,0.00001535855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005586074,0.00006284684,0.0000120693885,0.000057017634,0.0000140778375,0.0000017930056,0.00023780193,0.9895903,0.00034519215,0.0076601924,0.0003947604,0.0016183886],"study_design_scores_gemma":[0.00036846293,0.00009665495,0.000084753956,0.00009887445,0.0000032928574,0.0000010996647,0.00005348588,0.9905731,0.0042900904,0.0041548563,0.00017469392,0.00010065613],"about_ca_topic_score_codex":0.00005382003,"about_ca_topic_score_gemma":0.000022919805,"teacher_disagreement_score":0.7934555,"about_ca_system_score_codex":0.000017004448,"about_ca_system_score_gemma":0.000058913087,"threshold_uncertainty_score":0.3299513},"labels":[],"label_agreement":null},{"id":"W2089805118","doi":"10.1007/s10479-014-1690-7","title":"Security economics: an adversarial risk analysis approach to airport protection","year":2014,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Deep River Science Academy","funders":"","keywords":"Terrorism; Airport security; Adversarial system; Computer security; Control (management); Plan (archaeology); Risk analysis (engineering); Computer science; Port (circuit theory); Operations research; Business; Political science; Law; Engineering","score_opus":0.07864628547285307,"score_gpt":0.3611004496822594,"score_spread":0.28245416420940633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089805118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8705866,0.000009759909,0.124250874,0.0001528115,0.000032435702,0.00032674486,0.000032798627,0.00004138332,0.004566593],"genre_scores_gemma":[0.99795866,0.000060086426,0.0016125543,0.000019598701,0.00016299344,0.0000867857,0.000051742394,0.000011007984,0.00003655869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984844,0.00034438766,0.00031731042,0.00028999863,0.00026841607,0.0002955058],"domain_scores_gemma":[0.9987369,0.000040593008,0.000015807693,0.00055815204,0.0004912588,0.00015727319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025545333,0.00010300398,0.0002583926,0.0008354962,0.0003119168,0.00010237119,0.00026427105,0.00009949554,0.00009282449],"category_scores_gemma":[0.00032231477,0.00009975461,0.0001440468,0.0014902191,0.00008295045,0.00038096725,0.000038974707,0.0003447622,0.000024882873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000139022795,0.00005788109,0.0008886015,0.000015343572,0.00023124726,5.2285696e-8,0.00054795423,0.99248266,0.0002722951,0.0012707314,0.00014614534,0.004073189],"study_design_scores_gemma":[0.00007465429,0.00011271085,0.0064014103,0.0000020053328,0.000052902837,3.7014752e-7,0.00026433636,0.98651797,0.004570607,0.00075057644,0.0011388849,0.00011358367],"about_ca_topic_score_codex":0.0016657523,"about_ca_topic_score_gemma":0.0017103446,"teacher_disagreement_score":0.12737207,"about_ca_system_score_codex":0.000036698915,"about_ca_system_score_gemma":0.000048708032,"threshold_uncertainty_score":0.40678748},"labels":[],"label_agreement":null},{"id":"W2090452502","doi":"10.1007/s10479-011-1032-y","title":"On the decomposition of the absolute ruin probability in a perturbed compound Poisson surplus process with debit interest","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ruin theory; Mathematics; First-hitting-time model; Absolute (philosophy); Poisson distribution; Mathematical economics; Statistics; Risk model","score_opus":0.7238256754699147,"score_gpt":0.5407272151687531,"score_spread":0.18309846030116161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090452502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865908,0.000043495802,0.00024436793,0.0097780675,0.000026786745,0.0010493507,0.000023412964,0.000005228844,0.0022384701],"genre_scores_gemma":[0.99923676,0.000011954328,0.0003431859,0.000111969304,0.0000073884744,0.00009647578,0.0000015596493,0.000006086638,0.00018462517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99577326,0.0015565251,0.00063834165,0.00037358134,0.0013745073,0.00028381596],"domain_scores_gemma":[0.99450123,0.0020037927,0.000087266955,0.0010393349,0.0023077268,0.00006064277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009753973,0.00010389432,0.0002325882,0.0002507629,0.00038250766,0.00011240599,0.001338493,0.00006970655,0.0001871134],"category_scores_gemma":[0.004432167,0.000044851095,0.00008271735,0.0014649003,0.00091592025,0.00034548546,0.0001923347,0.00042732593,0.000019607212],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009000729,0.012412138,0.060769837,0.00030749076,0.00022797905,0.00001938032,0.09242135,0.10387574,0.014196428,0.69071907,0.006629048,0.009420829],"study_design_scores_gemma":[0.0007212199,0.0016342087,0.20710911,0.00044308143,0.0000070119204,0.000011660993,0.0027108097,0.07556196,0.06423693,0.6472373,0.00009098756,0.0002357411],"about_ca_topic_score_codex":0.0014683474,"about_ca_topic_score_gemma":0.013967122,"teacher_disagreement_score":0.14633927,"about_ca_system_score_codex":0.00003172053,"about_ca_system_score_gemma":0.00037732374,"threshold_uncertainty_score":0.7793982},"labels":[],"label_agreement":null},{"id":"W2092181454","doi":"10.1007/s10479-006-0136-2","title":"Credit risk optimization using factor models","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Portfolio optimization; Portfolio; Computer science; Mathematical optimization; Theory of computation; Credit risk; Modern portfolio theory; Curse of dimensionality; Optimization problem; Mathematics; Economics; Actuarial science; Machine learning; Algorithm; Finance","score_opus":0.6231119004332903,"score_gpt":0.5580227427264584,"score_spread":0.06508915770683199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092181454","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34338316,0.0002782936,0.6468681,0.00066728913,0.0001023363,0.00033161495,0.0001390108,0.000021317745,0.008208832],"genre_scores_gemma":[0.9647579,0.0010037757,0.031481057,0.000023407209,0.00019117538,0.000012452367,0.000046046527,0.000015056555,0.0024690968],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99576676,0.00068444054,0.00075299386,0.00036511038,0.002098317,0.00033238364],"domain_scores_gemma":[0.9943275,0.00048930326,0.000103950486,0.0005868778,0.0044006873,0.0000916714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003932675,0.00010147837,0.00020303625,0.000935746,0.0006656357,0.00048071487,0.0004946247,0.0001048915,0.0006491089],"category_scores_gemma":[0.0018625164,0.000081125814,0.00009220046,0.0020753234,0.00017140748,0.0013214002,0.000106194246,0.00020812683,0.0000635437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013514146,0.00007547537,0.0018793383,7.493713e-7,0.000005891994,9.160877e-7,0.0001516179,0.9857884,0.00019507576,0.0029377646,0.0067771967,0.0021740643],"study_design_scores_gemma":[0.00011521639,0.000051940304,0.0012671482,0.000006197686,0.00000261096,0.0000013861533,0.0001444121,0.98660177,0.0021011408,0.0084406845,0.0011821875,0.00008528976],"about_ca_topic_score_codex":0.0025389346,"about_ca_topic_score_gemma":0.00019544979,"teacher_disagreement_score":0.6213748,"about_ca_system_score_codex":0.000018964196,"about_ca_system_score_gemma":0.00026138063,"threshold_uncertainty_score":0.71072876},"labels":[],"label_agreement":null},{"id":"W2098518324","doi":"10.1007/s10479-008-0332-3","title":"A Bayesian approach for the alignment of high-resolution NMR spectra","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Image warping; Bayesian probability; Spectral line; Theory of computation; Computer science; Dynamic time warping; Nuclear magnetic resonance; Amplitude; Biological system; NMR spectra database; Resolution (logic); Algorithm; Artificial intelligence; Pattern recognition (psychology); Computational physics; Physics; Optics","score_opus":0.13986370215676733,"score_gpt":0.38872399052754253,"score_spread":0.2488602883707752,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098518324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79158777,0.007842975,0.1900617,0.004998258,0.000067917346,0.0015092825,0.00018904552,0.0000054658844,0.0037375593],"genre_scores_gemma":[0.9854092,0.0047516157,0.008443215,0.000042817643,0.00012081442,0.00013560138,0.00006721699,0.000008197087,0.0010213319],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908894,0.0000820069,0.00019668811,0.0001799594,0.00023810488,0.0002143119],"domain_scores_gemma":[0.99908376,0.00004073435,0.000024259283,0.00032012927,0.0004991275,0.00003201624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007674877,0.0000653026,0.00012930708,0.00008330319,0.00032760602,0.000009195168,0.00019670889,0.000048699312,0.000016064774],"category_scores_gemma":[0.00023050976,0.000046127203,0.00008183615,0.00019069754,0.00024739947,0.0000035150636,0.00009148529,0.0000649377,7.451339e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025964263,0.0006205017,0.0003488576,0.00006319401,0.00049191253,6.287133e-7,0.0003605244,0.015498501,0.89056313,0.05083365,0.039876707,0.0010827743],"study_design_scores_gemma":[0.0005849361,0.0010903584,0.004952571,0.000006336342,0.00001664707,0.000007453159,0.0005132503,0.010748964,0.9632137,0.0004399104,0.018287878,0.00013798523],"about_ca_topic_score_codex":0.00021121786,"about_ca_topic_score_gemma":0.000046645288,"teacher_disagreement_score":0.1938214,"about_ca_system_score_codex":0.0000044698113,"about_ca_system_score_gemma":0.000093465555,"threshold_uncertainty_score":0.2519714},"labels":[],"label_agreement":null},{"id":"W2099280887","doi":"10.1007/s10479-012-1100-y","title":"A MAP-modulated fluid flow model with multiple vacations","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Ministry of Education, Science and Technology; National Research Foundation of Korea; University of Seoul; National Research Foundation","keywords":"Markovian arrival process; Fluid dynamics; Fluid queue; Flow (mathematics); Laplace transform; Mathematics; Markov process; Computer science; Mathematical optimization; Applied mathematics; Queueing theory; Mathematical analysis; Geometry; Mechanics; Physics; Statistics","score_opus":0.1644797688412679,"score_gpt":0.3985013973777777,"score_spread":0.2340216285365098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099280887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9027719,0.00034971768,0.078496076,0.009000077,0.00006302779,0.00072277227,0.0000283741,0.00014265957,0.008425407],"genre_scores_gemma":[0.99162865,0.000017188286,0.005666158,0.0003141556,0.00027061894,0.00008754895,0.00010733878,0.000025818557,0.001882528],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99862057,0.000049705963,0.00023619656,0.00019253927,0.00045824013,0.00044277392],"domain_scores_gemma":[0.997785,0.00009748344,0.00003505611,0.00045191403,0.0015991504,0.000031441294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013654997,0.00010872283,0.00015543071,0.00057482236,0.0005544777,0.00013722121,0.00026853994,0.000048676226,0.00031880545],"category_scores_gemma":[0.0005190751,0.000091130416,0.000056735797,0.0010727954,0.00013993433,0.0020961002,0.00013838813,0.00018573913,0.00044026147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060375434,0.00029524087,0.0018899406,0.000042526226,0.00007266878,7.3356506e-7,0.00019103757,0.94767463,0.005162432,0.03989795,0.0039839833,0.0007285003],"study_design_scores_gemma":[0.00019178922,0.00001117713,0.00064230955,0.000026312067,0.000018604143,4.6113948e-7,0.00020873343,0.9909533,0.0016948999,0.0020668863,0.004058556,0.0001269282],"about_ca_topic_score_codex":0.00030543737,"about_ca_topic_score_gemma":0.0002509048,"teacher_disagreement_score":0.08885676,"about_ca_system_score_codex":0.000014319682,"about_ca_system_score_gemma":0.00004914989,"threshold_uncertainty_score":0.5658817},"labels":[],"label_agreement":null},{"id":"W2107650959","doi":"10.1007/s10479-006-0026-7","title":"DEA models for supply chain efficiency evaluation","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":462,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Supply chain; Data envelopment analysis; Context (archaeology); Computer science; Supply chain management; Measure (data warehouse); Theory of computation; Service management; Chain (unit); Operations research; Microeconomics; Business; Mathematical optimization; Economics; Marketing; Mathematics; Data mining; Algorithm","score_opus":0.5687705235917271,"score_gpt":0.5828705551331151,"score_spread":0.014100031541388058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107650959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76062983,0.0010683287,0.20857301,0.012613098,0.00011750385,0.0016229843,0.00010407463,0.000027560549,0.01524359],"genre_scores_gemma":[0.99303275,0.000019418352,0.002907983,0.00007991278,0.000108905384,0.00018507826,0.000050604845,0.000012229781,0.0036031012],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99184585,0.0010965399,0.0009910897,0.00060909736,0.0049238196,0.00053360267],"domain_scores_gemma":[0.9853854,0.0022450755,0.00008188979,0.0009204244,0.011284557,0.00008265681],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.037801385,0.00011625554,0.00027724166,0.0014977749,0.0008566994,0.0004683611,0.0010279318,0.00009144752,0.0003579922],"category_scores_gemma":[0.009814096,0.000091616304,0.00020088855,0.0034580159,0.00033353755,0.0006188379,0.00011838693,0.00016775398,0.0001336142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019852252,0.00029028315,0.00018859953,0.0000035671787,0.000008578011,4.0350304e-7,0.0002715115,0.90358204,0.0035344455,0.064111196,0.01935673,0.0086328285],"study_design_scores_gemma":[0.00022143903,0.00013881143,0.0008606012,0.000011602727,0.000007732077,7.993711e-7,0.00027576307,0.90996116,0.008777705,0.078105465,0.001545339,0.00009355793],"about_ca_topic_score_codex":0.0009025089,"about_ca_topic_score_gemma":0.00094299763,"teacher_disagreement_score":0.23240292,"about_ca_system_score_codex":0.000040489947,"about_ca_system_score_gemma":0.00064672565,"threshold_uncertainty_score":0.99852663},"labels":[],"label_agreement":null},{"id":"W2107724521","doi":"10.1007/s10479-006-0023-x","title":"The efficiency of joint decision making in buyer-supplier relationships","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Benchmarking; Data envelopment analysis; Supply chain; Supply chain management; Computer science; Joint (building); Product (mathematics); Business; Operations research; Supplier relationship management; Efficiency; Microeconomics; Industrial organization; Marketing; Economics; Mathematics; Mathematical optimization; Statistics","score_opus":0.24606156247508776,"score_gpt":0.41685051042443766,"score_spread":0.1707889479493499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107724521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94327766,0.00031080577,0.0043440037,0.010111417,0.00007152626,0.0006020589,0.000004003589,0.000014122066,0.04126441],"genre_scores_gemma":[0.9987896,0.00004153198,0.0003547898,0.000087786655,0.0001161971,0.0000384269,0.000012093994,0.000008257664,0.0005512886],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9981773,0.00010999899,0.00056565896,0.00017142344,0.0006868608,0.00028877455],"domain_scores_gemma":[0.99850214,0.00043841277,0.000054123273,0.0003423157,0.0006573772,0.000005662307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006010426,0.00007099983,0.00012782204,0.00060000014,0.00063950516,0.00023184417,0.00031816674,0.000044434455,0.00014332755],"category_scores_gemma":[0.0010261408,0.000053274816,0.0000560855,0.0012973831,0.00017834936,0.00048589212,0.00023675917,0.00024947408,0.0000920164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006671894,0.00040077476,0.010382744,0.00010781539,0.000011484279,0.0000035728515,0.00017901137,0.04261373,0.0007168684,0.91656965,0.021860898,0.007086717],"study_design_scores_gemma":[0.0011057456,0.00008700955,0.48086601,0.0006120562,0.00001701449,9.93198e-7,0.004631254,0.18803608,0.0024939019,0.20639212,0.115307644,0.0004501727],"about_ca_topic_score_codex":0.001622423,"about_ca_topic_score_gemma":0.0038461618,"teacher_disagreement_score":0.71017754,"about_ca_system_score_codex":0.000013564912,"about_ca_system_score_gemma":0.000039387767,"threshold_uncertainty_score":0.49186215},"labels":[],"label_agreement":null},{"id":"W2109343421","doi":"10.1007/s10479-012-1298-8","title":"An integrated optimization model for fuel management and fire suppression preparedness planning","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Fogarty International Center; Bushfire Cooperative Research Centre","keywords":"Preparedness; Theory of computation; Integer programming; Computer science; Operations research; Emergency management; Engineering; Economics; Algorithm; Management","score_opus":0.14333808738921683,"score_gpt":0.4245741071868484,"score_spread":0.2812360197976316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109343421","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33067408,0.00025198565,0.6671296,0.00024682743,0.000028083787,0.00077888725,0.00003715573,0.0000711988,0.0007822046],"genre_scores_gemma":[0.96474,0.00034488004,0.03363736,0.000024738747,0.000010747543,0.00029216753,0.00022321679,0.000017669334,0.0007092667],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999341,0.000036452748,0.0001660684,0.00012361935,0.00016962884,0.0001632276],"domain_scores_gemma":[0.99919033,0.000029258526,0.000006472597,0.00016924721,0.0005379716,0.0000667243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028176414,0.00006548547,0.00007559145,0.00014315106,0.00013819229,0.00013145874,0.00010678266,0.000051538453,0.000052129006],"category_scores_gemma":[0.000033485867,0.000060627743,0.000014505636,0.00017184713,0.00003336492,0.0004667529,0.000025738052,0.000079525555,0.0000027960962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007711159,0.00003007546,0.00003101193,0.00010161421,0.000014097768,1.3994692e-7,0.0011570822,0.9924835,0.00041872333,0.0005202894,0.0026908515,0.002544889],"study_design_scores_gemma":[0.00015055045,0.000041193493,0.00017972462,0.000041535837,0.0000022903628,2.956528e-7,0.00091921486,0.9980751,0.00024963656,0.00018447055,0.00009094534,0.00006501683],"about_ca_topic_score_codex":0.000028812727,"about_ca_topic_score_gemma":0.000012975541,"teacher_disagreement_score":0.63406587,"about_ca_system_score_codex":0.000013027041,"about_ca_system_score_gemma":0.000020327347,"threshold_uncertainty_score":0.24723276},"labels":[],"label_agreement":null},{"id":"W2112502728","doi":"10.1007/s10479-015-1907-4","title":"Operations Research challenges in forestry: 33 open problems","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":130,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Dalhousie University; Université Laval","funders":"","keywords":"Forestry; Community forestry; Forest management; Environmental planning; Computer science; Management science; Operations research; Business; Environmental resource management; Engineering; Geography; Economics","score_opus":0.7507399674572494,"score_gpt":0.5250244848031548,"score_spread":0.22571548265409458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112502728","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51456046,0.008657043,0.0011242243,0.034647714,0.00036114376,0.006495492,0.000102139005,0.0002491791,0.43380263],"genre_scores_gemma":[0.9912782,0.0045253322,0.00083145394,0.00002814506,0.00005077072,0.00064056105,0.00006498025,0.000032964977,0.0025476164],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975223,0.00040294224,0.00038628365,0.00027936132,0.00085984444,0.00054926955],"domain_scores_gemma":[0.9977461,0.0000701558,0.0000047711537,0.0005507462,0.0014283644,0.00019985947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005094521,0.000111666996,0.00018288077,0.00096802815,0.00020666272,0.0003376543,0.0008146965,0.000095962845,0.00011433477],"category_scores_gemma":[0.00053386495,0.000108148284,0.000026177482,0.0014779619,0.00018244375,0.00064932,0.0004835893,0.00038285163,0.00018242166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020314965,0.00037613965,0.00044511852,0.00016384314,0.000046773042,0.000010741055,0.004462575,0.7310422,0.00065162237,0.20980129,0.04773154,0.0052478034],"study_design_scores_gemma":[0.0019158617,0.0008651538,0.0069297603,0.000407421,0.000004454248,0.0000058287796,0.016222745,0.61894095,0.008722031,0.0066907173,0.33873683,0.00055826484],"about_ca_topic_score_codex":0.0010584514,"about_ca_topic_score_gemma":0.028838215,"teacher_disagreement_score":0.47671774,"about_ca_system_score_codex":0.000076233264,"about_ca_system_score_gemma":0.00023700013,"threshold_uncertainty_score":0.98888296},"labels":[],"label_agreement":null},{"id":"W2120018445","doi":"10.1007/s10479-005-3455-9","title":"On Compact Formulations for Integer Programs Solved by Column Generation","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; Kronos (Canada); HEC Montréal; St Mary's Hospital Centre","funders":"","keywords":"Column generation; Theory of computation; Diagonal; Mathematical optimization; Mathematics; Integer programming; Integer (computer science); Compatibility (geochemistry); Branching (polymer chemistry); Computer science; Algorithm","score_opus":0.3155450072934694,"score_gpt":0.48209199191541985,"score_spread":0.16654698462195044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120018445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3005428,0.00020641547,0.6891418,0.0045430083,0.00010025306,0.0017970828,0.000119873184,0.00020887538,0.003339913],"genre_scores_gemma":[0.9442317,0.000053183463,0.053871945,0.00008033348,0.0001464968,0.00017864615,0.00036496783,0.000036900925,0.0010358435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987177,0.00012972445,0.00033597002,0.000161854,0.0003301003,0.0003245963],"domain_scores_gemma":[0.99851805,0.00022741902,0.000014538415,0.00025649296,0.0008955899,0.00008792398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012935287,0.000099837845,0.00014255877,0.0002294291,0.00031993893,0.0001440377,0.00015374314,0.00008493963,0.00009850917],"category_scores_gemma":[0.00041355068,0.00010279888,0.0000623434,0.00044115266,0.000057830886,0.00029376833,0.000013899184,0.00019418396,0.000027792026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009025332,0.000120436656,0.000034604378,0.000016187232,0.000028409979,4.6223775e-8,0.00024741114,0.91048944,0.016207546,0.005255244,0.05411803,0.013473638],"study_design_scores_gemma":[0.00024061007,0.00016061738,0.000051664276,0.000018103668,0.000002684963,3.7346823e-7,0.00003163576,0.9363852,0.05362787,0.00009508899,0.009289504,0.00009661381],"about_ca_topic_score_codex":0.000030293224,"about_ca_topic_score_gemma":0.00012569637,"teacher_disagreement_score":0.6436889,"about_ca_system_score_codex":0.00005180259,"about_ca_system_score_gemma":0.000054876433,"threshold_uncertainty_score":0.41920164},"labels":[],"label_agreement":null},{"id":"W2124659975","doi":"10.1007/s10479-007-0176-2","title":"An overview of bilevel optimization","year":2007,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":1430,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"","keywords":"Bilevel optimization; Theory of computation; Mathematical optimization; Simple (philosophy); Computer science; Connection (principal bundle); Focus (optics); Mathematical economics; Optimization problem; Mathematics; Algorithm","score_opus":0.4883983889418265,"score_gpt":0.5434584453478315,"score_spread":0.055060056406004976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124659975","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002560046,0.00022528147,0.9928588,0.0024750687,0.00002429137,0.00011925361,0.000007702633,0.000016705195,0.0017128197],"genre_scores_gemma":[0.7460229,0.0005586738,0.25293645,0.00015914626,0.000028714852,0.0000058686537,0.000033421886,0.0000049150435,0.000249912],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984534,0.00018050552,0.00036938683,0.00018762898,0.00062915,0.00017993744],"domain_scores_gemma":[0.99667394,0.00012892763,0.000039562598,0.0004434092,0.0026258288,0.00008834497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027461175,0.0000534294,0.00012080224,0.0005853513,0.00016192821,0.000078233286,0.00054899475,0.000044450782,0.00018333456],"category_scores_gemma":[0.0002446724,0.000048491762,0.00005165728,0.0019697275,0.00006233132,0.00077130576,0.00008446159,0.00007972075,0.000010906192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040321943,0.0001965255,0.0001558569,0.000009480978,0.00001657831,4.361599e-7,0.00026364514,0.6956886,0.0007331767,0.2987503,0.00020944349,0.003971916],"study_design_scores_gemma":[0.000089697176,0.000111324945,0.0030927868,0.000012302784,0.0000018646513,6.9261245e-7,0.000045124914,0.9853575,0.010311236,0.0006793385,0.00024149923,0.00005660742],"about_ca_topic_score_codex":0.00018810411,"about_ca_topic_score_gemma":0.00006541425,"teacher_disagreement_score":0.74346286,"about_ca_system_score_codex":0.000008941021,"about_ca_system_score_gemma":0.000169296,"threshold_uncertainty_score":0.20073849},"labels":[],"label_agreement":null},{"id":"W2125597755","doi":"10.1007/s10479-009-0669-2","title":"Applications and extensions of cost curves to marine container inspection","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bentley (Canada); Government of Canada","funders":"","keywords":"Container (type theory); Theory of computation; Computer science; Marine engineering; Reliability engineering; Operations research; Engineering drawing; Mathematics; Mechanical engineering; Engineering; Algorithm","score_opus":0.1612641464641404,"score_gpt":0.43289161872632004,"score_spread":0.27162747226217965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125597755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9309621,0.0018112926,0.03409859,0.0061836727,0.00017765457,0.0042557493,0.00009593203,0.00024095124,0.022174088],"genre_scores_gemma":[0.99863523,0.0006699888,0.00020137454,0.00006410746,0.00006822825,0.00010431053,0.000010636754,0.000006825963,0.00023931456],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992209,0.000056735393,0.00025763866,0.000106167776,0.00022463009,0.00013389462],"domain_scores_gemma":[0.9989023,0.000059456583,0.000009867055,0.00019720191,0.0007524749,0.00007869738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006026039,0.000055931065,0.00013750717,0.00032309696,0.00014175239,0.00002236443,0.00005870667,0.000052514566,0.00003585029],"category_scores_gemma":[0.00016192035,0.000051892865,0.000025972422,0.0006693823,0.000035825546,0.00010544862,0.000024551138,0.00013964795,0.000013694354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012108697,0.00040267306,0.0006460486,0.00033326293,0.00010352469,0.0000029818373,0.0007662978,0.043335408,0.44530007,0.029617729,0.08907844,0.39029247],"study_design_scores_gemma":[0.0020761169,0.003809104,0.119927935,0.0014034377,0.000042070267,0.000069701884,0.0019840512,0.0814502,0.561611,0.0017420037,0.22490665,0.0009777487],"about_ca_topic_score_codex":0.00025241714,"about_ca_topic_score_gemma":0.00011710727,"teacher_disagreement_score":0.38931474,"about_ca_system_score_codex":0.000011911262,"about_ca_system_score_gemma":0.000025012438,"threshold_uncertainty_score":0.21161295},"labels":[],"label_agreement":null},{"id":"W2128628754","doi":"10.1007/s10479-011-1045-6","title":"Multiobjective scatter search for a commercial territory design problem","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; HEC Montréal","funders":"Instituto Tecnológico y de Estudios Superiores de Monterrey; Universidad de León; Ministerio de Ciencia e Innovación; Universidad Autónoma de Nuevo León; Consejo Nacional de Ciencia y Tecnología","keywords":"Tabu search; Heuristics; Mathematical optimization; Metaheuristic; Sorting; Computer science; Local search (optimization); Theory of computation; Genetic algorithm; Multi-objective optimization; Heuristic; Mathematics; Algorithm","score_opus":0.3634122278103288,"score_gpt":0.4893909142891731,"score_spread":0.1259786864788443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128628754","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017762565,0.00014347398,0.9925055,0.0029308652,0.00012104125,0.0017038016,0.000024929554,0.000049813665,0.0007443282],"genre_scores_gemma":[0.3377055,0.000035387908,0.6604506,0.00023350374,0.0002100608,0.00063788303,0.000012993767,0.000021824886,0.0006922966],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99726915,0.0006932766,0.00031303646,0.0003539177,0.00063335197,0.00073727267],"domain_scores_gemma":[0.995887,0.0006539039,0.000029151604,0.00051129266,0.0027190812,0.0001995781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002913869,0.00013426767,0.00018889691,0.00051179883,0.0006430519,0.00015441763,0.00073128147,0.00008472333,0.00003054716],"category_scores_gemma":[0.00030688217,0.00012781247,0.00007865719,0.0007619591,0.00024149292,0.0017518576,0.00030398986,0.0002984208,0.000057983198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003472897,0.0048950333,0.0028542865,0.00019822204,0.0003416878,0.0000056159133,0.045128748,0.55586576,0.025331173,0.106331095,0.023032323,0.23566873],"study_design_scores_gemma":[0.0014091375,0.000763484,0.0067473426,0.000062197614,0.000005271166,0.000012225444,0.00060265773,0.751836,0.23254159,0.0007132791,0.0048433226,0.000463477],"about_ca_topic_score_codex":0.00012799814,"about_ca_topic_score_gemma":0.000021159989,"teacher_disagreement_score":0.33592924,"about_ca_system_score_codex":0.000073037576,"about_ca_system_score_gemma":0.00032010832,"threshold_uncertainty_score":0.5212041},"labels":[],"label_agreement":null},{"id":"W2130360396","doi":"10.1007/s10479-013-1370-z","title":"A make-to-stock mountain-type inventory model","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Queue; Buffer (optical fiber); Fluid queue; Theory of computation; Markov chain; Computer science; Markov process; Content (measure theory); State (computer science); Mathematical optimization; Applied mathematics; Mathematics; Algorithm; Statistics; Mathematical analysis; Computer network; Telecommunications","score_opus":0.2188306103057322,"score_gpt":0.4250922636527753,"score_spread":0.2062616533470431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130360396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9670963,0.00008531821,0.002998509,0.009584195,0.000042972177,0.00064372766,0.0000029548967,0.000061636834,0.019484388],"genre_scores_gemma":[0.9878729,0.000016604077,0.0010430159,0.0021985823,0.00022766337,0.000117422496,0.000022035758,0.000026071508,0.008475718],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984873,0.000049389062,0.00027961898,0.0002637391,0.0005248678,0.00039510397],"domain_scores_gemma":[0.9967345,0.00004691959,0.000030707823,0.0004773905,0.0026743526,0.00003610004],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012154909,0.000108144406,0.00017008804,0.00083722867,0.00038272748,0.0002872984,0.00043260687,0.000050927225,0.0009205675],"category_scores_gemma":[0.0010170707,0.000101677375,0.00006449616,0.0016195644,0.000114737384,0.0011366302,0.00031951576,0.00021211825,0.0023411873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000583008,0.00022950569,0.0008706849,0.00008149463,0.00007743791,0.0000029716437,0.00023431743,0.7065296,0.014649513,0.22649069,0.04580051,0.0049749347],"study_design_scores_gemma":[0.0001262944,0.000029995053,0.00031474937,0.00003545804,0.000009724841,2.993478e-7,0.0003289823,0.9512517,0.00092663936,0.034813587,0.011984256,0.00017831348],"about_ca_topic_score_codex":0.0012696699,"about_ca_topic_score_gemma":0.0002584878,"teacher_disagreement_score":0.24472207,"about_ca_system_score_codex":0.000021572443,"about_ca_system_score_gemma":0.00006983155,"threshold_uncertainty_score":0.9999927},"labels":[],"label_agreement":null},{"id":"W2132083787","doi":"10.1007/s10479-005-5724-z","title":"A Tutorial on the Cross-Entropy Method","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":3031,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Cross-entropy method; Theory of computation; Computer science; Cross entropy; Combinatorial optimization; Entropy (arrow of time); Mathematical optimization; Theoretical computer science; Algorithm; Artificial intelligence; Principle of maximum entropy; Mathematics; Quadratic assignment problem","score_opus":0.7469201458343675,"score_gpt":0.7038611654305066,"score_spread":0.043058980403860914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132083787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57155424,0.00013379389,0.08853139,0.26313028,0.00021849055,0.0019823012,0.00012861163,0.000104273415,0.074216634],"genre_scores_gemma":[0.97966313,0.000027696451,0.007908563,0.0007017552,0.0004675444,0.00014527961,0.0000037939053,0.0000071245513,0.011075108],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99648035,0.00065829855,0.0005007505,0.00028765583,0.0018403969,0.00023255579],"domain_scores_gemma":[0.99274516,0.0035847183,0.00003776972,0.00091587374,0.0026426737,0.0000738311],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0109282,0.000065388194,0.00012060204,0.0003047116,0.0007632008,0.0005526304,0.00091514294,0.00005797087,0.0028312602],"category_scores_gemma":[0.0063959584,0.000037315975,0.00009733613,0.0013289624,0.00021325694,0.0002550446,0.00012836697,0.00026023993,0.00088580826],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033298977,0.00016512256,0.0001719366,5.2233673e-7,0.000008950096,2.2083967e-7,0.00034433047,0.028414195,0.0032202338,0.7754803,0.14408864,0.048072275],"study_design_scores_gemma":[0.00017688618,0.00016115086,0.002531968,0.000007048666,0.000001262759,0.0000011034616,0.0002320933,0.078536995,0.13358814,0.052632134,0.7320391,0.00009210775],"about_ca_topic_score_codex":0.00009192531,"about_ca_topic_score_gemma":0.000035992492,"teacher_disagreement_score":0.7228481,"about_ca_system_score_codex":0.000014986126,"about_ca_system_score_gemma":0.00013244255,"threshold_uncertainty_score":0.9998921},"labels":[],"label_agreement":null},{"id":"W2132931213","doi":"10.1007/s10479-013-1427-z","title":"Dynamic bidding strategies in search-based advertising","year":2013,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Bidding; Computer science; Search advertising; Dynamic programming; Revenue; Budget constraint; Display advertising; Theory of computation; Real-time bidding; Mathematical optimization; Position (finance); Online advertising; Dynamic pricing; Stochastic programming; Algorithm; Economics; Microeconomics; Mathematics; The Internet","score_opus":0.14514743534404403,"score_gpt":0.41663901693784144,"score_spread":0.2714915815937974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132931213","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98354053,0.00013989353,0.0003007614,0.0034011742,0.000037625738,0.0003848604,0.0000014337252,0.000027685457,0.012166038],"genre_scores_gemma":[0.99912614,0.000026346504,0.00030785106,0.00017432321,0.00003811836,0.000055896173,0.00001953503,0.000015834503,0.00023594557],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857914,0.00006983708,0.00028475167,0.00020483191,0.00044608826,0.00041535535],"domain_scores_gemma":[0.9987467,0.00012914487,0.000017843642,0.00023837549,0.00085150456,0.000016431024],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014129996,0.00009203121,0.00013873582,0.0011222315,0.00026986643,0.00074516947,0.00025796093,0.000047222915,0.0012591083],"category_scores_gemma":[0.00021423193,0.0000880876,0.00004559585,0.0012742667,0.00013186739,0.0019330786,0.00013599846,0.0002856632,0.00022937279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018132637,0.0012894913,0.23834851,0.0014030386,0.0000800973,0.00007319133,0.0012144515,0.13829553,0.17064948,0.048481524,0.005998245,0.3939851],"study_design_scores_gemma":[0.00047650206,0.000027009793,0.39730364,0.00028864143,0.000006213594,6.5700664e-7,0.0030617337,0.5946782,0.0013234611,0.0012928639,0.0012717207,0.0002693236],"about_ca_topic_score_codex":0.015190743,"about_ca_topic_score_gemma":0.003415658,"teacher_disagreement_score":0.45638272,"about_ca_system_score_codex":0.000015937687,"about_ca_system_score_gemma":0.00013960482,"threshold_uncertainty_score":0.9996539},"labels":[],"label_agreement":null},{"id":"W2134125472","doi":"10.1007/s10479-015-1805-9","title":"Multi-period hub network design problems with modular capacities","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Integer programming; Theory of computation; Modular design; Mathematical optimization; Set (abstract data type); Integer (computer science); Computer science; Relevance (law); Linear programming; Measure (data warehouse); Network planning and design; Facility location problem; Mathematics; Algorithm; Data mining; Telecommunications","score_opus":0.42360263638416223,"score_gpt":0.4270872876495254,"score_spread":0.003484651265363181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134125472","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050369635,0.00081974815,0.94641274,0.0005478611,0.0000618069,0.00059420936,0.000008949533,0.00015416513,0.0010308686],"genre_scores_gemma":[0.47294486,0.00009547545,0.5260765,0.000018165481,0.00007373457,0.00010805857,0.000010620495,0.000039844803,0.0006327549],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998203,0.00047643733,0.00025149956,0.00016174573,0.00048700054,0.00042032683],"domain_scores_gemma":[0.9981002,0.0000960548,0.000011125467,0.0003346659,0.0013061006,0.00015184839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030305847,0.000112999674,0.00017397167,0.00018537372,0.00019776706,0.000115320305,0.00021680535,0.00007442728,0.000033587643],"category_scores_gemma":[0.00035315566,0.0001001345,0.000024131044,0.0007500416,0.00020739285,0.00028184598,0.000039585873,0.00027608094,0.000025542118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009908865,0.000029561434,0.000103452774,0.000027429067,0.000038025937,0.000002496632,0.0021881915,0.99256676,0.0017508942,0.00033685716,0.0025809004,0.00036554737],"study_design_scores_gemma":[0.00027487535,0.00016406178,0.00009300734,0.000056753986,0.0000027676672,0.000005757058,0.0006774158,0.9898185,0.008012553,0.000078406396,0.00069188414,0.00012399103],"about_ca_topic_score_codex":0.00008129709,"about_ca_topic_score_gemma":0.00004301411,"teacher_disagreement_score":0.42257524,"about_ca_system_score_codex":0.000029240664,"about_ca_system_score_gemma":0.00016824932,"threshold_uncertainty_score":0.40833664},"labels":[],"label_agreement":null},{"id":"W2136180438","doi":"10.1007/s10479-011-0967-3","title":"Publicity vs. impact in nonprofit disclosures and donor preferences: a sequential game with one nonprofit organization and N donors","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Nonprofit Sector and Volunteering","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Donation; Publicity; Transparency (behavior); Business; Accountability; Public relations; Openness to experience; Nonprofit organization; Prosocial behavior; Boosting (machine learning); Value (mathematics); Accounting; Marketing; Economics; Political science; Social psychology; Psychology","score_opus":0.3158228932772897,"score_gpt":0.44596906760572774,"score_spread":0.13014617432843806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136180438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99538046,0.00009966974,0.00014795669,0.0006757258,0.000020510453,0.000556116,0.000020871195,0.000020209429,0.0030784719],"genre_scores_gemma":[0.9983648,0.0007176723,0.00042407925,0.000019204199,0.00006441128,0.000039879425,0.000013787149,0.000013783717,0.00034237799],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981827,0.0003674942,0.00023474003,0.00029057986,0.0005044283,0.00042002203],"domain_scores_gemma":[0.9986632,0.000079932484,0.000032361786,0.00016958223,0.00087835867,0.00017656722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017423813,0.00010710549,0.00019514046,0.00035096495,0.00043222128,0.00026518508,0.00020844245,0.00009992619,0.00047790413],"category_scores_gemma":[0.00051784643,0.00008595545,0.00001857324,0.0011435833,0.0006009256,0.0009032739,0.00010823244,0.00024635514,0.000005881485],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013591432,0.00017144051,0.95603853,0.000048960304,0.00004854109,0.0000031513518,0.02828655,0.0000311178,0.002100278,0.012159371,0.00008259849,0.00089353736],"study_design_scores_gemma":[0.00046142278,0.00057324616,0.9852217,0.000096939024,0.0000082420365,0.0000024271037,0.0039073806,0.00029209003,0.008478149,0.0006669076,0.000087341294,0.00020419343],"about_ca_topic_score_codex":0.08492623,"about_ca_topic_score_gemma":0.076619476,"teacher_disagreement_score":0.029183121,"about_ca_system_score_codex":0.00003863661,"about_ca_system_score_gemma":0.00044554664,"threshold_uncertainty_score":0.94022983},"labels":[],"label_agreement":null},{"id":"W2140198391","doi":"10.1007/s10479-009-0532-5","title":"Approximating zero-variance importance sampling in a reliability setting","year":2009,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Estimator; Mathematical optimization; Interpolation (computer graphics); Importance sampling; Applied mathematics; Approximation error; Function (biology); Mathematics; Markov chain; Bounded function; Heuristics; Computer science; Variance (accounting); Reliability (semiconductor); Parameterized complexity; Monte Carlo method; Algorithm; Statistics","score_opus":0.5793130532141241,"score_gpt":0.5796847489334721,"score_spread":0.0003716957193480308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140198391","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94736636,0.0003100367,0.031354647,0.016592802,0.00003133202,0.0005284077,0.000015754871,0.000019663925,0.0037810015],"genre_scores_gemma":[0.96165645,0.00005641781,0.03769691,0.00023387185,0.000033660406,0.000027485185,0.0000037164625,0.000004764216,0.0002867435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99482924,0.00090583984,0.0013276029,0.00063769583,0.0017700074,0.00052964245],"domain_scores_gemma":[0.99488115,0.0018254104,0.000089007546,0.0010464006,0.0020471471,0.00011087041],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03466161,0.00010302242,0.0003094544,0.00044018382,0.00046557677,0.00029571416,0.00087932334,0.000099960875,0.00008493676],"category_scores_gemma":[0.031903487,0.00008038527,0.00008809782,0.0022713079,0.00022457418,0.00090370217,0.00015084249,0.00054725877,0.000041764306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015908483,0.0011463318,0.054328453,0.00005156966,0.000011368299,0.00001200459,0.008563577,0.64013183,0.0130104255,0.1282557,0.0027219418,0.15160768],"study_design_scores_gemma":[0.0002582151,0.00017073844,0.054922696,0.000107492364,8.8832206e-7,0.000003203434,0.000867568,0.35807443,0.0036959962,0.5810833,0.0006379114,0.00017757497],"about_ca_topic_score_codex":0.00022168014,"about_ca_topic_score_gemma":0.0002827682,"teacher_disagreement_score":0.45282757,"about_ca_system_score_codex":0.00003850449,"about_ca_system_score_gemma":0.00034348515,"threshold_uncertainty_score":0.99401903},"labels":[],"label_agreement":null},{"id":"W2142232457","doi":"10.1007/s10479-010-0710-5","title":"Designing the master schedule for demand-adaptive transit systems","year":2010,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; HEC Montréal","funders":"Regione Lombardia; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Reservation; Computer science; Schedule; Operations research; Line (geometry); Theory of computation; Bus rapid transit; Set (abstract data type); Process (computing); Focus (optics); Real-time computing; Transport engineering; Public transport; Computer network; Engineering; Algorithm; Operating system","score_opus":0.2757419418382559,"score_gpt":0.41072793840617094,"score_spread":0.13498599656791505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142232457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5353964,0.00018336318,0.457017,0.0032579848,0.0002498749,0.0014132989,0.00012318473,0.00007816955,0.0022806877],"genre_scores_gemma":[0.99535364,0.00001841791,0.0037496388,0.000031936004,0.00004958935,0.00038387184,0.000025944644,0.0000143494535,0.0003725971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992239,0.00004193816,0.0002347137,0.0000950902,0.00020477716,0.00019957969],"domain_scores_gemma":[0.9986755,0.00017366832,0.00000626824,0.00021482076,0.0008900178,0.000039719234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011222748,0.00006075151,0.00008605974,0.00014015654,0.00027476042,0.0000752496,0.00015518487,0.000058160105,0.00005095958],"category_scores_gemma":[0.00007055358,0.00004696424,0.000041626696,0.00035134287,0.000088022156,0.00016676896,0.000004180626,0.0002814501,0.0000133530475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023782599,0.0000740891,0.00013281751,0.00009762545,0.00010794357,5.1240426e-7,0.002180263,0.55915207,0.3036907,0.12805888,0.005303515,0.0011778148],"study_design_scores_gemma":[0.0007028358,0.0002363787,0.0079131145,0.00007122366,0.000022422339,0.0000046424657,0.004287,0.6936518,0.2710181,0.000494506,0.021302622,0.00029539198],"about_ca_topic_score_codex":0.00006567329,"about_ca_topic_score_gemma":0.00050046056,"teacher_disagreement_score":0.45995724,"about_ca_system_score_codex":0.0000056026424,"about_ca_system_score_gemma":0.0000711075,"threshold_uncertainty_score":0.21132627},"labels":[],"label_agreement":null},{"id":"W2147388035","doi":"10.1007/s10479-005-2452-3","title":"Packing r-Cliques in Weighted Chordal Graphs","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Combinatorics; Chordal graph; Mathematics; Split graph; Theory of computation; Discrete mathematics; Disjoint sets; Interval graph; Clique; Vertex (graph theory); Treewidth; Exponential time hypothesis; Graph; Pathwidth; Algorithm; Line graph","score_opus":0.19093514737532585,"score_gpt":0.48248149731860274,"score_spread":0.2915463499432769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147388035","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9048279,0.0013951026,0.052437622,0.02738131,0.000072805065,0.000859265,0.000011273462,0.00012340237,0.012891342],"genre_scores_gemma":[0.9683897,0.00056530524,0.03014059,0.00014897803,0.00004436585,0.00007497468,0.0000041622134,0.00001107578,0.0006208317],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99699885,0.0007013572,0.0003633742,0.00039325294,0.0008894503,0.000653707],"domain_scores_gemma":[0.9976888,0.00031443883,0.000017967724,0.00074950844,0.0010933395,0.00013597799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003528683,0.00010252219,0.00017237343,0.001355587,0.00027285714,0.00019188615,0.0012992785,0.000067151836,0.00008809167],"category_scores_gemma":[0.00045317263,0.00009531931,0.00006463091,0.0027638737,0.0002747372,0.0013922867,0.00041837315,0.0005371667,0.000088712506],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027822682,0.0003026346,0.0013219087,0.00001371982,0.000016221156,0.000015871767,0.0014203048,0.0020089757,0.009235642,0.91619134,0.0013708594,0.068074696],"study_design_scores_gemma":[0.0011486652,0.0008506656,0.013233086,0.0002159711,0.0000013854824,0.000020289503,0.00043880777,0.36474288,0.31452745,0.28291592,0.021268148,0.00063675735],"about_ca_topic_score_codex":0.00015097609,"about_ca_topic_score_gemma":0.00063017354,"teacher_disagreement_score":0.63327545,"about_ca_system_score_codex":0.000030861946,"about_ca_system_score_gemma":0.0002134237,"threshold_uncertainty_score":0.38870084},"labels":[],"label_agreement":null},{"id":"W2153122315","doi":"10.1007/s10479-012-1148-8","title":"Approximately optimal bidding policies for repeated first-price auctions","year":2012,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Bidding; Common value auction; Theory of computation; Payment; Microeconomics; Bounded rationality; Rationality; Computer science; Real-time bidding; Mathematical optimization; Mathematical economics; Combinatorial auction; Economics; Operations research; Mathematics; Finance; Algorithm","score_opus":0.7247939710833537,"score_gpt":0.613052658155607,"score_spread":0.1117413129277467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153122315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79487526,0.00044995392,0.15642592,0.028748203,0.00029037558,0.0015803726,0.00029845658,0.000105031206,0.017226437],"genre_scores_gemma":[0.98227,0.00006953512,0.0069224657,0.000098013996,0.0002804776,0.00045220638,0.00002411104,0.000014094859,0.0098690875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99730414,0.00030160754,0.00061831967,0.00030048852,0.0009317815,0.00054367824],"domain_scores_gemma":[0.9944741,0.0017742759,0.00007159878,0.0007046739,0.0027707214,0.00020460055],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008417742,0.00009904232,0.00019304655,0.0007168715,0.0017791173,0.00026163476,0.0006281316,0.00008290378,0.0007677249],"category_scores_gemma":[0.0064469227,0.000079869504,0.00013155132,0.0022311064,0.00036948902,0.00092386594,0.000159414,0.000192486,0.00038534313],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094077564,0.00069297355,0.00085965253,0.00001902043,0.00006541783,2.0282552e-7,0.0052569383,0.048245016,0.007193718,0.8376392,0.093856685,0.0060770838],"study_design_scores_gemma":[0.0006349681,0.00040915393,0.010600489,0.000048031554,0.00002067612,0.000037778755,0.020902488,0.065373756,0.15617986,0.035246484,0.71000654,0.000539809],"about_ca_topic_score_codex":0.00010642961,"about_ca_topic_score_gemma":0.000028999226,"teacher_disagreement_score":0.8023927,"about_ca_system_score_codex":0.000020549081,"about_ca_system_score_gemma":0.00010868017,"threshold_uncertainty_score":0.9995204},"labels":[],"label_agreement":null},{"id":"W2178163879","doi":"10.1007/s10479-015-2008-0","title":"On the use of the $$L_{p}$$ L p distance in reference point-based approaches for multiobjective optimization","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Theory of computation; Multi-objective optimization; Point (geometry); Mathematical optimization; Mathematics; Computer science; Algorithm; Geometry","score_opus":0.6088702347949255,"score_gpt":0.4441123919419863,"score_spread":0.1647578428529392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2178163879","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022457675,0.000027466333,0.9911208,0.0049065812,0.000041136725,0.0012499846,0.000043711607,0.000012941113,0.00035160518],"genre_scores_gemma":[0.7094341,0.000014407052,0.2896981,0.00019566095,0.000010666402,0.000353705,0.0000118306925,0.000011610488,0.00026994527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99795574,0.00061025587,0.00030416204,0.00031142935,0.000580465,0.00023797018],"domain_scores_gemma":[0.9955593,0.0012083579,0.00007056832,0.0007356977,0.0023736202,0.000052453408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014278169,0.00009955615,0.00013918443,0.0002270325,0.00023423391,0.00011067825,0.0007719056,0.000055297452,0.0000041127655],"category_scores_gemma":[0.004922524,0.000062867555,0.000048442438,0.0013898002,0.00028335772,0.0006910191,0.00015580449,0.0002396215,0.0000019547972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043518106,0.0001804194,0.000051815507,0.000005534366,0.000005487668,1.4532314e-7,0.0006670829,0.91617334,0.000025140418,0.08122065,0.00023670263,0.0013901845],"study_design_scores_gemma":[0.0004033731,0.00014501139,0.00033012932,0.000042612544,7.851736e-7,2.4964262e-7,0.00023946005,0.9886501,0.008874851,0.0011042055,0.00014122299,0.00006800978],"about_ca_topic_score_codex":0.00012752734,"about_ca_topic_score_gemma":0.00019757383,"teacher_disagreement_score":0.7071883,"about_ca_system_score_codex":0.00006974694,"about_ca_system_score_gemma":0.00041766622,"threshold_uncertainty_score":0.58930767},"labels":[],"label_agreement":null},{"id":"W2196093576","doi":"10.1007/s10479-015-2075-2","title":"The impact of disruption characteristics on the performance of a server","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Queueing theory; Exponential distribution; Queueing system; Queue; Service (business); Theory of computation; Counterintuitive; Idle; Process (computing); Computer network; Real-time computing; Operations research; Operating system; Statistics; Mathematics; Algorithm","score_opus":0.22508071540636565,"score_gpt":0.4446745214119028,"score_spread":0.21959380600553713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2196093576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963637,0.000029258836,0.000027276155,0.001896859,0.000017306655,0.00015053152,0.0000059936788,0.0000043921705,0.0015046538],"genre_scores_gemma":[0.99929655,0.000071557144,0.000010381058,0.00004040259,0.00010421368,0.000014235234,0.00001179061,0.0000071487193,0.00044375018],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989969,0.00008633779,0.00025413552,0.00008171871,0.00042628238,0.00015462689],"domain_scores_gemma":[0.99742883,0.00022532728,0.000091988804,0.0003811084,0.0018633856,0.000009368546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003187752,0.000059108625,0.00011841112,0.00016000273,0.00026025964,0.00007143832,0.00031490863,0.000022090633,0.00006183054],"category_scores_gemma":[0.0014934143,0.000030401432,0.00007829286,0.0007038439,0.000224464,0.00044921212,0.0001098852,0.00013409441,0.000040336636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018380614,0.0011176434,0.049602274,0.0003109391,0.0006303847,0.0000025094657,0.0015006402,0.32195982,0.019638294,0.57138807,0.0142015405,0.01780984],"study_design_scores_gemma":[0.0006159085,0.00075613987,0.1309186,0.00035827587,0.000056812853,0.0000011265043,0.0029460893,0.83140653,0.018009556,0.0103865685,0.0042272354,0.0003171563],"about_ca_topic_score_codex":0.00037462555,"about_ca_topic_score_gemma":0.000040814,"teacher_disagreement_score":0.5610015,"about_ca_system_score_codex":0.000011917012,"about_ca_system_score_gemma":0.000057700483,"threshold_uncertainty_score":0.20017329},"labels":[],"label_agreement":null},{"id":"W219822362","doi":"10.1023/a:1021388515849","title":"Solvability of Implicit Complementarity Problems","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Theory of computation; Complementarity (molecular biology); Mathematics; Mixed complementarity problem; Complementarity theory; Mathematical economics; Computer science; Applied mathematics; Algorithm; Nonlinear system","score_opus":0.48455297427459304,"score_gpt":0.5179340628099413,"score_spread":0.03338108853534821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W219822362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9502855,0.00019416036,0.0013936564,0.009628918,0.000043001335,0.0006453208,0.00011503313,0.00002999149,0.037664454],"genre_scores_gemma":[0.99764764,0.00026158232,0.0011769389,0.00003186814,0.000021041727,0.000018718058,0.000032986343,0.0000030407166,0.00080616743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9985952,0.00028703007,0.00026783446,0.00011645178,0.00053517375,0.00019835595],"domain_scores_gemma":[0.9984428,0.00013445444,0.000024066343,0.00014783212,0.0011905337,0.000060259907],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019281966,0.000035370194,0.00009507104,0.0001242091,0.00048496353,0.00003098208,0.00016340372,0.00003946953,0.0015827365],"category_scores_gemma":[0.00028638175,0.000035473244,0.000034563618,0.0005272634,0.00034342456,0.00019756834,0.000011169247,0.00010366977,0.000013597899],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045091354,0.0023077936,0.23316275,0.00023230187,0.00011629999,0.0000015986734,0.15816015,0.16023248,0.005066271,0.38610807,0.04268395,0.011883247],"study_design_scores_gemma":[0.002467143,0.0017779386,0.59581757,0.00038773497,0.00004399107,0.0000011831362,0.047778692,0.10999132,0.029416231,0.013671171,0.19762664,0.0010203867],"about_ca_topic_score_codex":0.01144567,"about_ca_topic_score_gemma":0.01033315,"teacher_disagreement_score":0.37243688,"about_ca_system_score_codex":0.000011553457,"about_ca_system_score_gemma":0.00008114576,"threshold_uncertainty_score":0.9993299},"labels":[],"label_agreement":null},{"id":"W2205749379","doi":"10.1007/s10479-015-2026-y","title":"A simple analysis of the batch arrival queue with infinite-buffer and Markovian service process using roots method: $$ GI ^{[X]}/C$$ G I [ X ] / C - $$ MSP /1/\\infty $$ M S P / 1 / ∞","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Queue; Theory of computation; Simple (philosophy); Markovian arrival process; Markov process; Applied mathematics; Mathematics; Computer science; Buffer (optical fiber); Burke's theorem; Algorithm; Mathematical optimization; Discrete mathematics; Combinatorics; Queue management system; Statistics; Computer network; Fork–join queue; Telecommunications","score_opus":0.2093153899610347,"score_gpt":0.45275628948718816,"score_spread":0.24344089952615347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2205749379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907124,0.0000659931,0.00493404,0.0023013821,0.000016680675,0.00035796114,0.00002697307,0.000020843849,0.0015637443],"genre_scores_gemma":[0.997485,0.0000067029996,0.0016665003,0.00053510815,0.000099846926,0.000028321927,0.00003766598,0.000026176405,0.00011467207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99758166,0.00030402857,0.00045300796,0.0003740953,0.00091012265,0.00037709423],"domain_scores_gemma":[0.9945808,0.0002647263,0.0001630335,0.0006637092,0.004277416,0.00005029082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037191496,0.00018163506,0.0004580481,0.0011447758,0.0004504757,0.00023832933,0.0005314015,0.00007608277,0.0001412417],"category_scores_gemma":[0.0012789983,0.00012651314,0.00010973635,0.008056502,0.0002442407,0.0012708252,0.00038236874,0.00029013382,0.000009832535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033587372,0.00020901243,0.06680043,0.00027832013,0.0013005395,0.0000046265236,0.0012355592,0.9186102,0.0024933806,0.0073034056,0.00036985686,0.0010587986],"study_design_scores_gemma":[0.00045361792,0.000041284817,0.012462266,0.000092861395,0.0007145021,0.0000016111927,0.0037490556,0.9726594,0.0024682947,0.0056070886,0.001479511,0.00027050622],"about_ca_topic_score_codex":0.0045241714,"about_ca_topic_score_gemma":0.008283306,"teacher_disagreement_score":0.054338165,"about_ca_system_score_codex":0.000018636454,"about_ca_system_score_gemma":0.00020948269,"threshold_uncertainty_score":0.6839224},"labels":[],"label_agreement":null},{"id":"W2217046481","doi":"10.1007/s10479-015-2052-9","title":"Explicit formula for the optimal government debt ceiling","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Fiscal Policies and Political Economy","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Debt-to-GDP ratio; Government debt; Debt; Internal debt; Debt ratio; External debt; Ceiling (cloud); Economics; Debt levels and flows; Recourse debt; Senior debt; Monetary economics; Finance; Engineering","score_opus":0.5218130253534555,"score_gpt":0.44392939073866433,"score_spread":0.0778836346147912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2217046481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55201983,0.006022884,0.04277879,0.15144573,0.0004927333,0.0024721066,0.0017511512,0.00003364393,0.24298313],"genre_scores_gemma":[0.9938515,0.00015053245,0.0010283338,0.00069306395,0.00020241436,0.0001924572,0.000008450419,0.000012873843,0.003860415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989393,0.000017940818,0.0003917129,0.00016570857,0.00009453158,0.00039084535],"domain_scores_gemma":[0.99900097,0.00031260948,0.000029170871,0.0003008689,0.00022079555,0.0001356097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018230238,0.00006574255,0.00016879594,0.00006371816,0.00024722554,0.000110264955,0.00029214242,0.000048344005,0.0001315674],"category_scores_gemma":[0.000770444,0.000054262928,0.00009283088,0.00014809384,0.00010089585,0.00018493691,0.00009756583,0.00012794041,0.00016401435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018584717,0.000055669934,0.0002201048,0.00000985245,0.000027955359,1.2067864e-7,0.00046191018,0.0070372713,0.000009611082,0.96911997,0.022518389,0.0005205492],"study_design_scores_gemma":[0.0005979057,0.00049386383,0.00094363507,0.000011910613,0.0000029093303,0.0000014318931,0.0018633333,0.23946843,0.002805492,0.048901338,0.70471513,0.00019463626],"about_ca_topic_score_codex":0.0009985457,"about_ca_topic_score_gemma":0.00007781069,"teacher_disagreement_score":0.92021865,"about_ca_system_score_codex":0.000047832018,"about_ca_system_score_gemma":0.00005344682,"threshold_uncertainty_score":0.22127779},"labels":[],"label_agreement":null},{"id":"W2230461717","doi":"10.1007/s10479-015-2091-2","title":"Exact and heuristic approaches for the cycle hub location problem","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Bounding overwatch; Benchmark (surveying); Mathematical optimization; Metaheuristic; Theory of computation; Heuristic; Tree (set theory); Steiner tree problem; Network topology; Tree network; Set (abstract data type); Flow network; Branch and bound; Network planning and design; Routing (electronic design automation); Algorithm; Mathematics","score_opus":0.2801187575592472,"score_gpt":0.42866052791683307,"score_spread":0.14854177035758587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2230461717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042337507,0.00093711814,0.94749373,0.006952103,0.00003391028,0.00088895054,0.00002184029,0.000065322434,0.0012694922],"genre_scores_gemma":[0.9721858,0.00042283593,0.02663251,0.000011901922,0.00004887631,0.00020289152,0.0000039159145,0.000018628838,0.000472641],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924314,0.00012358896,0.00016651503,0.00011242456,0.00016971443,0.00018461951],"domain_scores_gemma":[0.99853206,0.00077735697,0.0000080324435,0.00020875905,0.000435367,0.000038411425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001819282,0.000054876717,0.00007383781,0.00009757031,0.00022045993,0.000059711947,0.00012508463,0.00003789355,0.000018370309],"category_scores_gemma":[0.0007092951,0.000033479795,0.000017477882,0.00027115032,0.00011289907,0.0001490664,0.000030709383,0.00007279847,0.0000060445755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010531389,0.000029663199,0.00016435151,0.00012531587,0.000041695792,9.860401e-8,0.0004965828,0.8718409,0.003612077,0.013197976,0.0017832002,0.10869763],"study_design_scores_gemma":[0.00018180588,0.000054730728,0.0015642935,0.000045935474,0.000004197638,0.000001342935,0.00012980252,0.9850655,0.010595365,0.0009346616,0.0013517735,0.00007059455],"about_ca_topic_score_codex":0.000018361727,"about_ca_topic_score_gemma":0.000016106407,"teacher_disagreement_score":0.9298483,"about_ca_system_score_codex":0.000010866174,"about_ca_system_score_gemma":0.000038115173,"threshold_uncertainty_score":0.16956218},"labels":[],"label_agreement":null},{"id":"W223119275","doi":"10.1023/a:1026102724889","title":"A Tabu Search with Slope Scaling for the Multicommodity Capacitated Location Problem with Balancing Requirements","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Tabu search; Initialization; Mathematical optimization; Heuristic; Integer programming; Theory of computation; Scaling; Mathematics; Integer (computer science); Computer science; Scale (ratio); Algorithm","score_opus":0.20830744040420834,"score_gpt":0.4026867677618781,"score_spread":0.19437932735766977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W223119275","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08744001,0.00020390358,0.90612924,0.00091142376,0.000023160226,0.002264254,0.000010301276,0.000091374604,0.0029263613],"genre_scores_gemma":[0.9318562,0.000044574605,0.06758884,0.000020377847,0.000012207573,0.0002922134,0.000015192378,0.00002637825,0.0001440164],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877626,0.00010410058,0.00022155301,0.00013678276,0.000421668,0.0003396107],"domain_scores_gemma":[0.9979867,0.00027720333,0.000011501492,0.00023984138,0.0014127791,0.0000720121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001623012,0.00009110458,0.000119132215,0.00012101874,0.00040924927,0.00013896888,0.00013750837,0.0000368862,0.000034652734],"category_scores_gemma":[0.00029265735,0.000057175814,0.000018988365,0.0006980064,0.00013714902,0.0002348877,0.000014191824,0.00019471107,0.000006658346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002517687,0.00008930233,0.00008760615,0.0002507283,0.0000761677,4.748069e-7,0.0012904044,0.9844324,0.0011626112,0.009915196,0.00025082304,0.0024191001],"study_design_scores_gemma":[0.0005245762,0.00017925561,0.00007716622,0.00018241501,0.000010485646,0.0000032265907,0.0016027516,0.976626,0.01971046,0.0001217275,0.00083920814,0.00012276124],"about_ca_topic_score_codex":0.00005278075,"about_ca_topic_score_gemma":0.0001326644,"teacher_disagreement_score":0.8444162,"about_ca_system_score_codex":0.000026753301,"about_ca_system_score_gemma":0.000104536,"threshold_uncertainty_score":0.3147656},"labels":[],"label_agreement":null},{"id":"W2233455626","doi":"10.1007/s10479-015-2096-x","title":"Self-regenerating environmental absorption efficiency and the $$\\varvec{ soylent~green~scenario}$$ s o y l e n t g r e e n s c e n a r i o","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Pollution; Biosphere; Social planner; Environmental science; Absorption (acoustics); Sink (geography); Theory of computation; Natural resource economics; Environmental economics; Computer science; Economics; Microeconomics; Physics; Ecology; Geography","score_opus":0.0406006296852944,"score_gpt":0.32394771970636255,"score_spread":0.28334709002106817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2233455626","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897157,0.0003960344,0.0007687608,0.0059086876,0.000031689317,0.00049104006,0.000020287296,0.000013474022,0.0026543026],"genre_scores_gemma":[0.99650514,0.0012325298,0.00037190504,0.000064757216,0.000035009856,0.000057058252,0.0000024428286,0.00000970963,0.0017214338],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802446,0.00037888164,0.00029029013,0.000314422,0.00064182567,0.0003501147],"domain_scores_gemma":[0.99927264,0.00022550266,0.000035675846,0.00033972866,0.000031254636,0.00009518689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022677216,0.0001012261,0.00012826061,0.000067894885,0.0006854055,0.000073092524,0.00032831632,0.000055833993,0.00044874553],"category_scores_gemma":[0.000113517825,0.000052354902,0.000050576105,0.00023050794,0.00084253214,0.0002717794,0.0003451092,0.00012917127,0.00022561905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035820456,0.0020458756,0.07787504,0.0001587151,0.00019885029,0.000020360954,0.014224398,0.03509921,0.62429094,0.118485995,0.0027520284,0.12449039],"study_design_scores_gemma":[0.004190734,0.00093125174,0.07047145,0.0002665416,0.000029331337,0.00008230188,0.0021640414,0.87218994,0.039529573,0.0015946385,0.007724131,0.0008260618],"about_ca_topic_score_codex":0.0007811933,"about_ca_topic_score_gemma":0.0007382519,"teacher_disagreement_score":0.83709073,"about_ca_system_score_codex":0.00004840357,"about_ca_system_score_gemma":0.000023470431,"threshold_uncertainty_score":0.5271654},"labels":[],"label_agreement":null},{"id":"W2253181232","doi":"10.1007/s10479-016-2114-7","title":"Loyal customer bases as innovation disincentives for duopolistic firms using strategic signaling and Bayesian analysis","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Incentive; Product (mathematics); Customer base; Industrial organization; Microeconomics; Game theory; Marketing; Business; New product development; Economics; Computer science","score_opus":0.6269283437231469,"score_gpt":0.5722951305975785,"score_spread":0.05463321312556835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2253181232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92083913,0.00003553999,0.075115554,0.0021786273,0.000044125693,0.00027582017,0.000086741085,0.000009817949,0.0014146363],"genre_scores_gemma":[0.99517685,0.000014924073,0.0025027234,0.00012382722,0.000075112664,0.000020298545,0.000019988403,0.000009642467,0.002056625],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968853,0.0002970886,0.0008578995,0.00041174347,0.0012097982,0.00033815324],"domain_scores_gemma":[0.99150974,0.0017825956,0.00013285554,0.0003202304,0.0061879307,0.00006662997],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0060268296,0.00010859263,0.00026337462,0.002594346,0.0007258636,0.0004359569,0.0002847111,0.00006915817,0.0010243009],"category_scores_gemma":[0.007818084,0.000068544774,0.00008468884,0.006561182,0.00036567097,0.0005765817,0.00010749699,0.00009916981,0.000026596132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019832572,0.00027531668,0.011668039,0.000028356742,0.00026710433,0.0000041973267,0.0009629545,0.007006609,0.19575559,0.7476683,0.0013855473,0.034779657],"study_design_scores_gemma":[0.0017303429,0.000636895,0.013830442,0.00027464388,0.0001223834,0.000010492035,0.010699759,0.7123902,0.087453075,0.16882923,0.003271532,0.0007510015],"about_ca_topic_score_codex":0.00016109971,"about_ca_topic_score_gemma":0.00006555544,"teacher_disagreement_score":0.7053836,"about_ca_system_score_codex":0.00002046469,"about_ca_system_score_gemma":0.00024651576,"threshold_uncertainty_score":0.9998889},"labels":[],"label_agreement":null},{"id":"W2258667926","doi":"10.1007/s10479-015-2046-7","title":"Ex-ante real estate Value at Risk calculation method","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Value at risk; Basel II; Real estate; Expected shortfall; Lease; Portfolio; Risk management; Market risk; Solvency; Actuarial science; Business; Computer science; Finance; Economics; Market liquidity; Capital requirement; Microeconomics","score_opus":0.389446211350737,"score_gpt":0.45290081348337274,"score_spread":0.06345460213263576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2258667926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70341235,0.00011437642,0.0040301518,0.0014046243,0.00014201172,0.00023181629,0.00013088985,0.000019290432,0.2905145],"genre_scores_gemma":[0.97736955,0.0075064977,0.009805006,0.000051334606,0.00014123724,0.000027694916,0.000074973046,0.000033437438,0.0049902904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99840504,0.00021635002,0.00058961986,0.00033048796,0.000094523246,0.00036397768],"domain_scores_gemma":[0.99876,0.0001634235,0.00009671168,0.00042505583,0.00037955065,0.00017527053],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006870102,0.00009631774,0.00028245233,0.00042712677,0.0002760004,0.00011599585,0.000222521,0.00009578054,0.00018484588],"category_scores_gemma":[0.0009084838,0.00011025091,0.000087831395,0.00037657193,0.00010008118,0.00036415798,0.00014521461,0.00021063403,0.00092566735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045648983,0.0005688608,0.16072135,0.00008026937,0.00032130815,0.000014237181,0.011177167,0.3602089,0.00040002016,0.34858662,0.052314416,0.06515039],"study_design_scores_gemma":[0.0010393967,0.0003663169,0.02224218,0.000019990768,0.000007839363,0.000006821626,0.0004805031,0.8388153,0.0021680838,0.025075672,0.10932166,0.00045629108],"about_ca_topic_score_codex":0.008720905,"about_ca_topic_score_gemma":0.0011098,"teacher_disagreement_score":0.47860634,"about_ca_system_score_codex":0.000115714516,"about_ca_system_score_gemma":0.000107110696,"threshold_uncertainty_score":0.99985224},"labels":[],"label_agreement":null},{"id":"W2269687184","doi":"10.1007/s10479-015-2062-7","title":"The multi-vehicle cumulative covering tour problem","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; HEC Montréal","funders":"Instituto Politécnico Nacional; Agence Nationale de la Recherche","keywords":"Computer science; Set cover problem; Theory of computation; Cover (algebra); Mathematical optimization; Set (abstract data type); Duration (music); Integer programming; Operations research; Time limit; Integer (computer science); Mathematics; Algorithm; Engineering","score_opus":0.4816960370809513,"score_gpt":0.45775293004690115,"score_spread":0.02394310703405017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2269687184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84856427,0.0006076429,0.0032901424,0.0558922,0.000405644,0.001894445,0.000009775853,0.00012599127,0.08920988],"genre_scores_gemma":[0.99103445,0.00005752556,0.0003545121,0.00038817732,0.00015281906,0.00008117115,0.000014863388,0.000009439187,0.007907016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863654,0.000052450556,0.000271756,0.00016776477,0.0005839414,0.0002875161],"domain_scores_gemma":[0.99770856,0.000033836048,0.000014892698,0.0002956678,0.0019239339,0.000023102808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00269477,0.00007292431,0.00008296656,0.00017870934,0.0005846144,0.00033451,0.0003290664,0.000025757283,0.00012715264],"category_scores_gemma":[0.00075240224,0.00005388231,0.00003905716,0.0007160423,0.00012310466,0.0008344361,0.00027335458,0.00013668407,0.0006202119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011457739,0.00057860994,0.00326863,0.00016491281,0.00011696701,0.000003201882,0.0014639341,0.41286504,0.00087887153,0.34619558,0.21819378,0.016155882],"study_design_scores_gemma":[0.0004441568,0.000032595777,0.004741779,0.000025938076,0.0000047023086,1.5212477e-7,0.0033337388,0.65773666,0.00048389353,0.001710299,0.3313431,0.00014295678],"about_ca_topic_score_codex":0.0066608125,"about_ca_topic_score_gemma":0.006569641,"teacher_disagreement_score":0.34448525,"about_ca_system_score_codex":0.000016728061,"about_ca_system_score_gemma":0.000064595755,"threshold_uncertainty_score":0.9999539},"labels":[],"label_agreement":null},{"id":"W2273410570","doi":"10.1007/s10479-015-1822-8","title":"Robust scenario-based value-at-risk optimization","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TD Bank Group","funders":"","keywords":"Theory of computation; Heuristic; Value at risk; Computer science; Mathematical optimization; Computational complexity theory; Expected shortfall; Value (mathematics); Robust optimization; Optimization algorithm; Algorithm; Risk management; Mathematics; Machine learning; Finance; Economics","score_opus":0.6708934013309007,"score_gpt":0.5373646680948094,"score_spread":0.13352873323609127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273410570","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24131861,0.0010218173,0.68972105,0.017588094,0.00048013148,0.0013402584,0.00018444347,0.00009408048,0.048251513],"genre_scores_gemma":[0.9296517,0.00096116296,0.058985583,0.00027040427,0.00014767726,0.00005620127,0.00014466896,0.000028432234,0.009754197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99387306,0.0013944432,0.0007655155,0.00045668322,0.0031207132,0.00038956848],"domain_scores_gemma":[0.9908585,0.0007183878,0.00011352408,0.0008831799,0.007105369,0.00032105364],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.013484234,0.00012085887,0.00024035099,0.0010297318,0.00065681443,0.00041781386,0.00072410644,0.000124996,0.0005711604],"category_scores_gemma":[0.012479272,0.00009477915,0.00009804352,0.0027437664,0.00026980508,0.0006661924,0.00017982387,0.00024883664,0.0004938746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006741108,0.0001124215,0.0046377946,9.991237e-7,0.000007938762,0.0000020075913,0.00037219876,0.93145263,0.00002208157,0.0012684696,0.05885494,0.003201104],"study_design_scores_gemma":[0.00038862342,0.00022016947,0.0010070354,0.000009598818,0.000004093999,0.0000016809274,0.00036952895,0.9810271,0.0024273742,0.00085484417,0.013579392,0.000110503155],"about_ca_topic_score_codex":0.00076109584,"about_ca_topic_score_gemma":0.0002758416,"teacher_disagreement_score":0.68833303,"about_ca_system_score_codex":0.000051505227,"about_ca_system_score_gemma":0.00081136805,"threshold_uncertainty_score":0.99583906},"labels":[],"label_agreement":null},{"id":"W2295318779","doi":"10.1023/a:1020966106259","title":"On the (r|X p )-Medianoid Problem on a Network with Vertex and Edge Demands","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Group for Research in Decision Analysis; University of New Brunswick; HEC Montréal","funders":"","keywords":"Theory of computation; Vertex (graph theory); Computer science; Enhanced Data Rates for GSM Evolution; Facility location problem; Operations research; Graph; Theoretical computer science; Mathematics; Algorithm; Artificial intelligence","score_opus":0.24393543535074527,"score_gpt":0.351529036306678,"score_spread":0.1075936009559327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295318779","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95145804,0.0001703587,4.576133e-7,0.039216593,0.000006905573,0.00022192679,0.000011996931,0.0000069842063,0.008906736],"genre_scores_gemma":[0.99739534,0.0004397397,0.000020006006,0.0012832714,0.000091750735,0.00004190633,0.000009837795,5.442454e-7,0.0007176107],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99922967,0.00017674075,0.00008110789,0.00013221246,0.00018620794,0.00019403803],"domain_scores_gemma":[0.9992402,0.00048326643,0.000008374378,0.000046416204,0.00016697831,0.00005472233],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031848327,0.000050970804,0.00007269525,0.000012029146,0.00043644523,0.000039968992,0.00011755071,0.00003665385,0.0009249475],"category_scores_gemma":[0.000057916568,0.000014325252,0.000019059842,0.00030758712,0.0001753885,0.00003956958,0.000026926617,0.00015617069,0.00007155927],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048759277,0.0009864236,0.0010973159,0.000018393595,0.000053844164,0.0000071398676,0.00049158017,0.00071694556,0.05264495,0.36973372,0.53864163,0.03512043],"study_design_scores_gemma":[0.001944752,0.061555203,0.5044296,0.00092296413,0.000019601495,0.000037241112,0.0024620516,0.02178081,0.011918044,0.05048252,0.34318745,0.0012598056],"about_ca_topic_score_codex":0.000050897077,"about_ca_topic_score_gemma":0.00026964847,"teacher_disagreement_score":0.50333226,"about_ca_system_score_codex":0.000002045166,"about_ca_system_score_gemma":0.0000042314427,"threshold_uncertainty_score":0.9999883},"labels":[],"label_agreement":null},{"id":"W2296485814","doi":"10.1023/a:1020949602625","title":"Sensitivity Analysis to the Value of p of the ℓ p Distance Weber Problem","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Theory of computation; Range (aeronautics); Sensitivity (control systems); Mathematical optimization; Value (mathematics); Computer science; Set (abstract data type); Mathematics; Algorithm; Statistics","score_opus":0.18074010714106006,"score_gpt":0.3758739859940399,"score_spread":0.19513387885297986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296485814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88316995,0.00014443819,0.003270663,0.08785636,0.00007885358,0.0010170446,0.000035576377,0.000012395145,0.024414713],"genre_scores_gemma":[0.99617755,0.000042223925,0.0000895608,0.00040456298,0.000043150478,0.000027450933,0.000005773222,0.000004034475,0.0032056859],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986158,0.00011416005,0.00031542237,0.00015158308,0.0006345647,0.00016845496],"domain_scores_gemma":[0.9980856,0.0000421475,0.000029061093,0.0005608391,0.0012732289,0.000009129206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021305876,0.000060803708,0.0001396794,0.00029246227,0.0002565709,0.00005232232,0.00032024906,0.00001990032,0.0005426037],"category_scores_gemma":[0.00041782128,0.00003726802,0.000120919205,0.0032809176,0.00014116564,0.00024719696,0.0002427516,0.00009328797,0.00007575376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001894476,0.00045091464,0.008758138,0.0002139237,0.00037634795,3.60832e-7,0.00078389386,0.76772475,0.0013702984,0.16353382,0.053682834,0.00308579],"study_design_scores_gemma":[0.00015878186,0.000026260412,0.14734001,0.000058047786,0.00013054001,1.1211922e-7,0.001062598,0.7715717,0.0032546138,0.00041735472,0.07582255,0.00015746048],"about_ca_topic_score_codex":0.006908494,"about_ca_topic_score_gemma":0.014870851,"teacher_disagreement_score":0.16311647,"about_ca_system_score_codex":0.0000063911807,"about_ca_system_score_gemma":0.00001355646,"threshold_uncertainty_score":0.9997046},"labels":[],"label_agreement":null},{"id":"W2302298156","doi":"10.1007/s10479-015-2001-7","title":"Multi-trip pickup and delivery problem with time windows and synchronization","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Computer Research Institute of Montréal; École de Technologie Supérieure; Université de Montréal; Transport Canada","funders":"","keywords":"Vehicle routing problem; Tabu search; Computer science; Pickup; Benchmark (surveying); Operations research; Scheduling (production processes); Routing (electronic design automation); Job shop scheduling; Synchronization (alternating current); Mathematical optimization; Theory of computation; Computer network; Algorithm; Mathematics; Artificial intelligence","score_opus":0.091053267242863,"score_gpt":0.36662861446233885,"score_spread":0.27557534721947585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2302298156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6875971,0.00088721554,0.3081831,0.001615782,0.000015439475,0.00071079633,0.000029067285,0.00012644594,0.00083503965],"genre_scores_gemma":[0.8767445,0.0009208974,0.12132417,0.000015501746,0.000023386385,0.000033370587,0.00000620505,0.000026605883,0.0009053345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991132,0.00015341493,0.00016722162,0.00015563435,0.00020844472,0.0002020705],"domain_scores_gemma":[0.9990349,0.00016746562,0.00000937166,0.0001544752,0.00055710477,0.00007667788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008261804,0.00007768914,0.00011047474,0.00020203287,0.00014468074,0.0000653134,0.00007064131,0.000054714135,0.000060227827],"category_scores_gemma":[0.0001774765,0.000055446395,0.000008689824,0.00031541867,0.00014346877,0.00032349984,0.000045574954,0.0000915211,0.000014431319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006433936,0.00013194367,0.009940169,0.0002813792,0.00016870942,0.000006913264,0.0015856235,0.6742479,0.18613896,0.0009436903,0.0019092564,0.124581076],"study_design_scores_gemma":[0.00077734044,0.00018243997,0.0053144693,0.00017914167,0.0000058392675,0.000010817517,0.000056516288,0.97138804,0.021459805,0.000027604023,0.00043702777,0.0001609277],"about_ca_topic_score_codex":0.000028996265,"about_ca_topic_score_gemma":0.000029933844,"teacher_disagreement_score":0.29714012,"about_ca_system_score_codex":0.00001570119,"about_ca_system_score_gemma":0.000053572243,"threshold_uncertainty_score":0.22610384},"labels":[],"label_agreement":null},{"id":"W2330511976","doi":"10.1007/s10479-016-2145-0","title":"Static target search path planning optimization with heterogeneous agents","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Research and Development Canada","keywords":"Mathematical optimization; Computer science; Motion planning; Integer programming; Key (lock); Relaxation (psychology); Theory of computation; Path (computing); Quadratic programming; Quadratic equation; Computational complexity theory; Mathematics; Algorithm; Artificial intelligence","score_opus":0.24273312120667526,"score_gpt":0.4363235730292383,"score_spread":0.19359045182256304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330511976","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03362188,0.000076728094,0.96128356,0.004208808,0.000045165027,0.00031730268,0.00001844426,0.000057165988,0.00037091432],"genre_scores_gemma":[0.56612504,0.00005119682,0.43301356,0.00011570878,0.000033363394,0.000044323282,0.000011971217,0.000016255748,0.00058859016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971852,0.00045468746,0.00028404614,0.00040641087,0.0011061565,0.000563556],"domain_scores_gemma":[0.9976628,0.0002855379,0.000029020859,0.0006512922,0.0011975955,0.0001737979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015008794,0.000120273704,0.00016793329,0.00040939965,0.00035130564,0.00020247282,0.0008347963,0.00005300814,0.00005634952],"category_scores_gemma":[0.00026285095,0.00007908837,0.000031187476,0.00081002497,0.0001600617,0.0006851336,0.00023438406,0.00016778769,0.000060365157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013245576,0.000084564635,0.0006051825,0.000012589593,0.000030939682,0.0000694526,0.0009445287,0.99308455,0.0005859172,0.00073529565,0.0015059431,0.0023277928],"study_design_scores_gemma":[0.00030788122,0.0005191991,0.00064470834,0.0001771209,0.0000012713455,0.000026240155,0.000055925993,0.98520017,0.012656004,0.00010633734,0.00016875331,0.0001363648],"about_ca_topic_score_codex":0.00006415376,"about_ca_topic_score_gemma":9.1669824e-7,"teacher_disagreement_score":0.5325031,"about_ca_system_score_codex":0.000031982625,"about_ca_system_score_gemma":0.00034077922,"threshold_uncertainty_score":0.322513},"labels":[],"label_agreement":null},{"id":"W2345837865","doi":"10.1007/s10479-016-2201-9","title":"Robust DEA to assess the reliability of methyl methacrylate-hardened hybrid poplar wood","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Service de Recherche et d'EXpertise en Transformation des Produits Forestiers; Université du Québec en Abitibi-Témiscamingue; University of Toronto","funders":"","keywords":"Data envelopment analysis; Theory of computation; Hardening (computing); Engineered wood; Computer science; Mathematical optimization; Mathematics; Pulp and paper industry; Algorithm; Materials science; Composite material; Engineering","score_opus":0.24463209559389026,"score_gpt":0.43112233088842944,"score_spread":0.18649023529453918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345837865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9839144,0.000034542947,0.0010025084,0.011752533,0.000023369355,0.0006714715,0.00005994737,0.000008555868,0.0025326884],"genre_scores_gemma":[0.9958418,0.000094128576,0.0017682833,0.00013083467,0.000015207063,0.00007140124,0.0000027958674,0.000012142487,0.0020634248],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99692285,0.00090638915,0.00039681248,0.00035519304,0.0009534194,0.00046534088],"domain_scores_gemma":[0.99811286,0.00056607946,0.000032147487,0.0009248518,0.00017025265,0.00019381469],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0057414835,0.00011944351,0.00020961002,0.000081461105,0.0003048594,0.000035891047,0.0006500748,0.00005255167,0.0028492084],"category_scores_gemma":[0.0024389152,0.00006631444,0.000102569364,0.0005047381,0.00086802186,0.00040917774,0.00061010075,0.00018478812,0.00019854882],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039125793,0.0018687099,0.16590005,0.00008117123,0.00010598205,0.000012053458,0.0023749124,0.13177994,0.6478506,0.0010551496,0.019867051,0.02871315],"study_design_scores_gemma":[0.00029009703,0.0005381813,0.1976786,0.000024692301,0.0000093813605,0.0000027041335,0.00083853403,0.0006214051,0.79161036,0.0016415638,0.006550357,0.00019411364],"about_ca_topic_score_codex":0.0015703341,"about_ca_topic_score_gemma":0.0003090539,"teacher_disagreement_score":0.1437598,"about_ca_system_score_codex":0.00014482459,"about_ca_system_score_gemma":0.000061678016,"threshold_uncertainty_score":0.9980623},"labels":[],"label_agreement":null},{"id":"W2400948522","doi":"10.1007/s10479-016-2218-0","title":"Coordination of supply chain with a dominant retailer under government price regulation by revenue sharing contracts","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Revenue sharing; Supply chain; Microeconomics; Revenue; Business; Industrial organization; Government revenue; Government (linguistics); Economics; Finance; Marketing","score_opus":0.09069082994476892,"score_gpt":0.3307609102312852,"score_spread":0.24007008028651627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400948522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9576685,0.00014655244,0.0039223023,0.026113257,0.0000734828,0.001134071,0.00004859451,0.000018227096,0.010875027],"genre_scores_gemma":[0.98937523,0.000058621088,0.00007545119,0.0002527452,0.00012138186,0.00008330488,0.000029463792,0.000017982838,0.009985805],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99815255,0.000045517645,0.00033790807,0.00025930486,0.00092545804,0.0002792642],"domain_scores_gemma":[0.99863404,0.00008130439,0.00011521065,0.0003271155,0.00082344643,0.000018865536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018805903,0.00010415427,0.00016653887,0.00021538169,0.00018095622,0.000108905726,0.0002441777,0.000045826608,0.00043664535],"category_scores_gemma":[0.00027705613,0.000072337854,0.000039626677,0.0004882014,0.00013537661,0.0010444706,0.00015129823,0.00008011334,0.000037441645],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007095795,0.001080218,0.020713849,0.0005724773,0.00026709028,0.0000070443407,0.00037965726,0.002424183,0.37549317,0.3463089,0.24006796,0.011975915],"study_design_scores_gemma":[0.00863899,0.0008570345,0.14549576,0.0030422607,0.000116100666,0.0000038838425,0.0036653248,0.06746849,0.29349253,0.009192063,0.46673092,0.001296655],"about_ca_topic_score_codex":0.0005584056,"about_ca_topic_score_gemma":0.00023254409,"teacher_disagreement_score":0.3371168,"about_ca_system_score_codex":0.000060606515,"about_ca_system_score_gemma":0.000031324667,"threshold_uncertainty_score":0.47809604},"labels":[],"label_agreement":null},{"id":"W2404422255","doi":"10.1007/s10479-017-2448-9","title":"Computational study of valid inequalities for the maximum k-cut problem","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Clique; Mathematics; Vertex (graph theory); Combinatorics; Focus (optics); Graph; Set (abstract data type); Inequality; Relaxation (psychology); Semidefinite programming; Mathematical optimization; Discrete mathematics; Computer science; Algorithm; Mathematical analysis","score_opus":0.5021551982509271,"score_gpt":0.5168750330118258,"score_spread":0.014719834760898665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404422255","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40653253,0.00025854635,0.5639283,0.0231617,0.0002200333,0.0030651852,0.000118673306,0.000039132756,0.0026759158],"genre_scores_gemma":[0.98186827,0.000022501521,0.017525764,0.000037679965,0.000045160643,0.00015548375,0.000003827453,0.0000042992615,0.00033704203],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984448,0.00019752169,0.000299102,0.00019569126,0.0006538811,0.00020901281],"domain_scores_gemma":[0.9964891,0.0007696196,0.000058478814,0.0008554382,0.0017915173,0.00003581072],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0025006554,0.00006380304,0.00013751515,0.00016447705,0.0016509922,0.00041243876,0.0018281507,0.000022833163,0.0000143124],"category_scores_gemma":[0.00038567354,0.000046318994,0.00006239123,0.00021002513,0.0003311843,0.00045734938,0.0005441804,0.0001336448,0.0000031359493],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025232575,0.0010311931,0.0007272792,0.00006265626,0.00013466498,0.0000014207938,0.009231118,0.05541032,0.00006567283,0.9056212,0.0032844213,0.024404846],"study_design_scores_gemma":[0.00094426115,0.0017298349,0.015707826,0.000055850844,0.0000067948413,0.0000031892278,0.0037492616,0.69452107,0.0021805656,0.2788074,0.002118882,0.0001750627],"about_ca_topic_score_codex":0.0008806332,"about_ca_topic_score_gemma":0.00039968058,"teacher_disagreement_score":0.63911074,"about_ca_system_score_codex":0.000004354118,"about_ca_system_score_gemma":0.00016511677,"threshold_uncertainty_score":0.99964875},"labels":[],"label_agreement":null},{"id":"W2407184141","doi":"10.1007/s10479-016-2221-5","title":"Multiobjective variable mesh optimization","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Eurostars; Erasmus+; European Commission","keywords":"Mathematical optimization; Benchmark (surveying); Multi-objective optimization; Crossover; Theory of computation; Metaheuristic; Pareto principle; Evolutionary algorithm; Computer science; Population; Mathematics; Operator (biology); Algorithm; Artificial intelligence","score_opus":0.14629043189146912,"score_gpt":0.4340246466199914,"score_spread":0.2877342147285223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407184141","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023467201,0.000053373235,0.9906257,0.003063736,0.00009372175,0.0004146739,0.000019330097,0.000078432895,0.005416407],"genre_scores_gemma":[0.12082438,0.00034695488,0.8746156,0.00013766145,0.000058507438,0.00013759833,0.000007357337,0.000018737459,0.0038531832],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997868,0.0003666897,0.0003061138,0.00044107475,0.00062343804,0.0003946626],"domain_scores_gemma":[0.99486965,0.00039410972,0.00003932123,0.000647168,0.0039301603,0.00011959269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011394625,0.00011188066,0.00015539513,0.00047729549,0.000376101,0.00012578323,0.0006864078,0.00007304909,0.00017164939],"category_scores_gemma":[0.0015811195,0.00008359284,0.000043427593,0.0015434399,0.00018926268,0.0018539013,0.00029889625,0.00013760556,0.00008213601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000140154,0.00021935173,0.000039320574,0.0000056735985,0.000031819363,0.0000025909553,0.0004625771,0.81878567,0.0051059066,0.15119314,0.00070904725,0.023430863],"study_design_scores_gemma":[0.00057015696,0.00017577296,0.00021056163,0.000046349873,0.0000012782559,0.0000048573334,0.00007065173,0.9505809,0.045303486,0.0018835124,0.0009858741,0.00016662016],"about_ca_topic_score_codex":0.00007563888,"about_ca_topic_score_gemma":0.000012195457,"teacher_disagreement_score":0.14930964,"about_ca_system_score_codex":0.000060716717,"about_ca_system_score_gemma":0.00032245295,"threshold_uncertainty_score":0.3408817},"labels":[],"label_agreement":null},{"id":"W2417816772","doi":"10.1007/s10479-018-2916-x","title":"Pricing policies for selling indivisible storable goods to strategic consumers","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Dynamic pricing; Monopolistic competition; Revenue management; Revenue; Product (mathematics); Nonlinear pricing; Pricing schedule; Order (exchange); Variable pricing","score_opus":0.43601966889142446,"score_gpt":0.46285017815339324,"score_spread":0.026830509261968782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2417816772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88179696,0.00011188471,0.0025638028,0.008103363,0.00027907518,0.001526012,0.0000121660805,0.00006825248,0.10553852],"genre_scores_gemma":[0.99392027,0.00003665288,0.00085533,0.0017388094,0.0006810603,0.00012467318,0.000026629628,0.000022564802,0.002594028],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985315,0.000028313698,0.00026794907,0.00024833743,0.000427724,0.0004961265],"domain_scores_gemma":[0.99856544,0.00008869719,0.0000325707,0.00027431105,0.0010084055,0.000030575557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020172456,0.00010544836,0.00015014157,0.00087027217,0.0007350992,0.000520229,0.00034122446,0.000040953328,0.0004388033],"category_scores_gemma":[0.00027908036,0.00010075374,0.000053961154,0.0011533296,0.00015345994,0.00065382116,0.00017469027,0.00010273019,0.00029533834],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018137663,0.00055845594,0.004511277,0.0008122613,0.0002508046,0.0000029981009,0.002442713,0.011104857,0.011780582,0.77070445,0.18800735,0.009642865],"study_design_scores_gemma":[0.0008377718,0.000505074,0.0014306554,0.00023280313,0.000030906634,4.7493836e-7,0.01306096,0.0913744,0.022174522,0.0085816,0.86121833,0.00055249815],"about_ca_topic_score_codex":0.0020678642,"about_ca_topic_score_gemma":0.00061145716,"teacher_disagreement_score":0.76212287,"about_ca_system_score_codex":0.000019650593,"about_ca_system_score_gemma":0.00007296561,"threshold_uncertainty_score":0.5653863},"labels":[],"label_agreement":null},{"id":"W24773904","doi":"10.1023/a:1014955216633","title":"Operational Decisions in AGV-Served Flowshop Loops: Fleet Sizing and Decomposition","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Texas at Dallas","keywords":"Theory of computation; Computer science; Decomposition; Set (abstract data type); Material flow; Minification; Mathematical optimization; Throughput; Loop (graph theory); Decomposition method (queueing theory); Industrial engineering; Algorithm; Mathematics; Engineering","score_opus":0.17081165853302757,"score_gpt":0.43412470764294725,"score_spread":0.2633130491099197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W24773904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.977603,0.0009813037,0.017728984,0.0016197464,0.00006962604,0.00022825376,0.000016314341,0.000052662628,0.0017001024],"genre_scores_gemma":[0.96181494,0.0028213784,0.034917656,0.00007605561,0.00006504689,0.00004771149,0.000080914295,0.000018286519,0.00015802572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882317,0.00010515057,0.0003158249,0.00017569495,0.00033119865,0.0002489648],"domain_scores_gemma":[0.9989797,0.00023121452,0.0000061029295,0.0001850408,0.00050207693,0.00009587323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008559643,0.00008740137,0.0001299929,0.0004765167,0.00021491919,0.00013742172,0.00012638156,0.00007641144,0.0001491431],"category_scores_gemma":[0.0003798589,0.00009035177,0.000026403943,0.0007757901,0.000060567636,0.00035458448,0.000042912165,0.00023053662,0.000028055276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000127904395,0.00007045158,0.0009250778,0.0000066530943,0.000014929613,0.0000068878326,0.00043884627,0.98662513,0.0036299764,0.0011387109,0.00036350818,0.006767006],"study_design_scores_gemma":[0.00030879976,0.0000435232,0.006195104,0.00007021515,0.0000015063645,0.000010330239,0.00024044732,0.9883002,0.004137626,0.00015411497,0.00043229992,0.00010583973],"about_ca_topic_score_codex":0.00010985439,"about_ca_topic_score_gemma":0.00041789695,"teacher_disagreement_score":0.017188674,"about_ca_system_score_codex":0.000022140779,"about_ca_system_score_gemma":0.000058682206,"threshold_uncertainty_score":0.36844385},"labels":[],"label_agreement":null},{"id":"W2527340811","doi":"10.1007/s10479-016-2321-2","title":"An integer programming approach to curriculum-based examination timetabling","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schedule; Computer science; Theory of computation; Curriculum; Set (abstract data type); Integer programming; Integer (computer science); Course (navigation); Operations research; Mathematics education; Programming language; Mathematics; Algorithm; Sociology; Pedagogy","score_opus":0.5537578790127029,"score_gpt":0.568445045148991,"score_spread":0.014687166136288066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527340811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50307727,0.00010224671,0.48734787,0.0053811567,0.000096946445,0.0006070536,0.000024833429,0.00006512397,0.0032974947],"genre_scores_gemma":[0.9359637,0.0000062880636,0.06204889,0.000088858185,0.000103799364,0.00015097138,0.000013321529,0.000014647686,0.0016095405],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945573,0.0012829785,0.00065840245,0.0006329925,0.002296481,0.00057180255],"domain_scores_gemma":[0.9920013,0.0011257426,0.000051280556,0.0009871033,0.00551904,0.00031552924],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.021116633,0.00012201692,0.00024027846,0.0017930907,0.0006395049,0.0005795826,0.0010128841,0.00009013369,0.00023621783],"category_scores_gemma":[0.016039463,0.00007422035,0.00010540348,0.0038454959,0.00022821476,0.00084506086,0.00010468766,0.00020591465,0.0005595528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045741155,0.0030831317,0.003664922,0.0000135141445,0.000054354867,0.000002441661,0.0016795391,0.079700805,0.040205967,0.048721593,0.0060509653,0.81677705],"study_design_scores_gemma":[0.0014946732,0.0018446307,0.029973717,0.00031601038,0.000028921058,0.000013275826,0.006496466,0.80578005,0.09988887,0.0048056613,0.04836996,0.0009877894],"about_ca_topic_score_codex":0.00024163551,"about_ca_topic_score_gemma":0.000059898393,"teacher_disagreement_score":0.8157892,"about_ca_system_score_codex":0.000029133296,"about_ca_system_score_gemma":0.00033346566,"threshold_uncertainty_score":0.99224883},"labels":[],"label_agreement":null},{"id":"W2529544702","doi":"10.1007/s10479-016-2336-8","title":"An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Calgary","keywords":"Computer science; Schedule; Scheduling (production processes); Operations research; Mathematical optimization; Operating system; Mathematics","score_opus":0.4946935409284301,"score_gpt":0.5864833560107651,"score_spread":0.09178981508233497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529544702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6839693,0.00018456676,0.30892292,0.0038454009,0.000013537895,0.0018700295,0.00022986757,0.00001848227,0.00094587123],"genre_scores_gemma":[0.8875474,0.00003188702,0.11160949,0.000085702275,0.000047025747,0.00040155073,0.0000068395802,0.00001963652,0.00025051952],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.991067,0.0036103053,0.0013106519,0.0008560625,0.0024270483,0.0007289121],"domain_scores_gemma":[0.98037183,0.015120002,0.00020556846,0.0015182527,0.0026243043,0.00016003089],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.030926015,0.0002030708,0.0004932801,0.0010906094,0.0004858337,0.00034148333,0.0025953706,0.00017806745,0.00010094675],"category_scores_gemma":[0.020929474,0.00011335793,0.00016623281,0.0020443178,0.0013165371,0.00066127133,0.00025994267,0.0004036242,0.000011205878],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010390839,0.0013478183,0.0070165223,0.00008770683,0.00012870962,0.000008386475,0.03425513,0.12738073,0.64975387,0.06284706,0.0010839921,0.115050994],"study_design_scores_gemma":[0.0023737496,0.0010679131,0.0053979815,0.00042387686,0.000013075831,0.000013008784,0.05238738,0.64224786,0.27849784,0.012165638,0.0049762754,0.00043540067],"about_ca_topic_score_codex":0.0011684237,"about_ca_topic_score_gemma":0.0007061215,"teacher_disagreement_score":0.5148671,"about_ca_system_score_codex":0.000027636077,"about_ca_system_score_gemma":0.00041380394,"threshold_uncertainty_score":0.9978656},"labels":[],"label_agreement":null},{"id":"W2530903825","doi":"10.1007/s10479-016-2348-4","title":"An integrated approach of data envelopment analysis and boosted generalized linear mixed models for efficiency assessment","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Data envelopment analysis; Theory of computation; Computer science; Operations research; Variable (mathematics); Econometrics; Sample (material); Efficiency; Control variable; Management science; Mathematical optimization; Economics; Mathematics; Statistics","score_opus":0.6296381408603613,"score_gpt":0.588157474481827,"score_spread":0.041480666378534314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2530903825","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36694923,0.000106639665,0.6307118,0.0012168688,0.000014525775,0.00040561592,0.00040437092,0.000009210043,0.00018174306],"genre_scores_gemma":[0.86103916,0.00015615344,0.13791066,0.000027442646,0.00001655632,0.000050492934,0.00024887806,0.000010174372,0.00054044346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99334437,0.0014320526,0.0012834719,0.0010068578,0.0025127116,0.00042053912],"domain_scores_gemma":[0.99024945,0.0016846596,0.0001619965,0.0022433437,0.0054760873,0.00018447834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02190094,0.00015777393,0.00063050457,0.0023293335,0.00042722406,0.00022965993,0.0021004274,0.00009850073,0.00010292868],"category_scores_gemma":[0.0033759947,0.0000918058,0.00015017185,0.0054436,0.00056107144,0.0010581069,0.00045750316,0.00013095916,0.0000041063813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036604982,0.0041178605,0.0044508595,0.000046364337,0.001826738,0.0000024668986,0.0024829225,0.6472943,0.13488084,0.031108165,0.004881597,0.16854186],"study_design_scores_gemma":[0.0004110447,0.0002273298,0.0016804711,0.000014672169,0.00007410161,4.6164254e-7,0.0006573578,0.9840124,0.011447868,0.0008553082,0.0004966813,0.00012227806],"about_ca_topic_score_codex":0.0005273222,"about_ca_topic_score_gemma":0.0003854112,"teacher_disagreement_score":0.49408996,"about_ca_system_score_codex":0.000027378752,"about_ca_system_score_gemma":0.0006687525,"threshold_uncertainty_score":0.75904727},"labels":[],"label_agreement":null},{"id":"W2531470941","doi":"10.1007/s10479-016-2344-8","title":"Using managerial revenue and cost estimates to value early stage real option investments","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cash flow; Margin (machine learning); Revenue; Econometrics; Economics; Index (typography); Gross margin; Terminal value; Value (mathematics); Cash flow forecasting; Computer science; Microeconomics; Finance; Production (economics)","score_opus":0.40448125066685753,"score_gpt":0.4477826350915301,"score_spread":0.04330138442467257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531470941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99532425,0.0006225688,0.000747558,0.0015877241,0.000049429986,0.0003145035,0.0003997344,0.000005697164,0.0009485372],"genre_scores_gemma":[0.98599106,0.0045438563,0.0031950523,0.00008306929,0.0000755847,0.00003813095,0.000014737987,0.000014184003,0.006044337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99905217,0.000053736276,0.0003217949,0.00025310827,0.000085211606,0.00023398543],"domain_scores_gemma":[0.9994146,0.000064371765,0.00004073897,0.00022574462,0.00013873432,0.000115773284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011489786,0.000073133095,0.00018786876,0.00048775924,0.00021285318,0.0001311344,0.00012207744,0.0000489369,0.00011705625],"category_scores_gemma":[0.0002888294,0.00006340002,0.000044885084,0.00035120946,0.00012316693,0.00037706376,0.000103174614,0.00005782407,0.00016281911],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004707121,0.00009316375,0.010524562,0.000018523797,0.00009254409,0.0000035625374,0.0007133664,0.0012602749,0.0074674613,0.97754574,0.0013780021,0.00085572],"study_design_scores_gemma":[0.003973316,0.0019886307,0.4625168,0.0005932465,0.000063837986,0.0000069787325,0.000983829,0.14700058,0.06155897,0.27861995,0.040909264,0.0017845843],"about_ca_topic_score_codex":0.006630741,"about_ca_topic_score_gemma":0.00025621193,"teacher_disagreement_score":0.6989258,"about_ca_system_score_codex":0.00003790855,"about_ca_system_score_gemma":0.000024215698,"threshold_uncertainty_score":0.9999842},"labels":[],"label_agreement":null},{"id":"W2550116943","doi":"10.1007/s10479-016-2380-4","title":"Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"SFU Community Trust Endowment Fund","keywords":"Stock (firearms); Shareholder; Portfolio; Financial economics; Earnings; Economics; Emerging markets; Business; Context (archaeology); Econometrics; Finance; Corporate governance","score_opus":0.26575713921673744,"score_gpt":0.3940926706013812,"score_spread":0.12833553138464376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550116943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8898634,0.00017058742,0.0033260407,0.0075407876,0.00011817698,0.0005392581,0.0003747855,0.000027915105,0.09803905],"genre_scores_gemma":[0.9963775,0.00042218846,0.0015044743,0.0003129741,0.0000702592,0.00008158741,0.000009261365,0.000014950386,0.0012068024],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9983752,0.000060570623,0.0005134512,0.0004019509,0.00015850792,0.00049034134],"domain_scores_gemma":[0.9987929,0.000068743044,0.00013574354,0.0003532804,0.00048692164,0.00016242544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012295636,0.00014104503,0.00029822538,0.00036880875,0.0003189599,0.00021931753,0.00020868091,0.000074268115,0.00050528446],"category_scores_gemma":[0.00025610105,0.00010741997,0.000049935083,0.0007346417,0.00029442282,0.00058650936,0.00004949898,0.00010057391,0.00019442945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016409226,0.0000956382,0.014390061,0.000014386403,0.000042232743,0.0000040936766,0.00012095556,0.0009481651,0.000097048876,0.9767715,0.0033830141,0.0039688274],"study_design_scores_gemma":[0.0041806204,0.0089308005,0.64172816,0.00078565546,0.000013441479,0.00004766732,0.005417003,0.0010929885,0.0058968537,0.22396325,0.10634215,0.0016013831],"about_ca_topic_score_codex":0.0011018544,"about_ca_topic_score_gemma":0.00030712894,"teacher_disagreement_score":0.7528082,"about_ca_system_score_codex":0.00007494762,"about_ca_system_score_gemma":0.00029830128,"threshold_uncertainty_score":0.553251},"labels":[],"label_agreement":null},{"id":"W2598497522","doi":"10.1007/s10479-018-2829-8","title":"NORTA for portfolio credit risk","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Group for Research in Decision Analysis; Brock University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Credit risk; Multivariate normal distribution; Econometrics; Mathematics; Marginal distribution; Monte Carlo method; Portfolio; Inverse; Multivariate statistics; Computer science; Applied mathematics; Statistics; Random variable; Economics; Actuarial science; Finance","score_opus":0.34951970351562434,"score_gpt":0.4431592246527254,"score_spread":0.09363952113710106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598497522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9311044,0.00093606947,0.020955725,0.0029251943,0.00042643648,0.00071598374,0.0016693972,0.000023570032,0.04124323],"genre_scores_gemma":[0.99087805,0.00064034434,0.002059965,0.000025709824,0.00087091676,0.00011360003,0.00006513386,0.000016800292,0.005329465],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878335,0.00002259249,0.0004971969,0.0002753044,0.000084683954,0.00033687986],"domain_scores_gemma":[0.9983375,0.00012069834,0.00007002247,0.00040524226,0.000981825,0.000084675965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018011685,0.00007270763,0.00020726585,0.00046941408,0.00060623686,0.00007841775,0.0002480666,0.00008355803,0.0007300178],"category_scores_gemma":[0.0015701682,0.00008140281,0.000109164066,0.0005913627,0.00028223539,0.00023036248,0.00005762146,0.00013874554,0.00042431158],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040956522,0.00018316957,0.038004663,0.000012267591,0.000045760193,4.720845e-7,0.0005359502,0.00032949744,0.00007304529,0.8395789,0.116024755,0.0051705507],"study_design_scores_gemma":[0.00043391204,0.00071349123,0.24743094,0.000014814249,0.000004104109,0.0000010906572,0.0001279236,0.020531489,0.0022265108,0.06345465,0.66484094,0.00022012736],"about_ca_topic_score_codex":0.0013574515,"about_ca_topic_score_gemma":0.000795286,"teacher_disagreement_score":0.77612424,"about_ca_system_score_codex":0.000015665819,"about_ca_system_score_gemma":0.00009326323,"threshold_uncertainty_score":0.79931825},"labels":[],"label_agreement":null},{"id":"W2612949480","doi":"10.1007/s10479-017-2512-5","title":"On the optimality of coupon books","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Coupon; Market share; Business; Marketing; Set (abstract data type); Advertising; Action (physics); Computer science; Finance","score_opus":0.44090244058046657,"score_gpt":0.4539300486181374,"score_spread":0.013027608037670835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612949480","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.655951,0.000037788886,0.000045457167,0.02847776,0.00010023009,0.00044166352,0.0000054274933,0.000010340954,0.31493032],"genre_scores_gemma":[0.9955713,0.000030170453,0.000022422666,0.0008409535,0.00017225867,0.000035525005,0.0000061850014,0.000007581748,0.0033135903],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99889684,0.000039078644,0.0001979236,0.00013855682,0.0005326686,0.00019491372],"domain_scores_gemma":[0.99831,0.00008750115,0.00006402276,0.0007924103,0.00073753635,0.000008479337],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0026278014,0.00006351767,0.000105959654,0.00018391579,0.0008653199,0.0003753209,0.0007046335,0.000025800206,0.0009201325],"category_scores_gemma":[0.0010484533,0.00004341479,0.00006008373,0.00011619739,0.00032072386,0.0004951047,0.00034177068,0.00013591653,0.00015075073],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037062782,0.0001549871,0.00080353767,0.00006536694,0.000031327705,0.0000014585331,0.000051420062,0.0008064695,0.00060874806,0.90248483,0.09370368,0.0012510974],"study_design_scores_gemma":[0.0017133908,0.00046010833,0.11031312,0.00063181017,0.00004814184,5.7982356e-7,0.0035849623,0.17883097,0.039232153,0.065926395,0.598524,0.00073441514],"about_ca_topic_score_codex":0.0016916515,"about_ca_topic_score_gemma":0.00017067266,"teacher_disagreement_score":0.83655846,"about_ca_system_score_codex":0.0000054671477,"about_ca_system_score_gemma":0.000025614961,"threshold_uncertainty_score":0.99999315},"labels":[],"label_agreement":null},{"id":"W2613210738","doi":"10.1007/s10479-017-2507-2","title":"On component commonality for periodic review assemble-to-order systems","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Component (thermodynamics); Mathematical optimization; Stock (firearms); Computer science; Order (exchange); Regular polygon; Base (topology); Operations research; Mathematics; Economics; Engineering","score_opus":0.4354616218522958,"score_gpt":0.4860514672669335,"score_spread":0.05058984541463768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613210738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37082568,0.0072134384,0.0031401832,0.34675744,0.0020184945,0.015903303,0.00014831188,0.00015886933,0.2538343],"genre_scores_gemma":[0.9884553,0.0005875717,0.00011696854,0.006225564,0.0004904339,0.0007327266,0.00009655035,0.000023321309,0.0032715749],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99829364,0.00006376165,0.0003533521,0.00027811853,0.0006652012,0.0003459043],"domain_scores_gemma":[0.9971692,0.000094308365,0.00007684089,0.0009112563,0.0017163799,0.000032030148],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0035735613,0.00011882713,0.0002684174,0.00028550427,0.0014188669,0.0009565193,0.000757671,0.000034732937,0.0002772116],"category_scores_gemma":[0.0014271439,0.00010302303,0.000090655776,0.00023353158,0.00011106791,0.0005676819,0.00035353162,0.0001346551,0.00039622287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070357244,0.0004038223,0.00067312404,0.0035143949,0.00007295058,0.000003081697,0.000034145134,0.002382019,0.00022276834,0.4090013,0.58117616,0.0024458666],"study_design_scores_gemma":[0.0005070769,0.00012799622,0.0063104676,0.0020644204,0.000021712847,3.2104538e-7,0.0001956944,0.03078604,0.00011743853,0.00082200643,0.9587881,0.00025871064],"about_ca_topic_score_codex":0.0018399674,"about_ca_topic_score_gemma":0.00020337652,"teacher_disagreement_score":0.6176296,"about_ca_system_score_codex":0.000020527368,"about_ca_system_score_gemma":0.00004213261,"threshold_uncertainty_score":0.99988115},"labels":[],"label_agreement":null},{"id":"W2730563372","doi":"10.1007/s10479-017-2567-3","title":"A meta-heuristic for capacitated green vehicle routing problem","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Vehicle routing problem; Mathematical optimization; Alternative fuel vehicle; Heuristic; Routing (electronic design automation); Ant colony optimization algorithms; Computer science; Ant colony; Engineering; Automotive engineering; Alternative fuels; Mathematics; Computer network","score_opus":0.484601735208781,"score_gpt":0.48273314728261624,"score_spread":0.0018685879261647886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2730563372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52021754,0.0013113343,0.42557925,0.014090922,0.0003357139,0.0045436188,0.00048757848,0.0006716257,0.03276243],"genre_scores_gemma":[0.9159498,0.00005542617,0.08214051,0.000020674834,0.00006879518,0.00024397952,0.000017163411,0.000042189917,0.0014614264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985015,0.00019863443,0.00035914703,0.00019512148,0.00033136332,0.0004142663],"domain_scores_gemma":[0.9976161,0.00033455165,0.00003357404,0.0006109081,0.0013113278,0.00009354784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033463473,0.00011283878,0.00026478182,0.00019474242,0.0009408182,0.00026644216,0.00046544807,0.00007604043,0.00006869796],"category_scores_gemma":[0.0015745757,0.00010646997,0.00011158331,0.00021116616,0.00014820456,0.00035838364,0.000082069106,0.00023481013,0.000018682087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024077026,0.00008326255,0.00031748103,0.0002889801,0.0011391625,0.0000032383055,0.0018757038,0.9496488,0.02237333,0.013335484,0.0030736164,0.007836887],"study_design_scores_gemma":[0.00026710238,0.00007728803,0.0006355938,0.000029154993,0.000060278864,0.0000013345547,0.000098381264,0.969481,0.027631084,0.0009097417,0.0006717138,0.00013734754],"about_ca_topic_score_codex":0.00044574885,"about_ca_topic_score_gemma":0.00010597678,"teacher_disagreement_score":0.3957323,"about_ca_system_score_codex":0.000018070208,"about_ca_system_score_gemma":0.00006744803,"threshold_uncertainty_score":0.7236108},"labels":[],"label_agreement":null},{"id":"W2734352835","doi":"10.1007/s10479-020-03580-1","title":"Balancing supply and demand in the presence of renewable generation via demand response for electric water heaters","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Demand response; Renewable energy; Electric power; Grid; Population; Peak demand; Power demand; Environmental science; Power (physics); Engineering; Automotive engineering; Electricity; Electrical engineering; Mathematics; Power consumption","score_opus":0.09946719576344583,"score_gpt":0.3411121605336217,"score_spread":0.24164496477017589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2734352835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9750155,0.00038774518,0.018631296,0.005383877,0.000021496768,0.00046558827,0.0000051462966,0.0000102385075,0.00007906511],"genre_scores_gemma":[0.99880457,0.00030853372,0.00051455677,0.00009732123,0.000055885175,0.00013686987,0.000015528076,0.000011095253,0.000055637727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890316,0.0002505833,0.00022611597,0.00013717647,0.00024047577,0.0002424722],"domain_scores_gemma":[0.9994612,0.00017258688,0.000005684045,0.00016110842,0.00016102214,0.000038400638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020591132,0.00006509023,0.00011191908,0.00019301666,0.000099675344,0.000051527215,0.00015241702,0.000032193653,0.000010438113],"category_scores_gemma":[0.00023304854,0.00004676889,0.000020133913,0.00035599258,0.00003487316,0.0001680341,0.00004081789,0.0000858242,0.0000014000476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006624655,0.000009616913,0.00018799354,0.000049149123,0.000012462867,9.464908e-7,0.0011792864,0.59438443,0.40031034,0.000048556194,0.0036220371,0.00012892396],"study_design_scores_gemma":[0.00015259067,0.00014036901,0.0013384894,0.000010233081,0.0000022700785,6.755528e-7,0.00009557068,0.57899636,0.41843247,0.000024061788,0.00076725805,0.00003962249],"about_ca_topic_score_codex":0.00021920138,"about_ca_topic_score_gemma":0.00018648242,"teacher_disagreement_score":0.023789026,"about_ca_system_score_codex":0.000010848316,"about_ca_system_score_gemma":0.000020905709,"threshold_uncertainty_score":0.19071801},"labels":[],"label_agreement":null},{"id":"W2741542409","doi":"10.1007/s10479-018-2868-1","title":"Improving set partitioning problem solutions by zooming around an improving direction","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Set (abstract data type); Computer science; Zoom; Mathematical optimization; Integer programming; Algorithm; Mathematics; Programming language","score_opus":0.1797821635311046,"score_gpt":0.4289831972472035,"score_spread":0.24920103371609892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741542409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44682434,0.000353697,0.547079,0.00061520026,0.00022701675,0.0006129432,0.00006650699,0.00046483832,0.0037564265],"genre_scores_gemma":[0.9053536,0.00006203309,0.09367511,0.000026608377,0.0002867375,0.00010496906,0.00007861664,0.000051920077,0.00036041508],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978115,0.00039986434,0.00044448086,0.00030366605,0.00042384455,0.0006166627],"domain_scores_gemma":[0.99806815,0.00013919137,0.00003274325,0.0003818235,0.0012276969,0.00015036968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003342338,0.00013853486,0.00016541014,0.00036865103,0.0012146954,0.00032147893,0.00022520873,0.00011676641,0.00010256566],"category_scores_gemma":[0.0005777627,0.00015684495,0.00004548824,0.00091811887,0.00020500568,0.0010793288,0.000091337475,0.00037039662,0.00003384751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001346926,0.00011366654,0.00040340016,0.00012469145,0.000056470835,9.551321e-7,0.0021121588,0.35401765,0.6007808,0.0016512263,0.0041841795,0.036541358],"study_design_scores_gemma":[0.00013147885,0.0001616589,0.00014611373,0.000041434017,0.000005636871,0.0000037912619,0.00060669275,0.93231034,0.065698236,0.00009334934,0.000641064,0.00016020972],"about_ca_topic_score_codex":0.00084775616,"about_ca_topic_score_gemma":0.0003629202,"teacher_disagreement_score":0.57829267,"about_ca_system_score_codex":0.00007856934,"about_ca_system_score_gemma":0.000113638605,"threshold_uncertainty_score":0.9342578},"labels":[],"label_agreement":null},{"id":"W2741806916","doi":"10.1007/s10479-017-2593-1","title":"A modular capacitated multi-objective model for locating maritime search and rescue vessels","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; Dalhousie University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Backup; Coast guard; Computer science; Search and rescue; Operations research; Modular design; Artificial intelligence; Marine engineering; Engineering","score_opus":0.385724764705991,"score_gpt":0.4452719322457438,"score_spread":0.05954716753975281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741806916","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94284296,0.00012879574,0.04165025,0.011525711,0.000074176656,0.0015733627,0.00004660686,0.00004105358,0.0021170622],"genre_scores_gemma":[0.9935303,0.00009072202,0.0026008901,0.00022399504,0.00010258951,0.00021306427,0.000050694,0.000018831512,0.003168931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847645,0.000039936775,0.00030150008,0.00035943024,0.00042224416,0.00040041542],"domain_scores_gemma":[0.9967263,0.000030397307,0.000015612812,0.00058974494,0.0026089333,0.000029023375],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0026027407,0.00011704383,0.00017302803,0.00041064422,0.0017938592,0.000675811,0.00043431247,0.000059839418,0.00005324422],"category_scores_gemma":[0.0016143833,0.000116499294,0.000054030243,0.00023401862,0.0003070985,0.0014177571,0.00037416824,0.00017886398,0.00004860806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014265532,0.0004996681,0.0009225657,0.0010045959,0.00015373572,0.000002421655,0.0016096188,0.8765498,0.008790483,0.09779939,0.0030909658,0.009434088],"study_design_scores_gemma":[0.0004112599,0.000020326375,0.007390127,0.000047226116,0.0000070855967,1.5896853e-7,0.00077456364,0.9895367,0.0007429799,0.00060484157,0.00034261987,0.00012207917],"about_ca_topic_score_codex":0.01548532,"about_ca_topic_score_gemma":0.009635084,"teacher_disagreement_score":0.11298692,"about_ca_system_score_codex":0.000014938042,"about_ca_system_score_gemma":0.00007366948,"threshold_uncertainty_score":0.9995057},"labels":[],"label_agreement":null},{"id":"W2742664076","doi":"10.1007/s10479-017-2601-5","title":"Solving the capacitated clustering problem with variable neighborhood search","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja","keywords":"Variable neighborhood search; Heuristics; Benchmark (surveying); Mathematical optimization; Cluster analysis; Heuristic; Iterated local search; Variable (mathematics); Mathematics; Iterated function; Computer science; Metaheuristic; Artificial intelligence","score_opus":0.18524376840212,"score_gpt":0.41619169996105954,"score_spread":0.23094793155893953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2742664076","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20769952,0.00035060302,0.6610196,0.0072249393,0.00015624154,0.0016731987,0.000042359112,0.00029532026,0.12153821],"genre_scores_gemma":[0.91946805,0.00010879265,0.07950444,0.000021017388,0.00006187395,0.00006337525,0.0000060564316,0.0000402081,0.00072618516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831945,0.00027524217,0.00024231029,0.00017776161,0.0005151318,0.00047011973],"domain_scores_gemma":[0.99772465,0.00022605833,0.000019199504,0.00083643786,0.0011106597,0.00008299012],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0033573885,0.000106971296,0.00014548347,0.00016430095,0.0015413419,0.0006055476,0.00066853565,0.00006359025,0.000103818034],"category_scores_gemma":[0.0004848359,0.00007704771,0.000025618769,0.00039007905,0.00025519775,0.0004959999,0.0001709627,0.0004890887,0.000018755605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009540946,0.000020620948,0.00048094554,0.00006258361,0.000056213856,0.0000019448223,0.0010795443,0.98587435,0.006484401,0.0033236565,0.00040958283,0.002196583],"study_design_scores_gemma":[0.00019174234,0.00007234969,0.0012884759,0.00010350535,0.0000037137524,0.0000059683357,0.0003403737,0.9860117,0.0114666,0.00011828563,0.00028988183,0.0001073947],"about_ca_topic_score_codex":0.00041316578,"about_ca_topic_score_gemma":0.00016576082,"teacher_disagreement_score":0.7117685,"about_ca_system_score_codex":0.000023714576,"about_ca_system_score_gemma":0.00014220194,"threshold_uncertainty_score":0.99975854},"labels":[],"label_agreement":null},{"id":"W2763920787","doi":"10.1007/s10479-015-2019-x","title":"Simulation optimization: a review of algorithms and applications","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":444,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dow Chemical (Canada)","funders":"Dow Chemical Company","keywords":"Theory of computation; Homogeneous; Function (biology); Subject (documents); Algebraic number; Optimization problem","score_opus":0.7149842999777986,"score_gpt":0.6440607833342126,"score_spread":0.07092351664358598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763920787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015091335,0.009506396,0.96739644,0.009756688,0.00001991156,0.0019160039,0.00008689084,0.000039275834,0.009769268],"genre_scores_gemma":[0.92581624,0.007818862,0.0630576,0.00057983125,0.00012789202,0.0006040619,0.000085193504,0.000019705378,0.0018906012],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970082,0.00030967305,0.00081410137,0.00028482126,0.0014404175,0.00014280714],"domain_scores_gemma":[0.9892685,0.0011809845,0.000103187595,0.0006844275,0.008614651,0.00014823857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062663094,0.00007174365,0.00023234844,0.000432234,0.0001822892,0.00007842895,0.00040124965,0.00005690329,0.00025171114],"category_scores_gemma":[0.0049925786,0.00005880271,0.000053891734,0.0022811182,0.00024808318,0.000344256,0.00014025609,0.00011016062,0.000029541927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007417801,0.00014152638,0.00020554634,0.000103012586,0.0000098517485,1.3400513e-7,0.00018223145,0.9111582,0.000049555878,0.031267982,0.0076362807,0.049238272],"study_design_scores_gemma":[0.00017632707,0.00013245843,0.00022553613,0.00025853375,0.000006241185,0.0000015010614,0.00034996684,0.9111502,0.0012078421,0.011668606,0.07471868,0.000104115985],"about_ca_topic_score_codex":0.000054338398,"about_ca_topic_score_gemma":0.000005241405,"teacher_disagreement_score":0.9243071,"about_ca_system_score_codex":0.000010297798,"about_ca_system_score_gemma":0.00022175122,"threshold_uncertainty_score":0.5976944},"labels":[],"label_agreement":null},{"id":"W2786412505","doi":"10.1007/s10479-018-2767-5","title":"Preface: Risk management decisions and wealth management in Financial Economics","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Agence Nationale de la Recherche","keywords":"Theory of computation; Economics; Business management; Risk management; Finance; Business; Computer science; Business administration","score_opus":0.17091186050506654,"score_gpt":0.38945663443982764,"score_spread":0.2185447739347611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2786412505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85280955,0.0012437872,0.0019936573,0.0013865982,0.00023637433,0.0010325375,0.00016006528,0.000012564622,0.14112486],"genre_scores_gemma":[0.9432558,0.049797963,0.0042347913,0.00020016693,0.00009823725,0.00014566499,0.000010569453,0.000016584874,0.0022402331],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99817544,0.000056702902,0.0007090734,0.00048374146,0.00008976412,0.00048526353],"domain_scores_gemma":[0.9991462,0.000052692685,0.000080732,0.00048810782,0.00015127983,0.00008096485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002808383,0.00012261783,0.00028370827,0.0009781829,0.00041759564,0.00010182743,0.0003294494,0.00007409472,0.00012005982],"category_scores_gemma":[0.00017725615,0.00014237886,0.00005475271,0.00070375093,0.0002305364,0.0002896938,0.00032853003,0.00021820964,0.00040567722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052979252,0.00019364766,0.008394217,0.000031754636,0.000041869316,0.000005775549,0.0005330336,0.0007188031,5.164094e-7,0.9268592,0.0031720619,0.05999617],"study_design_scores_gemma":[0.0012904301,0.0004830943,0.48971853,0.00010329794,0.0000065823606,7.7395197e-7,0.0005980663,0.009249637,0.00011194888,0.17438854,0.3236669,0.00038219744],"about_ca_topic_score_codex":0.0007959364,"about_ca_topic_score_gemma":0.0014980352,"teacher_disagreement_score":0.7524706,"about_ca_system_score_codex":0.000054595588,"about_ca_system_score_gemma":0.000028534163,"threshold_uncertainty_score":0.58060414},"labels":[],"label_agreement":null},{"id":"W2787207162","doi":"10.1007/s10479-018-2792-4","title":"Computation of the corrected Cornish–Fisher expansion using the response surface methodology: application to VaR and CVaR","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Fonds de Recherche du Québec-Société et Culture; Université Laval","keywords":"Quantile; Kurtosis; CVAR; Skewness; Econometrics; Value at risk; Mathematics; Computation; Moment (physics); Taylor series; Portfolio; Risk management; Expected shortfall; Statistics; Economics; Algorithm; Mathematical analysis","score_opus":0.6406208474316435,"score_gpt":0.6007372589748402,"score_spread":0.03988358845680329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787207162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84556067,0.00006407412,0.14845191,0.005073824,0.00009733098,0.00057749584,0.000012781973,0.0000059276617,0.000155976],"genre_scores_gemma":[0.98416644,0.00007096586,0.0150607,0.00019931415,0.00003963035,0.000011549146,0.0000032134153,0.000008076697,0.00044012954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9937884,0.0041252854,0.0005267812,0.00029383233,0.0010821152,0.00018353897],"domain_scores_gemma":[0.9920239,0.0026288629,0.00011304306,0.00060263084,0.004569188,0.000062393345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016106231,0.000074826996,0.00017302208,0.00024708678,0.000740696,0.00013178779,0.00048594235,0.00007483342,0.000041153213],"category_scores_gemma":[0.008057289,0.00004222606,0.00004174636,0.0024413299,0.00055406353,0.00022508169,0.00022797241,0.000145265,0.000020089892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013019767,0.00015342842,0.010323409,0.0000059544655,0.000034600787,4.2801008e-7,0.012450064,0.5052353,0.4040847,0.0015871511,0.021270005,0.04355296],"study_design_scores_gemma":[0.00026453126,0.00046437437,0.10996108,0.00004282953,0.000011724489,0.000009352144,0.0034904347,0.7303131,0.14761053,0.0030455375,0.0046541113,0.00013239149],"about_ca_topic_score_codex":0.0005889013,"about_ca_topic_score_gemma":0.00018273591,"teacher_disagreement_score":0.2564742,"about_ca_system_score_codex":0.000012344772,"about_ca_system_score_gemma":0.00024048526,"threshold_uncertainty_score":0.96459097},"labels":[],"label_agreement":null},{"id":"W2788911476","doi":"10.1007/s10479-018-2761-y","title":"Mixed-asset portfolio allocation under mean-reverting asset returns","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Agence Nationale de la Recherche","keywords":"Mean reversion; Portfolio; Asset allocation; Asset (computer security); Stochastic investment model; Theory of computation; Capital asset pricing model; Economics; Computer science; Econometrics; Financial economics; Algorithm","score_opus":0.3366580378507829,"score_gpt":0.4153375755108499,"score_spread":0.07867953766006697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788911476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36300182,0.0016532186,0.57127446,0.017664373,0.00032160798,0.0009000792,0.00051365455,0.00006635171,0.04460444],"genre_scores_gemma":[0.99526894,0.00019160083,0.002799805,0.00030132945,0.00028014396,0.00012672579,0.000073738025,0.000020358437,0.0009373505],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983997,0.000019835577,0.00065896445,0.0003878497,0.00014196892,0.00039168732],"domain_scores_gemma":[0.9980797,0.00009889638,0.00010591387,0.0004899962,0.0011260784,0.0000994176],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017795647,0.00010546401,0.0002374125,0.00041003147,0.0005124052,0.000119095974,0.00037661562,0.000110179244,0.0003671621],"category_scores_gemma":[0.0007173583,0.000118539014,0.00006999788,0.0010947982,0.00023350301,0.00032488327,0.00011221827,0.00021504254,0.0008139027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008343286,0.000120458884,0.00029903813,0.000014368472,0.000025525398,3.8837766e-7,0.00033625896,0.00015246113,0.0004780833,0.9901308,0.0073839584,0.0010503195],"study_design_scores_gemma":[0.0006615839,0.000741253,0.059349496,0.000104809915,0.000010891025,0.000012253238,0.0014160717,0.035054177,0.01666278,0.8261211,0.05914556,0.0007200086],"about_ca_topic_score_codex":0.0012095246,"about_ca_topic_score_gemma":0.0007854726,"teacher_disagreement_score":0.6322671,"about_ca_system_score_codex":0.000036773967,"about_ca_system_score_gemma":0.00014385981,"threshold_uncertainty_score":0.99996406},"labels":[],"label_agreement":null},{"id":"W2796045805","doi":"10.1007/s10479-018-2830-2","title":"A clustering-based feature selection method for automatically generated relational attributes","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Data mining; Cluster analysis; Feature selection; Selection (genetic algorithm); Set (abstract data type); Table (database); Relational database; Lasso (programming language); Machine learning; Artificial intelligence","score_opus":0.26245056220044977,"score_gpt":0.4869737738800862,"score_spread":0.22452321167963646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796045805","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013433306,0.000024284653,0.9765356,0.02127125,0.000039860195,0.00040282152,0.00009658815,0.00006997984,0.0002162942],"genre_scores_gemma":[0.035347864,0.0000039579945,0.9628729,0.0002853756,0.0001675417,0.00027851344,0.00014746426,0.000009000909,0.0008873796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985752,0.00018661152,0.00023022894,0.00032580455,0.00039756458,0.00028460874],"domain_scores_gemma":[0.9960635,0.00040694335,0.00002770142,0.00038342839,0.0030341393,0.00008434311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019321406,0.00007970246,0.00011632177,0.00025563725,0.00071428774,0.0002421458,0.00050073833,0.00008090604,0.000037293223],"category_scores_gemma":[0.0006204255,0.00007282575,0.000047698144,0.0012487418,0.000106834595,0.00037459948,0.00011930318,0.00015579745,0.000034211414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006484617,0.00079317996,0.000144053,0.0000925668,0.00015352314,0.0000012318006,0.0009814063,0.0698441,0.05621543,0.4514486,0.2894125,0.13084859],"study_design_scores_gemma":[0.00016333374,0.00029532638,0.00076689763,0.000017316745,0.0000021050735,0.0000029404912,0.000008679969,0.96178526,0.023681529,0.0006399522,0.012561365,0.00007528491],"about_ca_topic_score_codex":0.000059460912,"about_ca_topic_score_gemma":0.00017889513,"teacher_disagreement_score":0.8919412,"about_ca_system_score_codex":0.000019820638,"about_ca_system_score_gemma":0.00041463578,"threshold_uncertainty_score":0.5493796},"labels":[],"label_agreement":null},{"id":"W2806849789","doi":"10.1007/s10479-018-2915-y","title":"On a 2-class polling model with reneging and $$k_i$$ k i -limited service","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polling; Polling system; Computer science; Service (business); Queue; Poisson distribution; Class (philosophy); Queueing theory; Mathematical optimization; Computer network; Mathematics; Statistics; Economics","score_opus":0.17696072489331402,"score_gpt":0.40529354322275973,"score_spread":0.2283328183294457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806849789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96810395,0.000035707282,0.00729857,0.012984397,0.0000124344,0.00018593087,0.0000032363232,0.000042853877,0.011332942],"genre_scores_gemma":[0.9955121,0.000014089961,0.0012875958,0.0020869744,0.0002071088,0.000018808916,0.0000123173595,0.000021226693,0.00083972816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988301,0.000039500428,0.00017214227,0.00026636253,0.00040215746,0.00028975535],"domain_scores_gemma":[0.9975774,0.00011198535,0.000036410405,0.000331365,0.0019236774,0.000019149707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011246181,0.000100043515,0.00014301794,0.000632161,0.0006507957,0.0002373405,0.00020014597,0.000038158865,0.000074034346],"category_scores_gemma":[0.0003953806,0.000082097955,0.000023040891,0.0014608302,0.00019028985,0.00086516485,0.00014034125,0.0001730604,0.00007333088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000389016,0.00014814603,0.00022676268,0.00011299555,0.00010477385,0.0000055824275,0.00044306627,0.5018929,0.008544242,0.4843294,0.0016706589,0.002132405],"study_design_scores_gemma":[0.00020126122,0.000051773543,0.000068432295,0.0001246298,0.0000138029045,6.482992e-7,0.00034035795,0.98349893,0.0023146244,0.012220393,0.0010457112,0.000119447344],"about_ca_topic_score_codex":0.00043280606,"about_ca_topic_score_gemma":0.0010004911,"teacher_disagreement_score":0.48160598,"about_ca_system_score_codex":0.000008685906,"about_ca_system_score_gemma":0.000039826467,"threshold_uncertainty_score":0.50054604},"labels":[],"label_agreement":null},{"id":"W2809417058","doi":"10.1007/s10479-018-2942-8","title":"Reduced cost-based variable fixing in two-stage stochastic programming","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Transport Canada","funders":"","keywords":"Mathematical optimization; Stochastic programming; Theory of computation; Variable (mathematics); Heuristic; Set (abstract data type); Random variable; Range (aeronautics); Integer programming; Computer science; Reduction (mathematics); Measure (data warehouse); Mathematics; Linear programming; Algorithm; Statistics","score_opus":0.4932199997891655,"score_gpt":0.5907253176075067,"score_spread":0.09750531781834121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809417058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7556957,0.00014762924,0.22348635,0.004352487,0.00025022423,0.0018686678,0.00004842911,0.000042590786,0.014107914],"genre_scores_gemma":[0.98335403,0.00001780344,0.013043066,0.00009335712,0.00010116376,0.00010970652,0.000021215154,0.000011675816,0.00324796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99636674,0.00059725175,0.0006638594,0.0003922771,0.0015126606,0.00046723022],"domain_scores_gemma":[0.99495137,0.0008744307,0.000059062633,0.0005930291,0.0033983495,0.00012378691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010127509,0.00009094182,0.00020233633,0.0011449666,0.00045153694,0.00044772672,0.00056253787,0.000055588607,0.0007745823],"category_scores_gemma":[0.0075937603,0.000075458796,0.000044200206,0.0036338773,0.00030665094,0.000506915,0.00010077439,0.00023763074,0.0001796413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012159502,0.00029562958,0.0019689451,0.0000050292188,0.000009979002,0.000005616002,0.0012364339,0.9363845,0.005015999,0.009115976,0.004287682,0.04155263],"study_design_scores_gemma":[0.0006511521,0.00033981373,0.0014847236,0.000073075396,0.0000021537664,0.0000014401908,0.0010044118,0.9636806,0.015166704,0.0015139154,0.015910808,0.00017116261],"about_ca_topic_score_codex":0.0011801097,"about_ca_topic_score_gemma":0.0010303559,"teacher_disagreement_score":0.22765835,"about_ca_system_score_codex":0.000024113286,"about_ca_system_score_gemma":0.00065829506,"threshold_uncertainty_score":0.90909886},"labels":[],"label_agreement":null},{"id":"W2810632803","doi":"10.1007/s10479-018-2941-9","title":"Closed-form variance swap prices under general affine GARCH models and their continuous-time limits","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Variance swap; Autoregressive conditional heteroskedasticity; Mathematics; Gaussian; Econometrics; Stochastic volatility; Affine transformation; Variance (accounting); Applied mathematics; Volatility (finance); Economics; Forward volatility","score_opus":0.2830431286606594,"score_gpt":0.3861320112043833,"score_spread":0.10308888254372389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810632803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9523666,0.002296595,0.02440366,0.0030002655,0.00006408871,0.0003569886,0.00015970011,0.00002000441,0.017332107],"genre_scores_gemma":[0.9904573,0.0014497737,0.0027017547,0.00017431671,0.00027411978,0.000032952838,0.000020301854,0.000021564398,0.004867949],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983796,0.000047539572,0.0005664834,0.0004312175,0.00010363798,0.00047154253],"domain_scores_gemma":[0.9985814,0.00012139793,0.00006128705,0.0004033575,0.0007296341,0.00010288502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002131941,0.00013676826,0.00036074503,0.00036559926,0.0004838889,0.00017297437,0.0002974451,0.00012505408,0.0002585582],"category_scores_gemma":[0.00025466314,0.00013298342,0.0000669543,0.00044104134,0.00031422265,0.00059916044,0.00013646632,0.00025097042,0.0001810504],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011892981,0.00034693768,0.0021339075,0.000050450864,0.00009755015,0.0000010954518,0.004265548,0.008735011,0.0029120506,0.96776575,0.0028901934,0.010682589],"study_design_scores_gemma":[0.0003401476,0.0003865458,0.0073572337,0.000032471613,0.0000014998448,0.0000014238494,0.00013135688,0.86895937,0.0035577873,0.112649016,0.00636344,0.0002197341],"about_ca_topic_score_codex":0.0012648123,"about_ca_topic_score_gemma":0.00032392648,"teacher_disagreement_score":0.8602243,"about_ca_system_score_codex":0.000023204264,"about_ca_system_score_gemma":0.00010042376,"threshold_uncertainty_score":0.5422906},"labels":[],"label_agreement":null},{"id":"W2896429187","doi":"10.1007/s10479-018-3077-7","title":"Sustainability dimensions and PM2.5 in supply chain logistics","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Sustainability; Work (physics); Sustainable transport; Supply chain; Environmental economics; Computer science; Dimension (graph theory); Operations research; Business; Economics; Engineering; Marketing","score_opus":0.13017586529140718,"score_gpt":0.40978408613083617,"score_spread":0.279608220839429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896429187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94495296,0.0001950676,0.0007947272,0.041302465,0.00008854635,0.0013750081,0.000006637919,0.000044052962,0.01124056],"genre_scores_gemma":[0.9971973,0.00006348972,0.00022532983,0.0006807649,0.00030664413,0.00008787549,0.000020431351,0.00001709656,0.0014010919],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981535,0.00009927971,0.0003407446,0.00034891302,0.00047750023,0.0005800711],"domain_scores_gemma":[0.9961841,0.00017087148,0.000029026942,0.00045329222,0.003137127,0.000025542531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003534056,0.000120595374,0.00018246396,0.001113011,0.00044553305,0.0002798295,0.00028492176,0.00006372418,0.00027642876],"category_scores_gemma":[0.003630724,0.0001152656,0.0000308627,0.0016158097,0.0007081914,0.00068557716,0.0006970298,0.0002255373,0.000059355603],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015915591,0.00076815847,0.054834884,0.0007983679,0.000047196805,0.00008076982,0.0010192338,0.010189229,0.0003818832,0.8703836,0.05252926,0.008808221],"study_design_scores_gemma":[0.0022496956,0.0005090795,0.2494509,0.00023846664,0.000034113265,0.0000035000953,0.045608543,0.25900173,0.0013226641,0.1890959,0.25144216,0.0010432297],"about_ca_topic_score_codex":0.006119191,"about_ca_topic_score_gemma":0.0028320586,"teacher_disagreement_score":0.68128777,"about_ca_system_score_codex":0.000059547227,"about_ca_system_score_gemma":0.00013538823,"threshold_uncertainty_score":0.92504275},"labels":[],"label_agreement":null},{"id":"W2896479483","doi":"10.1007/s10479-018-3076-8","title":"Shared mobility systems: an updated survey","year":2018,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"TRIPS architecture; Variety (cybernetics); Field (mathematics); Computer science; Point (geometry); Operations research; Transport engineering; Data science; Telecommunications; Management science; Engineering","score_opus":0.3362647373297932,"score_gpt":0.4692835955316023,"score_spread":0.13301885820180914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896479483","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942886,0.000049411054,0.0016436361,0.00016604188,0.000117784024,0.00039348486,0.00056126877,0.00012416532,0.002655608],"genre_scores_gemma":[0.9981776,0.000015843072,0.00022261885,0.000023141361,0.000052015268,0.00006807229,0.0011547391,0.000014814521,0.0002711598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987093,0.00021298895,0.0003624944,0.00016777143,0.00031765376,0.00022975728],"domain_scores_gemma":[0.99623954,0.00005202091,0.000007330083,0.00047244833,0.003136388,0.000092259885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020390602,0.00007380687,0.00012155875,0.00025709756,0.00020492253,0.00009272694,0.00021037675,0.000068774134,0.00057029416],"category_scores_gemma":[0.00012884299,0.00007460077,0.000021686214,0.0010894443,0.00020170475,0.00039414232,0.000011190231,0.00016824271,0.000104657425],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023436757,0.0026560128,0.04695706,0.00041174018,0.00060688285,0.000006908913,0.007986374,0.413532,0.123025976,0.07234185,0.32839453,0.003846303],"study_design_scores_gemma":[0.00032897017,0.0003692619,0.7225667,0.000028887096,0.0000045827155,0.000001401628,0.0007899099,0.23906933,0.026551846,0.00008572003,0.009938819,0.0002645462],"about_ca_topic_score_codex":0.0016304562,"about_ca_topic_score_gemma":0.0047772024,"teacher_disagreement_score":0.67560965,"about_ca_system_score_codex":0.000015599928,"about_ca_system_score_gemma":0.00010069489,"threshold_uncertainty_score":0.62443215},"labels":[],"label_agreement":null},{"id":"W2911134757","doi":"10.1007/s10479-020-03517-8","title":"On fairness and diversification in WTA and ATP tennis tournaments generation","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Tournament; Diversification (marketing strategy); Cluster analysis; Theory of computation; Order (exchange); Limiting; Solver","score_opus":0.4936605848398045,"score_gpt":0.40150367765372835,"score_spread":0.09215690718607616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911134757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873051,0.00050561957,0.00023656966,0.010546655,0.000017334642,0.000130688,0.00003561299,0.0000021865796,0.0012202007],"genre_scores_gemma":[0.9974454,0.001879134,0.000058772133,0.00032084397,0.000038604063,0.000009117701,0.000018220677,0.0000044577664,0.00022543767],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993967,0.0000123103655,0.00023335482,0.00018785949,0.000057241024,0.00011257588],"domain_scores_gemma":[0.99970084,0.000021730848,0.000028356302,0.00009706147,0.0000930497,0.00005896005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005400175,0.000043717173,0.000112247704,0.00019944979,0.00012670476,0.00008503883,0.000066221626,0.00003317199,0.00011912995],"category_scores_gemma":[0.00013429334,0.00004623027,0.000012576299,0.00024264026,0.00005118104,0.0001985253,0.000039726357,0.000102181875,0.000026245398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102365666,0.0003295509,0.3014788,0.00010482481,0.000066132285,0.000007795443,0.013222976,0.020842168,0.0016493525,0.64357966,0.0079824,0.01063396],"study_design_scores_gemma":[0.0006469498,0.00040102328,0.25608662,0.00002738606,0.0000016158771,7.7962784e-7,0.0005241417,0.7278232,0.0013666468,0.0021917,0.010749299,0.00018064538],"about_ca_topic_score_codex":0.00038964726,"about_ca_topic_score_gemma":0.00007140885,"teacher_disagreement_score":0.706981,"about_ca_system_score_codex":0.00000949074,"about_ca_system_score_gemma":0.000012674283,"threshold_uncertainty_score":0.18852158},"labels":[],"label_agreement":null},{"id":"W2914910073","doi":"10.1007/s10479-018-3122-6","title":"Improving the computational efficiency of stochastic programs using automated algorithm configuration: an application to decentralized energy systems","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Compute Canada","keywords":"Theory of computation; Computer science; Mathematical optimization; Computational complexity theory; Energy (signal processing); Integer (computer science); Scale (ratio); Stack (abstract data type); Photovoltaic system; Algorithm; Mathematics","score_opus":0.08685261222821998,"score_gpt":0.41343236826343277,"score_spread":0.3265797560352128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914910073","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00999476,0.00010083275,0.9879788,0.00026780154,0.000101991216,0.0014067224,0.000014177553,0.000103383165,0.0000315218],"genre_scores_gemma":[0.7514115,0.0000046547843,0.24825461,0.00004130074,0.000025221898,0.00014977578,0.000054619828,0.000013377216,0.000044968587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99738055,0.0004215997,0.0005161591,0.00042883927,0.0009116307,0.00034122204],"domain_scores_gemma":[0.99506724,0.00020909769,0.00011957002,0.0006121081,0.0038686802,0.00012330119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011065342,0.00012595112,0.00020896406,0.00034471438,0.00035742877,0.00025209234,0.00076247565,0.00005899542,0.000008529873],"category_scores_gemma":[0.00015783543,0.00010438288,0.00004186088,0.0018198187,0.00014053484,0.0007301152,0.00016062161,0.00012425739,0.0000125270535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070860556,0.0001765072,0.0000064427913,0.000012159984,0.000013880939,2.929335e-7,0.0005288048,0.946901,0.005778976,0.018975725,0.000006768818,0.02759231],"study_design_scores_gemma":[0.00028027594,0.00024056541,0.00008577162,0.000031403666,0.00000222388,0.0000070624546,0.0002700533,0.99603426,0.0028101613,0.00009837019,0.00003125515,0.00010860877],"about_ca_topic_score_codex":0.0008564018,"about_ca_topic_score_gemma":0.00001818024,"teacher_disagreement_score":0.7414167,"about_ca_system_score_codex":0.000058135953,"about_ca_system_score_gemma":0.00043762068,"threshold_uncertainty_score":0.42566103},"labels":[],"label_agreement":null},{"id":"W2937788857","doi":"10.1007/s10479-019-03197-z","title":"Preface: reliability and quality management in stochastic systems","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Theory of computation; Robustness (evolution); Reliability (semiconductor); Operations research; Quality (philosophy); Annals; Task (project management); Risk analysis (engineering); Systems engineering; Engineering","score_opus":0.12200030967543281,"score_gpt":0.407875745290656,"score_spread":0.2858754356152232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937788857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882316,0.00034488438,0.0044752606,0.00029631268,0.00007480195,0.00097204035,0.000009620919,0.000026441141,0.0055690464],"genre_scores_gemma":[0.99815553,0.0005322008,0.00044465731,0.0000054536936,0.000006938838,0.000086188425,0.0000076277915,0.000007608813,0.00075376517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989503,0.00015359464,0.0002787778,0.00016566955,0.00025207154,0.00019958903],"domain_scores_gemma":[0.9992756,0.00009849981,0.000006431068,0.000311433,0.00026860624,0.00003939366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002093676,0.00005774956,0.0001337092,0.00016114967,0.000039441213,0.000046424517,0.00009426696,0.00004853956,0.000028746681],"category_scores_gemma":[0.00015951648,0.000054351352,0.000015671409,0.00031957866,0.000063953434,0.00019767541,0.00004929264,0.00015621114,0.00002437266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011137772,0.000035436475,0.00047659446,0.00028829338,0.000008418709,1.911409e-7,0.00020545548,0.9883313,0.00030237588,0.009785564,0.0001367126,0.00041850517],"study_design_scores_gemma":[0.0002630052,0.000059668924,0.017621877,0.00010716489,0.000001304365,3.6901073e-7,0.00071028067,0.98017675,0.0003048863,0.0002966813,0.00036353208,0.000094506875],"about_ca_topic_score_codex":0.00029988133,"about_ca_topic_score_gemma":0.00006568073,"teacher_disagreement_score":0.017145282,"about_ca_system_score_codex":0.000031442876,"about_ca_system_score_gemma":0.000016932343,"threshold_uncertainty_score":0.22163838},"labels":[],"label_agreement":null},{"id":"W2943717539","doi":"10.1007/s10479-019-03243-w","title":"Preface: DEA and its applications in operations and data analytics","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Theory of computation; Computer science; Analytics; Data analysis; Data science; Operations research; Econometrics; Data mining; Algorithm; Mathematics","score_opus":0.730479985523337,"score_gpt":0.6177284169091471,"score_spread":0.11275156861418989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943717539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98413646,0.00067228114,0.0030374269,0.0075882594,0.0000100745665,0.0013376443,0.00029655377,0.000020859135,0.002900436],"genre_scores_gemma":[0.99153143,0.0006318631,0.0051663714,0.000056647565,0.000018488141,0.00013582883,0.000078728175,0.000008615506,0.0023720423],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99777794,0.00018796834,0.0005196364,0.00056099356,0.0007208548,0.00023259662],"domain_scores_gemma":[0.99649656,0.0008974025,0.000027491222,0.0012908254,0.0011802729,0.00010744427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004617202,0.000084500345,0.00019027044,0.0005627199,0.00033240678,0.00034677703,0.00095663377,0.000071146635,0.00014507554],"category_scores_gemma":[0.0021238944,0.00006790357,0.000017814242,0.0016707394,0.00017199675,0.00059546577,0.00080288586,0.00024071588,0.00007450877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031622523,0.0008606874,0.057423923,0.00008298705,0.000054879856,0.0000018472684,0.0019160239,0.028440217,0.015358397,0.8381006,0.022672359,0.03505642],"study_design_scores_gemma":[0.00025576213,0.00016010096,0.029694134,0.00004741512,0.0000057602874,0.0000066134194,0.0011848152,0.9126448,0.0037196584,0.011444653,0.040622007,0.0002142674],"about_ca_topic_score_codex":0.00029003786,"about_ca_topic_score_gemma":0.0011534226,"teacher_disagreement_score":0.88420457,"about_ca_system_score_codex":0.000008189272,"about_ca_system_score_gemma":0.0001639338,"threshold_uncertainty_score":0.33439788},"labels":[],"label_agreement":null},{"id":"W2951140915","doi":"10.1007/s10479-019-03296-x","title":"A bi-criteria optimization model for medical device sterilization","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Mathematical optimization; Sterilization (economics); Theory of computation; Scheduling (production processes); Computer science; Bottleneck; Job shop scheduling; Integer programming; Linear programming; Pareto principle; Algorithm; Mathematics; Schedule; Embedded system","score_opus":0.1807393677163225,"score_gpt":0.4466198620249063,"score_spread":0.26588049430858374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951140915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032858517,0.00015406219,0.96428186,0.0008908907,0.00013670493,0.000505398,0.000034290024,0.000085330794,0.0010529413],"genre_scores_gemma":[0.7244327,0.0005602389,0.27270165,0.00018402295,0.00011404301,0.00017049341,0.0003249887,0.00005570525,0.0014561217],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987806,0.000060046987,0.00029293224,0.00015694668,0.00047798638,0.00023150234],"domain_scores_gemma":[0.99848336,0.000103726794,0.000009570865,0.0002213338,0.0010847147,0.00009731202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009717094,0.0000802604,0.00013175668,0.00026439008,0.000103714134,0.00008446078,0.00018621213,0.000115617906,0.00052203384],"category_scores_gemma":[0.0004043894,0.00008108886,0.00004024294,0.00045873687,0.0000359394,0.0002725222,0.000031223943,0.00012406117,0.000035347744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012661086,0.000030003739,0.000016233722,0.00006965106,0.000015229371,1.290504e-7,0.0002831602,0.9966456,0.00039737707,0.0008588222,0.0008535278,0.0008176025],"study_design_scores_gemma":[0.0002658784,0.000047045825,0.0000089851765,0.00004477123,0.000002081272,8.663642e-7,0.000089315625,0.9975101,0.0017479672,0.000038678627,0.00016017936,0.000084137224],"about_ca_topic_score_codex":0.000010424739,"about_ca_topic_score_gemma":0.000017826642,"teacher_disagreement_score":0.69158024,"about_ca_system_score_codex":0.000014973946,"about_ca_system_score_gemma":0.00013264744,"threshold_uncertainty_score":0.5715904},"labels":[],"label_agreement":null},{"id":"W2955649334","doi":"10.1007/s10479-019-03295-y","title":"Goal programming approach for political districting in Santa Catarina State: Brazil","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Contiguity; Legislation; Redistricting; Politics; Context (archaeology); Population; State (computer science); Distribution (mathematics); Public administration; Operations research; Computer science; Political science; Economics; Sociology; Geography; Mathematics; Law; Demography","score_opus":0.11756106179337812,"score_gpt":0.42744367272472567,"score_spread":0.30988261093134756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955649334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64882356,0.00036382335,0.31879914,0.00091542973,0.00010820512,0.004107918,0.00007273311,0.00023594566,0.026573254],"genre_scores_gemma":[0.958575,0.000023180255,0.040822737,0.000015951968,0.000023006734,0.00016284181,0.00007197878,0.000022595337,0.00028270902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986905,0.000046458335,0.00030830098,0.00015963992,0.00025652783,0.0005385789],"domain_scores_gemma":[0.9992497,0.00018444574,0.0000070555193,0.0001860413,0.00026770047,0.00010503517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086647493,0.00008209429,0.00016140593,0.00022168536,0.00008390315,0.00010773468,0.00015692084,0.000054806897,0.00003271209],"category_scores_gemma":[0.00033901312,0.000078917896,0.000044573117,0.0004828384,0.000059344664,0.0001998604,0.0000503489,0.00022889793,0.000016177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007058042,0.001241059,0.0041835126,0.002868309,0.0001095176,0.000004265264,0.0026635642,0.6690401,0.0035323454,0.24852838,0.0019761352,0.06578225],"study_design_scores_gemma":[0.00037246797,0.00012696469,0.00024456703,0.000047426933,0.0000021568599,0.0000020568814,0.0010988439,0.99191475,0.0036913292,0.0004532556,0.0018973,0.00014889581],"about_ca_topic_score_codex":0.00010466185,"about_ca_topic_score_gemma":0.00003171976,"teacher_disagreement_score":0.32287464,"about_ca_system_score_codex":0.000032267206,"about_ca_system_score_gemma":0.000051713057,"threshold_uncertainty_score":0.32181785},"labels":[],"label_agreement":null},{"id":"W2963239290","doi":"10.1007/s10479-019-03343-7","title":"Biologically Inspired Parent Selection in Genetic Algorithms","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Quality control and genetic algorithms; Genetic algorithm; Selection (genetic algorithm); Computer science; Genetic representation; Theory of computation; Algorithm; Mathematical optimization; Simple (philosophy); Artificial intelligence; Meta-optimization; Mathematics; Machine learning","score_opus":0.23378032836205606,"score_gpt":0.45118896427990646,"score_spread":0.2174086359178504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963239290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55125904,0.00046708382,0.43243974,0.008042311,0.00019356282,0.0018884448,0.000015521277,0.000099666606,0.0055946563],"genre_scores_gemma":[0.86287194,0.00062739116,0.13469894,0.00011568159,0.000044150416,0.00012537633,0.0000103649645,0.000011226562,0.0014949157],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968411,0.0007483513,0.00047937216,0.00047733274,0.000952702,0.000501175],"domain_scores_gemma":[0.9975671,0.00025291013,0.00002749397,0.00046275306,0.0015634974,0.0001262545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024369275,0.00010222442,0.00020330513,0.0008853577,0.00015679767,0.00021169096,0.0009899966,0.000092747185,0.00033556085],"category_scores_gemma":[0.0007738998,0.00008931255,0.0000469511,0.0025205598,0.00011376106,0.00035916307,0.0003595421,0.00036334083,0.0003228685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079456826,0.002085334,0.042335384,0.00013224997,0.000100337755,0.00004591493,0.0014066059,0.6540633,0.022748774,0.090537034,0.0037739947,0.18269165],"study_design_scores_gemma":[0.0002727835,0.0003687812,0.059369057,0.00001955564,3.8634403e-7,0.0000044781973,0.000032051787,0.934696,0.0033679265,0.00050296145,0.0012565835,0.00010941175],"about_ca_topic_score_codex":0.00049163454,"about_ca_topic_score_gemma":0.00007148031,"teacher_disagreement_score":0.31161293,"about_ca_system_score_codex":0.000040894083,"about_ca_system_score_gemma":0.00038586403,"threshold_uncertainty_score":0.4149929},"labels":[],"label_agreement":null},{"id":"W2964355227","doi":"10.1007/s10479-019-03342-8","title":"Combined maintenance and routing optimization for large-scale sewage cleaning","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"HEC Montréal","keywords":"Sewerage; Scheduling (production processes); Computer science; Sanitary sewer; Routing (electronic design automation); Population; Flood myth; Operations research; Environmental science; Engineering; Operations management; Environmental engineering","score_opus":0.045520989528172115,"score_gpt":0.34967770830667694,"score_spread":0.3041567187785048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964355227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8988986,0.00011237389,0.09628874,0.00035679288,0.0002298934,0.0006655308,0.00003109467,0.00006430365,0.003352675],"genre_scores_gemma":[0.9871869,0.00013209556,0.012029477,0.000029736608,0.00007462154,0.000035049547,0.000020285723,0.000022569991,0.00046924505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991632,0.000025515714,0.00017847828,0.00013388165,0.00015064447,0.00034828315],"domain_scores_gemma":[0.9992675,0.000072684124,0.000009406138,0.00015716424,0.0004511426,0.00004209355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069797406,0.00007206497,0.00012441137,0.00012201138,0.00017032438,0.00006693566,0.000093847404,0.00005193273,0.000037199305],"category_scores_gemma":[0.00011778993,0.00006891044,0.00002752545,0.00018955015,0.000024383877,0.00022287677,0.00004413452,0.00015497547,0.0000051530383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025347417,0.000014041032,0.0014245234,0.00012873922,0.000023838667,5.441568e-7,0.0012759416,0.9750173,0.010820883,0.008180669,0.0014075687,0.0016806214],"study_design_scores_gemma":[0.000381431,0.00009480334,0.0009921228,0.000097088916,0.0000018001725,9.590756e-7,0.0011830006,0.9798612,0.016355112,0.00010814373,0.00083152484,0.000092785405],"about_ca_topic_score_codex":0.000014388895,"about_ca_topic_score_gemma":0.000014326602,"teacher_disagreement_score":0.08828832,"about_ca_system_score_codex":0.000015231774,"about_ca_system_score_gemma":0.000021391126,"threshold_uncertainty_score":0.28100863},"labels":[],"label_agreement":null},{"id":"W2979460476","doi":"10.1007/s10479-019-03411-y","title":"Number of performance measures versus number of decision making units in DEA","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Data envelopment analysis; Efficiency; Power (physics); Rank (graph theory); Theory of computation; Computer science; Rule of thumb; Statistics; Quality (philosophy); Mathematical optimization; Unit (ring theory); Econometrics; Mathematics; Algorithm","score_opus":0.4701715564610774,"score_gpt":0.5709311294462142,"score_spread":0.10075957298513677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979460476","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9819166,0.000094848336,0.00062811276,0.00025363392,0.000093741364,0.00019533988,0.000012416667,0.0000036726633,0.016801625],"genre_scores_gemma":[0.99733925,0.00009763783,0.0017849391,0.000014875128,0.000013878205,0.000006157365,0.0000024775584,0.000009066129,0.00073170225],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9937569,0.00068340026,0.0011189402,0.00037679623,0.003719428,0.00034454072],"domain_scores_gemma":[0.98910046,0.0033407705,0.00013019405,0.0009424907,0.0064317514,0.00005435758],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01246093,0.0001017412,0.0004084421,0.00094425114,0.00013709626,0.00008778919,0.0010622357,0.00009619056,0.0014926682],"category_scores_gemma":[0.011427555,0.000080192,0.000098724624,0.0061699925,0.00030549042,0.0005400555,0.0002638416,0.00027995708,0.00057155866],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011731273,0.00071671966,0.5858707,0.00006427254,0.00008919858,0.000006472319,0.0032956048,0.2827958,0.008927251,0.016624002,0.002668748,0.097768106],"study_design_scores_gemma":[0.0042748307,0.0011952088,0.30076784,0.002194191,0.00003901088,0.000024782088,0.009174035,0.5201469,0.14292298,0.007910409,0.010417768,0.00093201647],"about_ca_topic_score_codex":0.00031251454,"about_ca_topic_score_gemma":0.00053940876,"teacher_disagreement_score":0.28510287,"about_ca_system_score_codex":0.000024392757,"about_ca_system_score_gemma":0.0004626021,"threshold_uncertainty_score":0.9994201},"labels":[],"label_agreement":null},{"id":"W2979848724","doi":"10.1007/s10479-019-03371-3","title":"Joint maintenance and just-in-time spare parts provisioning policy for a multi-unit production system","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spare part; Production (economics); Computer science; Reliability engineering; Interval (graph theory); Provisioning; Process (computing); Sensitivity (control systems); Holding cost; Theory of computation; Minification; Operations research; Total cost; Mathematical optimization; Operations management; Engineering; Mathematics; Economics; Algorithm","score_opus":0.1834285068207878,"score_gpt":0.4011294589257651,"score_spread":0.21770095210497734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979848724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983322,0.00024256598,0.009523513,0.002645523,0.00012448031,0.0030331851,0.000032946362,0.000090702924,0.0009850538],"genre_scores_gemma":[0.9924826,0.0002562586,0.0048898337,0.000012410498,0.00005533366,0.0002302085,0.000021499716,0.000020393585,0.002031453],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989113,0.00007258601,0.0002788235,0.00021921772,0.00020509199,0.00031293713],"domain_scores_gemma":[0.9989653,0.000044074397,0.0000140866,0.00025135404,0.0006723394,0.00005280344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013150689,0.00008337037,0.00017082733,0.00032912352,0.00011142301,0.00007156648,0.000093729475,0.00006282826,0.000010358889],"category_scores_gemma":[0.0007220472,0.00007606241,0.000029036688,0.00041639493,0.000058157886,0.00031018333,0.00004047226,0.00014724677,0.000024169502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030190602,0.000056935933,0.00039860132,0.00079022517,0.000012277762,5.8436154e-7,0.0008899485,0.9839327,0.007281007,0.0044577657,0.00089618395,0.0012535803],"study_design_scores_gemma":[0.00034093505,0.000109068686,0.0017842834,0.0004932186,0.0000016540964,0.0000041086737,0.0010003175,0.9860575,0.009213176,0.000037126316,0.0008569802,0.00010163211],"about_ca_topic_score_codex":0.00015923033,"about_ca_topic_score_gemma":0.00007925429,"teacher_disagreement_score":0.009160579,"about_ca_system_score_codex":0.00005511779,"about_ca_system_score_gemma":0.000092302755,"threshold_uncertainty_score":0.3101735},"labels":[],"label_agreement":null},{"id":"W2982442037","doi":"10.1007/s10479-019-03439-0","title":"Measuring short-term risk of initial public offering of equity securities: a hybrid Bayesian and Data-Envelopment-Analysis-based approach","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Equity (law); Data envelopment analysis; Term (time); Bayesian probability; Theory of computation; Econometrics; Computer science; Actuarial science; Business; Financial economics; Economics; Mathematics; Statistics; Algorithm; Artificial intelligence","score_opus":0.6435510354886637,"score_gpt":0.5586636561304721,"score_spread":0.08488737935819157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982442037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9608576,0.000315474,0.03497624,0.0003240391,0.000024085402,0.0003479497,0.00032777758,0.000008801877,0.0028179854],"genre_scores_gemma":[0.996724,0.00009159942,0.0029190558,0.000015796035,0.000019017343,0.000013340162,0.00010914442,0.000011056494,0.00009696803],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99168384,0.0014769996,0.0014382126,0.00082201185,0.0041131005,0.00046586042],"domain_scores_gemma":[0.9924713,0.0016301997,0.00020733647,0.002151624,0.0033735193,0.00016602078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02708214,0.00015623348,0.0007811179,0.0029225072,0.00034966564,0.0004278022,0.0021631895,0.000071336835,0.00031914082],"category_scores_gemma":[0.0069640214,0.0001285119,0.00021835399,0.0042646173,0.0006560024,0.00091531355,0.0013066463,0.00036042856,0.000009415999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033314526,0.0031248657,0.5653715,0.0006040377,0.0046147006,0.000014126973,0.0064616674,0.32770425,0.023627011,0.0070754755,0.0011496976,0.059919503],"study_design_scores_gemma":[0.00030093323,0.0001668237,0.02823906,0.000059109152,0.00015146619,0.0000017842972,0.0015775717,0.94401956,0.024774373,0.00037640336,0.00012789415,0.00020504964],"about_ca_topic_score_codex":0.00053249986,"about_ca_topic_score_gemma":0.0004234501,"teacher_disagreement_score":0.61631525,"about_ca_system_score_codex":0.00002245929,"about_ca_system_score_gemma":0.00071530073,"threshold_uncertainty_score":0.93861836},"labels":[],"label_agreement":null},{"id":"W2984997159","doi":"10.1007/s10479-019-03456-z","title":"A novel fuzzy reference-neighborhood rough set approach for green supplier development practices","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Theory of computation; Computer science; Fuzzy logic; Set (abstract data type); Rough set; Fuzzy set; Development (topology); Operations research; Mathematical optimization; Data mining; Artificial intelligence; Mathematics; Algorithm","score_opus":0.4492385413761365,"score_gpt":0.4634509594129097,"score_spread":0.0142124180367732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984997159","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07801319,0.0005349975,0.58501214,0.031902265,0.00028706272,0.006044106,0.00022438969,0.00017500813,0.29780683],"genre_scores_gemma":[0.7010459,0.00006693487,0.29538688,0.00020490018,0.00006212389,0.00031120013,0.00011341245,0.00001233554,0.00279634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976868,0.00012851336,0.00036605995,0.0005335128,0.000761494,0.0005236145],"domain_scores_gemma":[0.9975848,0.00025979237,0.00008470602,0.00074375817,0.0012132117,0.000113685805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021565976,0.00013357746,0.00021466352,0.00026290806,0.00037972143,0.00033385117,0.00126754,0.00010256114,0.000047006728],"category_scores_gemma":[0.0002458319,0.000106129046,0.000053185995,0.0006944498,0.0000656235,0.0009775383,0.00043235125,0.00027470596,0.00011180433],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020241798,0.0028942577,0.0018149235,0.00054684153,0.00039196725,0.000005173997,0.014088992,0.015275389,0.011560547,0.81724834,0.02668782,0.109283336],"study_design_scores_gemma":[0.0024455253,0.0020142242,0.008787671,0.00009403895,0.000012407873,0.000037806945,0.0019044826,0.6630868,0.015137337,0.0062917913,0.29908416,0.0011037748],"about_ca_topic_score_codex":0.00033113643,"about_ca_topic_score_gemma":0.000064023174,"teacher_disagreement_score":0.81095654,"about_ca_system_score_codex":0.000022463584,"about_ca_system_score_gemma":0.00063212716,"threshold_uncertainty_score":0.4327817},"labels":[],"label_agreement":null},{"id":"W2989473899","doi":"10.1007/s10479-019-03437-2","title":"Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Supply chain; Process (computing); Business; Blood collection; Operations management; Health care; Computer science; Operations research; Medicine; Medical emergency; Economics; Economic growth; Engineering; Marketing","score_opus":0.10846076419759984,"score_gpt":0.3876371638371688,"score_spread":0.279176399639569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989473899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99641305,0.000131599,0.0003494672,0.0017076686,0.000045538283,0.00075068406,5.6800127e-7,0.000025444133,0.0005759553],"genre_scores_gemma":[0.99888307,0.000043877604,0.00056828803,0.00023693933,0.00010550128,0.0000442264,0.000011427248,0.000015132057,0.00009154053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851835,0.00026739895,0.00028559862,0.00027985216,0.00039207653,0.00025672934],"domain_scores_gemma":[0.9990118,0.00012305535,0.00004476182,0.00016945896,0.0006292902,0.000021624526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030945737,0.00009036168,0.00013884666,0.00054220273,0.00040909756,0.0004917512,0.0001181595,0.00004332635,0.00030118166],"category_scores_gemma":[0.0001893327,0.00008595566,0.000019615645,0.0009864677,0.000033034503,0.0014870546,0.00009167266,0.000308483,0.000018478395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031948246,0.000716001,0.062134057,0.000026979082,0.000018465456,0.000085713655,0.00079905597,0.93395394,0.00010591751,0.0015433638,0.000060990464,0.0005235903],"study_design_scores_gemma":[0.0010708568,0.0002276793,0.0064171758,0.000025831332,0.000020122834,0.000020895906,0.020719709,0.9710738,0.00005817013,0.000018620623,0.00021690576,0.00013019645],"about_ca_topic_score_codex":0.0061201444,"about_ca_topic_score_gemma":0.0022015434,"teacher_disagreement_score":0.05571688,"about_ca_system_score_codex":0.0000030172025,"about_ca_system_score_gemma":0.000029922541,"threshold_uncertainty_score":0.9251869},"labels":[],"label_agreement":null},{"id":"W2989983753","doi":"10.1007/s10479-019-03465-y","title":"Certify or not? An analysis of organic food supply chain with competing suppliers","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Business; Certification; Supply chain; Purchasing; Dilemma; Product (mathematics); Profit (economics); Marketing; Organic certification; Organic product; Quality (philosophy); Industrial organization; Commerce; Organic farming; Microeconomics; Economics","score_opus":0.16621436024384248,"score_gpt":0.37173020917607386,"score_spread":0.20551584893223138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989983753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99040514,0.00002345956,0.000114444956,0.0024960213,0.000036975078,0.00059341453,0.000018406894,0.000027328186,0.0062847934],"genre_scores_gemma":[0.9974376,0.000024147137,0.00019275011,0.000630096,0.00009783079,0.0000360394,0.00020385264,0.000027201188,0.001350481],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787265,0.00007996754,0.00041613495,0.0003627089,0.0008535553,0.0004150031],"domain_scores_gemma":[0.9980886,0.000098297234,0.00008437747,0.0006042689,0.0010928016,0.000031670297],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017638801,0.00014460359,0.0003687686,0.0017035793,0.00022866395,0.00023965484,0.00050580676,0.000053645308,0.005513201],"category_scores_gemma":[0.0001492451,0.0001112625,0.000097163,0.0033090725,0.00014951604,0.00091080193,0.00023005335,0.0001784004,0.00011406375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032812343,0.003475872,0.48214853,0.002238836,0.007100427,0.00003358246,0.0044265753,0.16199344,0.061151553,0.25755453,0.0104929535,0.006102454],"study_design_scores_gemma":[0.0037700085,0.0027048562,0.21086942,0.0004149334,0.0009089448,0.0000019212753,0.04861626,0.64785314,0.029205654,0.00024222901,0.05399717,0.0014154455],"about_ca_topic_score_codex":0.0009605316,"about_ca_topic_score_gemma":0.0042082653,"teacher_disagreement_score":0.4858597,"about_ca_system_score_codex":0.000020253397,"about_ca_system_score_gemma":0.00008289139,"threshold_uncertainty_score":0.9953959},"labels":[],"label_agreement":null},{"id":"W3013428274","doi":"10.1007/s10479-020-03582-z","title":"Brexit and foreign exchange market expectations: Could it have been predicted?","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Brexit; Economics; Foreign exchange market; Currency; Skewness; Econometrics; Exchange rate; Volatility (finance); Foreign exchange; Financial economics; Monetary economics; International economics; European union","score_opus":0.299972120852087,"score_gpt":0.3923003954867154,"score_spread":0.0923282746346284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013428274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5579516,0.007729759,0.0074620354,0.080133595,0.00008173055,0.0018540929,0.0036959746,0.00006066853,0.34103054],"genre_scores_gemma":[0.9955697,0.0013117153,0.00061034283,0.00037478903,0.00007000262,0.000072200266,0.00007324587,0.000016266102,0.0019017131],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872404,0.00006834644,0.00047500798,0.0003512075,0.00011358884,0.0002678089],"domain_scores_gemma":[0.9990655,0.0001261725,0.00005054308,0.00025848107,0.00033271752,0.00016656086],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001198144,0.0000933447,0.00024116348,0.00022571124,0.0002522838,0.00013733291,0.00021787836,0.00008995226,0.00224411],"category_scores_gemma":[0.00090523134,0.00010650612,0.000056454697,0.00034875213,0.0001632438,0.00029637705,0.0001468773,0.00023166044,0.000028454098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035134776,0.00059638673,0.21039395,0.00076302857,0.0003590671,0.000015675643,0.016130483,0.00046398427,0.00010640069,0.63783884,0.12831753,0.004663318],"study_design_scores_gemma":[0.00092222734,0.0005882119,0.05614774,0.000057485366,0.0000049632417,0.0000023694151,0.0029624023,0.8553507,0.0001458566,0.04225449,0.041214854,0.0003487272],"about_ca_topic_score_codex":0.00051602954,"about_ca_topic_score_gemma":0.00017215272,"teacher_disagreement_score":0.8548867,"about_ca_system_score_codex":0.000020097083,"about_ca_system_score_gemma":0.000056362496,"threshold_uncertainty_score":0.99866796},"labels":[],"label_agreement":null},{"id":"W3014313361","doi":"10.1007/s10479-020-03589-6","title":"Preface: advances of real-case based operations research","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Computer science; Management science; Operations research; Mathematics; Algorithm; Economics","score_opus":0.4674967474093574,"score_gpt":0.5018092103358104,"score_spread":0.03431246292645296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014313361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80037946,0.0007044604,0.0031875928,0.12867627,0.0001035326,0.0023588669,0.000103626815,0.000098909564,0.06438729],"genre_scores_gemma":[0.9965151,0.0003270053,0.00092005986,0.00095880165,0.0003400005,0.00014247696,0.00008429768,0.000021312842,0.00069092866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99693006,0.00032987425,0.00057484175,0.00038643784,0.0012937505,0.0004850586],"domain_scores_gemma":[0.9958133,0.00024527474,0.00003019449,0.0004939112,0.003364987,0.000052297597],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004736305,0.00012397347,0.0002535002,0.00073638745,0.00084968423,0.00036935086,0.0005300476,0.00006882332,0.001260787],"category_scores_gemma":[0.0017472738,0.00011566725,0.0000904208,0.0024317715,0.0004345379,0.0016041545,0.00042591384,0.00041698958,0.00027354254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042489506,0.0015777018,0.0016901398,0.0028851784,0.0001627882,0.00024337931,0.0020461085,0.33037484,0.010645307,0.5410056,0.09671921,0.012224821],"study_design_scores_gemma":[0.0013648875,0.00052163086,0.0013389504,0.00023253997,0.000031956017,0.000003582866,0.011416574,0.6396845,0.01480705,0.0020234506,0.3280646,0.00051028957],"about_ca_topic_score_codex":0.005230081,"about_ca_topic_score_gemma":0.002787209,"teacher_disagreement_score":0.53898215,"about_ca_system_score_codex":0.0000133842095,"about_ca_system_score_gemma":0.00018768654,"threshold_uncertainty_score":0.9996522},"labels":[],"label_agreement":null},{"id":"W3016514782","doi":"10.1007/s10479-020-03612-w","title":"Assessing the performance of Canadian credit unions using a three-stage network bootstrap DEA","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Data envelopment analysis; Intermediation; Revenue; Production (economics); Economics; Bootstrapping (finance); Business; Finance; Microeconomics; Statistics","score_opus":0.7285265786464573,"score_gpt":0.5723947053950232,"score_spread":0.15613187325143407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016514782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.971964,0.0003120908,0.003080012,0.021112252,0.000060694198,0.00023319949,0.00003390984,0.000007451472,0.003196402],"genre_scores_gemma":[0.99748576,0.0000588065,0.0016304674,0.00042200828,0.00016049524,0.0000057020297,0.000005598947,0.0000105324125,0.00022063593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952717,0.0007927749,0.0007991086,0.00036753804,0.0022003916,0.0005685231],"domain_scores_gemma":[0.9947068,0.0012323977,0.000105073574,0.0007684384,0.0029103516,0.00027695528],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.010297123,0.00010622544,0.00028024372,0.0010026052,0.0015754967,0.00065375795,0.0014164825,0.00007333585,0.0005067791],"category_scores_gemma":[0.004581466,0.00007217328,0.00013051677,0.009913458,0.00064493425,0.0007568068,0.00019662247,0.00044046057,0.000044413333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006274473,0.0000312494,0.012419148,0.0000075454022,0.00003079991,0.0000038001579,0.000786591,0.9733605,0.0026240642,0.0037600975,0.0055356375,0.001434288],"study_design_scores_gemma":[0.000058289188,0.00010215198,0.014080856,0.00004268493,0.000008802872,0.0000014410786,0.0013884432,0.97400206,0.002398731,0.00019382176,0.0076345666,0.000088157074],"about_ca_topic_score_codex":0.046159543,"about_ca_topic_score_gemma":0.082947806,"teacher_disagreement_score":0.03678826,"about_ca_system_score_codex":0.000025790969,"about_ca_system_score_gemma":0.0018752821,"threshold_uncertainty_score":0.9997243},"labels":[],"label_agreement":null},{"id":"W3029114129","doi":"10.1007/s10479-020-03642-4","title":"The distributionally robust optimization model for a remanufacturing system under cap-and-trade policy: a newsvendor approach","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Taishan Scholar Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Newsvendor model; Remanufacturing; Theory of computation; Robust optimization; Computer science; Mathematical optimization; Operations research; Business; Mathematics; Supply chain; Algorithm; Manufacturing engineering; Engineering","score_opus":0.21145288266930098,"score_gpt":0.35855572599865837,"score_spread":0.14710284332935739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029114129","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021839708,0.00017899674,0.8452778,0.14792447,0.000021558822,0.0017435121,0.000032461565,0.00006717535,0.0025700897],"genre_scores_gemma":[0.9917777,0.00005709004,0.004917963,0.0015372552,0.0005705901,0.00043122808,0.00019556104,0.000030205721,0.0004824157],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983717,0.000050114988,0.0003179887,0.00030486187,0.00051819603,0.0004371205],"domain_scores_gemma":[0.9988301,0.00013382972,0.000053703247,0.00024122675,0.0007062366,0.000034937882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013831361,0.0001249076,0.00015522251,0.00025183387,0.0011448843,0.00070742815,0.0003564857,0.000049609524,0.0000058492474],"category_scores_gemma":[0.00073571387,0.00009834362,0.00006855428,0.0007253635,0.00012771894,0.0006262959,0.0003159359,0.0001549235,0.0000040590753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040682917,0.000024690347,0.000011749817,0.000332202,0.000034073742,4.8136206e-7,0.00009476194,0.740553,0.000010796313,0.25212523,0.006555058,0.00021723306],"study_design_scores_gemma":[0.00028163733,0.000013766601,0.00005887838,0.000019701029,0.000012828763,4.1568322e-7,0.0038597432,0.99044216,0.00003450526,0.00072758674,0.0044513857,0.000097366596],"about_ca_topic_score_codex":0.00044905147,"about_ca_topic_score_gemma":0.000039707105,"teacher_disagreement_score":0.98959374,"about_ca_system_score_codex":0.00006342533,"about_ca_system_score_gemma":0.00015922489,"threshold_uncertainty_score":0.88056403},"labels":[],"label_agreement":null},{"id":"W3034123046","doi":"10.1007/s10479-020-03667-9","title":"A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Data envelopment analysis; Restructuring; Cost efficiency; Mergers and acquisitions; Efficiency; Industrial organization; Inverse; Computer science; Economics; Econometrics; Operational efficiency; Operations research; Mathematical optimization; Finance; Mathematics; Statistics","score_opus":0.6036382136610892,"score_gpt":0.5492192108670334,"score_spread":0.05441900279405576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034123046","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36689156,0.00012665929,0.6068343,0.02402836,0.00006809559,0.00088923186,0.00025465337,0.00001366993,0.000893497],"genre_scores_gemma":[0.93183845,0.000010313788,0.06687302,0.00045895675,0.000069249945,0.000027981974,0.000012469312,0.0000134422635,0.00069612986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961898,0.00036573943,0.0009632908,0.0005289089,0.0013896817,0.0005625882],"domain_scores_gemma":[0.9937767,0.0007739086,0.000100599565,0.0005984453,0.0041176868,0.000632663],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0060817553,0.00012595582,0.0003522372,0.002003917,0.00075031817,0.000259992,0.0008884708,0.0000934768,0.0003242521],"category_scores_gemma":[0.01936851,0.00010657187,0.000216244,0.005337822,0.00025934918,0.0003858757,0.00014778592,0.00024996596,0.00006134489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002163771,0.000052099113,0.00002333353,0.00001032284,0.000020585117,0.000036687838,0.0030820332,0.9503102,0.0033988617,0.0016122251,0.034996945,0.006435093],"study_design_scores_gemma":[0.00020702132,0.00012655015,0.000010544111,0.000017365393,0.000012409806,0.0000126774485,0.000952432,0.9958854,0.0017035726,0.00047646035,0.0004965997,0.00009901116],"about_ca_topic_score_codex":0.091854684,"about_ca_topic_score_gemma":0.13868128,"teacher_disagreement_score":0.5649469,"about_ca_system_score_codex":0.000029494577,"about_ca_system_score_gemma":0.002921251,"threshold_uncertainty_score":0.9888918},"labels":[],"label_agreement":null},{"id":"W3039575466","doi":"10.1007/s10479-020-03708-3","title":"Sustainable supply chain for disaster management: structural dynamics and disruptive risks","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Supply chain; Supply chain risk management; Business; Emergency management; Interoperability; Supply chain management; Information sharing; Risk analysis (engineering); Risk management; Process management; System dynamics; Industrial organization; Service management; Computer science; Economics; Marketing; Finance; Economic growth","score_opus":0.14020661080637978,"score_gpt":0.40821713718630587,"score_spread":0.26801052637992606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039575466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9272745,0.0003127664,0.005318474,0.050556295,0.00008115202,0.0031862084,0.00005990908,0.000060852868,0.013149808],"genre_scores_gemma":[0.9937658,0.00016940861,0.0004485122,0.0012233567,0.0003064721,0.00018890986,0.00011967306,0.000022238824,0.0037556866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984049,0.000029528948,0.00025833267,0.00036222287,0.00041454,0.00053042924],"domain_scores_gemma":[0.9989595,0.000071280185,0.000036951235,0.00021167913,0.0006829219,0.000037689195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007170574,0.0001390188,0.00018106341,0.00035727996,0.0006175884,0.00050222623,0.00033179138,0.000044385208,0.00013475437],"category_scores_gemma":[0.0002108453,0.00011727361,0.00006327837,0.00074580923,0.00021166862,0.0010613855,0.00054260326,0.00014326425,0.000027728496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002241909,0.00007402378,0.0066624437,0.0012430329,0.00012029899,0.000026291715,0.0015535051,0.0051428145,0.000036019173,0.94795656,0.0149685135,0.02199228],"study_design_scores_gemma":[0.0013406135,0.00021465136,0.021345742,0.00007234444,0.000054156306,8.4001175e-7,0.083675444,0.847319,0.00017272691,0.011471868,0.033877794,0.00045482023],"about_ca_topic_score_codex":0.00096594705,"about_ca_topic_score_gemma":0.00025783104,"teacher_disagreement_score":0.9364847,"about_ca_system_score_codex":0.000017069002,"about_ca_system_score_gemma":0.000018583742,"threshold_uncertainty_score":0.48429793},"labels":[],"label_agreement":null},{"id":"W3039783047","doi":"10.1007/s10479-020-03699-1","title":"Managing rail-truck intermodal transportation for hazardous materials with random yard disruptions","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Flow network; Hazardous waste; Contingency plan; Transport engineering; Computer science; Operations research; Reliability (semiconductor); Robustness (evolution); Yard; Interdependence; Engineering; Computer security","score_opus":0.40497733431133587,"score_gpt":0.5167435438435632,"score_spread":0.11176620953222738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039783047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72098285,0.00010885569,0.18550214,0.090993725,0.00007536805,0.0009782296,0.0005549712,0.000028560326,0.0007753059],"genre_scores_gemma":[0.9957588,0.00025432408,0.0025531456,0.00023374635,0.00012782846,0.00013666705,0.0001045536,0.000013746709,0.00081722374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967582,0.00042881316,0.00074682647,0.00043057138,0.0013272716,0.00030827956],"domain_scores_gemma":[0.99550146,0.0007239935,0.00006778564,0.00038503527,0.0031571102,0.00016458967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036879738,0.00011002496,0.00038663737,0.0004148101,0.0005519792,0.00042952524,0.00057029934,0.000053159736,0.00066022994],"category_scores_gemma":[0.0024731094,0.00007647222,0.00016445803,0.0013361925,0.00022013452,0.0005411265,0.000031646683,0.00013489569,0.0000942127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016767057,0.0007907425,0.005974988,0.0002894725,0.0014097575,0.00007214355,0.04786692,0.47288147,0.0923527,0.06884239,0.10566843,0.18708393],"study_design_scores_gemma":[0.016820673,0.006062309,0.062433485,0.00038870366,0.00040251503,0.000012504199,0.048721954,0.36684212,0.32530278,0.08579361,0.08522194,0.0019974115],"about_ca_topic_score_codex":0.00018067229,"about_ca_topic_score_gemma":0.00065087026,"teacher_disagreement_score":0.27477592,"about_ca_system_score_codex":0.000007768558,"about_ca_system_score_gemma":0.00014508222,"threshold_uncertainty_score":0.7229055},"labels":[],"label_agreement":null},{"id":"W3042514062","doi":"10.1007/s10479-020-03721-6","title":"A new branch-and-cut approach for the generalized regenerator location problem","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Regenerative heat exchanger; Theory of computation; Benchmark (surveying); Set (abstract data type); Node (physics); Computer science; Integer programming; Mathematical optimization; Path (computing); Network planning and design; Integer (computer science); Mathematics; Algorithm; Computer network; Engineering","score_opus":0.18910986534815194,"score_gpt":0.38546336022224637,"score_spread":0.19635349487409443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042514062","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0085403295,0.0048893397,0.96777594,0.01704847,0.000016903577,0.0010552751,0.00001083192,0.00017100692,0.00049187726],"genre_scores_gemma":[0.65117645,0.0016671898,0.3459875,0.00020050701,0.0002096567,0.0004151746,0.000021880353,0.000030669184,0.00029094936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992182,0.000031595777,0.00017866991,0.00015370632,0.00018550282,0.00023232668],"domain_scores_gemma":[0.99923056,0.00013750006,0.0000063361,0.00020586343,0.00034440425,0.00007535827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002984622,0.00007623021,0.00011648583,0.000053834836,0.00017344378,0.00006227672,0.00022629926,0.000064846405,0.000010153816],"category_scores_gemma":[0.00034710576,0.000056045952,0.0000272345,0.00056662987,0.00010568117,0.00013437787,0.00006401514,0.00019761371,0.0000043479395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019693112,0.000010357345,0.0000073282085,0.0000856418,0.00004026561,1.1367663e-7,0.00023781332,0.88630563,0.009417445,0.053275026,0.023882084,0.026718602],"study_design_scores_gemma":[0.00021926631,0.0000960109,0.000024745317,0.000010158564,0.0000044928724,6.9760193e-7,0.000117373136,0.96015733,0.029576095,0.0013595802,0.00834904,0.00008518494],"about_ca_topic_score_codex":0.000017640354,"about_ca_topic_score_gemma":0.000015834785,"teacher_disagreement_score":0.6426361,"about_ca_system_score_codex":0.000007853754,"about_ca_system_score_gemma":0.000050425668,"threshold_uncertainty_score":0.22854875},"labels":[],"label_agreement":null},{"id":"W3046951078","doi":"10.1007/s10479-020-03743-0","title":"Optimal scheduling of airport ferry vehicles based on capacity network","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Fisheries and Oceans Canada","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Integer programming; Computer science; Scheduling (production processes); Operations research; Linear programming; Flow network; Mathematical optimization; Engineering; Mathematics; Algorithm","score_opus":0.2884538788196349,"score_gpt":0.4198422238996973,"score_spread":0.13138834508006236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046951078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.837126,0.00013191302,0.15674204,0.0029109789,0.000051919124,0.00029197702,0.000026433228,0.00011167574,0.0026070366],"genre_scores_gemma":[0.81707567,0.00003989902,0.1825803,0.00012845758,0.00010754858,0.000014432807,0.0000110425835,0.00002514111,0.000017512253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983434,0.00027643947,0.00037730532,0.0001770205,0.00051339605,0.00031245608],"domain_scores_gemma":[0.99863774,0.00026549087,0.000020247093,0.000267734,0.00067380053,0.00013501408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017557228,0.000101377926,0.00021574204,0.00015228587,0.00015136355,0.0000380147,0.000240369,0.00008659961,0.00010788733],"category_scores_gemma":[0.00087191444,0.00010701907,0.00006817484,0.00088880816,0.00011541977,0.00012754326,0.00004548913,0.00039958814,0.000016360154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022108034,0.000033683245,0.0006309158,0.00007321255,0.000022296681,0.0000013170877,0.00023681563,0.99030644,0.0063519734,0.000702514,0.0009966359,0.00062210707],"study_design_scores_gemma":[0.00014205712,0.0001347562,0.0009954287,0.00005870995,0.0000026596106,2.7075157e-7,0.00006187432,0.9448607,0.053466424,0.000014891422,0.0001791633,0.00008305472],"about_ca_topic_score_codex":0.000027396592,"about_ca_topic_score_gemma":0.0000039120127,"teacher_disagreement_score":0.04711445,"about_ca_system_score_codex":0.000014017549,"about_ca_system_score_gemma":0.00010627781,"threshold_uncertainty_score":0.4364111},"labels":[],"label_agreement":null},{"id":"W3088183368","doi":"10.1007/s10479-020-03786-3","title":"Preface: multiple criteria decision making for sustainable decisions","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Development and Environmental Policy","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; University of Ottawa; Wilfrid Laurier University","funders":"","keywords":"Theory of computation; Management science; Computer science; Operations research; Mathematics; Economics; Algorithm","score_opus":0.20654371739490027,"score_gpt":0.4540070326966883,"score_spread":0.24746331530178803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088183368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9777695,0.00007485224,0.008392942,0.005621481,0.000021202963,0.0012260587,0.000021115626,0.00002448693,0.006848363],"genre_scores_gemma":[0.98356247,0.00008845321,0.013157154,0.0006134778,0.000049977363,0.0001785373,0.00001993768,0.00002070358,0.002309264],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980351,0.00009165708,0.00030973204,0.00035066588,0.0005917959,0.00062104926],"domain_scores_gemma":[0.99888104,0.0005243428,0.000020018608,0.00025343624,0.00013662784,0.0001845507],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010104972,0.00011201825,0.00014938781,0.00011252415,0.00069522933,0.00012540702,0.00041780534,0.00006594145,0.002389427],"category_scores_gemma":[0.0037728464,0.000104172264,0.000068257206,0.0006984914,0.00022037234,0.0005835732,0.0006722005,0.00014189167,0.0002943505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012400122,0.0007628956,0.02277157,0.00015889242,0.0000739689,0.000057927376,0.010930302,0.12384696,0.034421556,0.005788831,0.6952629,0.1046842],"study_design_scores_gemma":[0.0026996455,0.0017053211,0.12968227,0.00016601753,0.000018398778,0.0000072618295,0.027077463,0.23908205,0.055569388,0.016878858,0.52602243,0.0010908743],"about_ca_topic_score_codex":0.00025058814,"about_ca_topic_score_gemma":0.00005827242,"teacher_disagreement_score":0.16924044,"about_ca_system_score_codex":0.00008989879,"about_ca_system_score_gemma":0.00005944141,"threshold_uncertainty_score":0.9985225},"labels":[],"label_agreement":null},{"id":"W3090423329","doi":"10.1007/s10479-022-04771-8","title":"Malmquist productivity indices and plant capacity utilisation: new proposals and empirical application","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Xi’an Jiaotong-Liverpool University","keywords":"Bootstrapping (finance); Productivity; Econometrics; Index (typography); Malmquist index; Rank (graph theory); Economics; Spearman's rank correlation coefficient; Mathematics; Statistics; Total factor productivity; Computer science; Economic growth","score_opus":0.5926169263538534,"score_gpt":0.55466085896995,"score_spread":0.03795606738390345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090423329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9698533,0.0003533698,0.0010618251,0.027607037,0.000027199869,0.00045453344,0.000066550114,0.000012113554,0.00056411355],"genre_scores_gemma":[0.99808455,0.000030912157,0.0006646492,0.00011819996,0.00006093329,0.000066252804,0.000016411475,0.0000052566925,0.0009528597],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99514306,0.0012406724,0.00047997318,0.00059663266,0.0023010604,0.00023859362],"domain_scores_gemma":[0.99754906,0.0007962096,0.00007496716,0.0005624215,0.0008798897,0.00013744118],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.012472627,0.000083813924,0.00021428154,0.0006718297,0.0013531389,0.00033639744,0.00044840446,0.00003763836,0.00023382477],"category_scores_gemma":[0.003993368,0.000067716544,0.000035180416,0.0021284074,0.00055039144,0.00042298535,0.0004493408,0.0003359405,0.000016051203],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005165338,0.0029694363,0.3794247,0.000111519745,0.0002227674,0.000019208972,0.044734307,0.036707368,0.04515988,0.094344355,0.16069065,0.23509929],"study_design_scores_gemma":[0.000850599,0.0015757504,0.37601382,0.000029945251,0.000039520517,0.0001461761,0.010719547,0.3621848,0.028789395,0.053245235,0.16567197,0.0007332632],"about_ca_topic_score_codex":0.0009324999,"about_ca_topic_score_gemma":0.0005846428,"teacher_disagreement_score":0.32547742,"about_ca_system_score_codex":0.000022061913,"about_ca_system_score_gemma":0.0003926732,"threshold_uncertainty_score":0.99994695},"labels":[],"label_agreement":null},{"id":"W3092059796","doi":"10.1007/s10479-020-03804-4","title":"Early box office prediction in China’s film market based on a stacking fusion model","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Gradient boosting; Stacking; Computer science; Random forest; Boosting (machine learning); Artificial intelligence; Box office; Investment (military); Machine learning; Econometrics; Data mining; Economics; Business; Political science","score_opus":0.2255844233831955,"score_gpt":0.3631559994353164,"score_spread":0.1375715760521209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092059796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9164079,0.0004592892,0.002369026,0.023391813,0.00006005742,0.00046750155,0.00039517856,0.000018954965,0.056430314],"genre_scores_gemma":[0.9972493,0.00041604243,0.00034995057,0.00035836583,0.00006137626,0.000057357694,0.0000249527,0.0000115319845,0.0014710897],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892884,0.000046993166,0.000378652,0.0002749853,0.00012611561,0.00024438315],"domain_scores_gemma":[0.99947625,0.00007285716,0.000032137385,0.00018780206,0.00014992958,0.0000810454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010502235,0.00007586449,0.00021037008,0.00040250568,0.0001556659,0.00004874888,0.00013920733,0.000054416854,0.00041268757],"category_scores_gemma":[0.0009639107,0.00008187833,0.000049999973,0.0005588116,0.00004869484,0.00017797551,0.000064834734,0.00025525576,0.00009787609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008822155,0.0009838091,0.054757994,0.00021953679,0.00007184441,0.000013901237,0.012070429,0.768771,0.0011458833,0.033549685,0.12501872,0.002514965],"study_design_scores_gemma":[0.00038652867,0.00029551884,0.10735017,0.00003401978,7.036373e-7,7.4409236e-8,0.00013335972,0.88896656,0.00026939003,0.0002671945,0.0022258821,0.000070592345],"about_ca_topic_score_codex":0.0005455289,"about_ca_topic_score_gemma":0.00013730739,"teacher_disagreement_score":0.12279283,"about_ca_system_score_codex":0.000024111525,"about_ca_system_score_gemma":0.0000678246,"threshold_uncertainty_score":0.45186397},"labels":[],"label_agreement":null},{"id":"W3093320459","doi":"10.1007/s10479-020-03813-3","title":"A multi-objective distributionally robust model for sustainable last mile relief network design problem","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Ambiguity; Computer science; Mile; Operations research; Natural disaster; Mathematical optimization; Emergency management; Network planning and design; Set (abstract data type); Economics; Mathematics; Geography","score_opus":0.31121544282338576,"score_gpt":0.3813135937394925,"score_spread":0.07009815091610672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093320459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002922722,0.00014059173,0.9671536,0.02500885,0.000030202355,0.0025385676,0.000035300985,0.00007040027,0.0020997315],"genre_scores_gemma":[0.94308305,0.00010669968,0.043852247,0.002601552,0.00058782496,0.0012856071,0.0005344074,0.000038324706,0.0079103075],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982233,0.0000536229,0.00036939804,0.00035410028,0.0004491536,0.0005504301],"domain_scores_gemma":[0.9958248,0.00005279827,0.00002474181,0.0002130781,0.0038457671,0.00003882643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018943552,0.00012665335,0.00016972313,0.00016648417,0.0007754712,0.00027578723,0.00033791337,0.000054603057,0.00016026117],"category_scores_gemma":[0.0010831172,0.00012501671,0.000086503125,0.0011504295,0.000093307135,0.0009719737,0.00026332677,0.00016122613,0.000115778115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091355054,0.0001648926,0.000040197403,0.00022392375,0.00003183099,8.1205627e-7,0.0001403414,0.7816539,0.00007014153,0.06670995,0.1507371,0.00013558951],"study_design_scores_gemma":[0.00035215402,0.00005345007,0.00020787268,0.000019266869,0.000009182118,5.7056166e-8,0.00076465256,0.9804869,0.000069039444,0.0014128636,0.01649627,0.00012828436],"about_ca_topic_score_codex":0.00090397714,"about_ca_topic_score_gemma":0.0006530719,"teacher_disagreement_score":0.94016033,"about_ca_system_score_codex":0.00003102043,"about_ca_system_score_gemma":0.00019483906,"threshold_uncertainty_score":0.59643763},"labels":[],"label_agreement":null},{"id":"W3110436430","doi":"10.1007/s10479-020-03886-0","title":"Stochastic efficiency and inefficiency in portfolio optimization with incomplete information: a set-valued probability approach","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Inefficiency; Complete information; Theory of computation; Set (abstract data type); Mathematical optimization; Portfolio; Portfolio optimization; Probability measure; Computer science; Metric (unit); Mathematics; Mathematical economics; Algorithm; Economics; Statistics","score_opus":0.371803939000855,"score_gpt":0.45643776027668737,"score_spread":0.08463382127583235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110436430","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27872503,0.00010309307,0.7124015,0.0032261084,0.000018448784,0.0012884845,0.000042539104,0.000024297933,0.004170496],"genre_scores_gemma":[0.98071426,0.00008277518,0.01879698,0.00018480935,0.00002443731,0.00007490104,0.00007342652,0.000007766499,0.00004065603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958831,0.0005082729,0.0009640141,0.00042789624,0.0018753062,0.00034139468],"domain_scores_gemma":[0.9964521,0.00029551072,0.0001136005,0.00042036106,0.0025162934,0.0002021486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005013256,0.00013870896,0.00030274366,0.0008405013,0.00032484252,0.0004055116,0.00049211294,0.00008050983,0.000122012614],"category_scores_gemma":[0.004738226,0.00010107925,0.00003517681,0.004921002,0.00038069513,0.0015539208,0.00017999299,0.00028165738,0.000021255673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096563286,0.000106876185,0.0017550293,0.000012283701,0.0000041340836,8.243488e-7,0.0033466583,0.98897016,0.000009658388,0.0035565093,0.00038111937,0.0017602069],"study_design_scores_gemma":[0.00041449175,0.00037592623,0.0032510299,0.000014005957,0.0000023310947,0.000005283527,0.0013561879,0.99387324,0.00004518278,0.00034553022,0.00019951205,0.00011727828],"about_ca_topic_score_codex":0.00019773046,"about_ca_topic_score_gemma":0.000043482443,"teacher_disagreement_score":0.70198923,"about_ca_system_score_codex":0.00001759165,"about_ca_system_score_gemma":0.0004615157,"threshold_uncertainty_score":0.5672441},"labels":[],"label_agreement":null},{"id":"W3116607398","doi":"10.1007/s10479-020-03843-x","title":"Decision-based scenario clustering for decision-making under uncertainty","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Computer science; Theory of computation; Cluster analysis; Context (archaeology); Graph; Decision maker; Operations research; Machine learning; Mathematics; Theoretical computer science; Algorithm","score_opus":0.15333997407954997,"score_gpt":0.43286781790440215,"score_spread":0.2795278438248522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116607398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23981561,0.0005349513,0.71999943,0.027818494,0.00059290335,0.002198852,0.00002453534,0.00011466374,0.008900562],"genre_scores_gemma":[0.9812956,0.0000186773,0.014564142,0.0024730563,0.00041580317,0.0001948116,0.00005802773,0.000041163912,0.0009387325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974205,0.0000548217,0.00047584262,0.00047532315,0.00093992177,0.00063361024],"domain_scores_gemma":[0.9930551,0.0014889423,0.00005089506,0.0006530098,0.0047255903,0.000026439055],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00286672,0.00015900197,0.0002397726,0.0009240793,0.0009441355,0.0009038466,0.00048955117,0.00007982418,0.0009207202],"category_scores_gemma":[0.006267731,0.00015501466,0.00015193147,0.001743778,0.00011035876,0.00073457253,0.0006027382,0.0002050491,0.00008451747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016060087,0.0001865781,0.00025715865,0.00023051444,0.00004332903,0.000027251059,0.000052435676,0.90908796,0.00014575727,0.02225646,0.018465396,0.049086533],"study_design_scores_gemma":[0.00063396204,0.000032595224,0.00085887936,0.00048234,0.000015229227,8.1249095e-7,0.004386266,0.9147187,0.00019356703,0.018913887,0.05951824,0.00024553522],"about_ca_topic_score_codex":0.00035456193,"about_ca_topic_score_gemma":0.0026720949,"teacher_disagreement_score":0.74148,"about_ca_system_score_codex":0.00008320695,"about_ca_system_score_gemma":0.00038568283,"threshold_uncertainty_score":0.99999255},"labels":[],"label_agreement":null},{"id":"W3119909670","doi":"10.1007/s10479-020-03871-7","title":"Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Pandemic; Reinforcement learning; Computer science; Coronavirus disease 2019 (COVID-19); Artificial intelligence; Dominance (genetics); Operations research; Machine learning; Mathematics; Medicine; Infectious disease (medical specialty)","score_opus":0.5094805475649316,"score_gpt":0.5179004433015533,"score_spread":0.008419895736621719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119909670","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31468958,0.00030509493,0.6721646,0.011075578,0.000011874249,0.001415169,0.000016126745,0.000032802913,0.00028917534],"genre_scores_gemma":[0.9917935,0.00016737782,0.006963104,0.0003119796,0.000013447744,0.0003604238,0.00002017978,0.000008237163,0.0003617282],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973591,0.0011450022,0.00052223227,0.00024185794,0.0004888922,0.000242933],"domain_scores_gemma":[0.9962699,0.002743102,0.00007268716,0.0002975533,0.0005662053,0.00005059597],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00462105,0.000081846774,0.0002410691,0.00018912287,0.00020468752,0.00001873986,0.00017239877,0.00005019519,0.000033978493],"category_scores_gemma":[0.012074993,0.000056733414,0.000043812455,0.000958915,0.00018036657,0.00009293568,0.00013413622,0.00039471927,0.0000013694291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089019566,0.00034798397,0.18068306,0.00031147662,0.000044945304,0.0000088088955,0.0019040881,0.7968555,0.006729606,0.004275776,0.00081570365,0.00793405],"study_design_scores_gemma":[0.001652542,0.00042229277,0.03106606,0.0004288506,0.000014886258,0.0000063610964,0.002873207,0.927181,0.025946805,0.0075693345,0.0026379349,0.00020071799],"about_ca_topic_score_codex":0.016643673,"about_ca_topic_score_gemma":0.02773248,"teacher_disagreement_score":0.67710394,"about_ca_system_score_codex":0.00020761992,"about_ca_system_score_gemma":0.0007575557,"threshold_uncertainty_score":0.9962467},"labels":[],"label_agreement":null},{"id":"W3121781925","doi":"10.1007/s10479-025-06862-8","title":"Asset classes and portfolio diversification: evidence from a stochastic spanning approach","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Grantová Agentura České Republiky; Egg Farmers of Canada","keywords":"Portfolio; Diversification (marketing strategy); Sharpe ratio; Post-modern portfolio theory; Portfolio insurance; Financial economics; Capital asset pricing model; Real estate; Asset allocation; Bond; Economics; Econometrics; Parametric statistics; Asset (computer security); Stock (firearms); Portfolio optimization; Replicating portfolio; Business; Computer science; Finance; Mathematics; Geography","score_opus":0.3658973618812557,"score_gpt":0.407215683274081,"score_spread":0.041318321392825264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121781925","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8765622,0.017952379,0.01814781,0.007842436,0.00013596247,0.00058448955,0.00023645216,0.000023739847,0.07851456],"genre_scores_gemma":[0.995171,0.0016897755,0.0013124776,0.00012312343,0.000034331708,0.000052870826,0.000030109119,0.000004957965,0.0015813722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990316,0.000044869816,0.00034258937,0.00030990326,0.000074475465,0.0001965431],"domain_scores_gemma":[0.999199,0.00020451579,0.000043753556,0.00026921203,0.00023969784,0.000043835997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010001797,0.00007446463,0.00020030703,0.00039388018,0.0003070124,0.00019657938,0.0002064705,0.00006091347,0.0001410226],"category_scores_gemma":[0.00085492636,0.00008032912,0.000034989433,0.0005304806,0.00021046348,0.0005135127,0.000117326286,0.00015560063,0.000027905173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032460597,0.00013279427,0.01696588,0.000054084332,0.00006569922,9.449128e-7,0.00055021426,0.0016611901,0.00018537563,0.9617193,0.017885463,0.00074663665],"study_design_scores_gemma":[0.0005326224,0.00031089867,0.78756964,0.00044861293,0.000013341403,0.0000011409724,0.0024771357,0.082664885,0.0007567909,0.11107035,0.013732734,0.00042186351],"about_ca_topic_score_codex":0.002050321,"about_ca_topic_score_gemma":0.000039930484,"teacher_disagreement_score":0.8506489,"about_ca_system_score_codex":0.000017166925,"about_ca_system_score_gemma":0.000103003855,"threshold_uncertainty_score":0.32757264},"labels":[],"label_agreement":null},{"id":"W3124698695","doi":"10.1007/s10479-017-2474-7","title":"The impact of covariance misspecification in risk-based portfolios","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Covariance matrix; Portfolio; Econometrics; Diversification (marketing strategy); Volatility (finance); Mathematics; Covariance; Portfolio optimization; Inverse; Variance (accounting); Statistics; Economics; Financial economics","score_opus":0.4412080252485119,"score_gpt":0.4870787279534551,"score_spread":0.0458707027049432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124698695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894399,0.0011626675,0.0029652778,0.0016233707,0.000033933455,0.0002594306,0.00014781117,0.0000025559204,0.004365063],"genre_scores_gemma":[0.9975534,0.0017879814,0.00037912236,0.00000429196,0.000028010463,0.000023840961,0.00000656298,0.0000065745494,0.0002101864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99893993,0.000059182094,0.0005307619,0.00017746656,0.00007585707,0.00021679206],"domain_scores_gemma":[0.99842596,0.00014407853,0.0001832133,0.0007842218,0.0004276597,0.00003489203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038953947,0.000055258377,0.0001819395,0.00021925167,0.00064711523,0.00012258747,0.00046317358,0.000055414705,0.00005577316],"category_scores_gemma":[0.0029416187,0.000047414396,0.000094226416,0.00021293308,0.00020927358,0.00023169738,0.000042409505,0.00020759081,0.000031456893],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019154149,0.00042463918,0.59094745,0.000024007797,0.000043015578,0.0000012318106,0.00068479014,0.11517528,0.00044244507,0.2808568,0.0016250852,0.009583737],"study_design_scores_gemma":[0.0002025516,0.000089459834,0.687597,0.000018701066,3.7719468e-7,6.979823e-8,0.000027644115,0.29731297,0.00096624537,0.013079125,0.0006528291,0.0000530528],"about_ca_topic_score_codex":0.016405536,"about_ca_topic_score_gemma":0.0009577459,"teacher_disagreement_score":0.26777765,"about_ca_system_score_codex":0.00002816758,"about_ca_system_score_gemma":0.00015766393,"threshold_uncertainty_score":0.9901443},"labels":[],"label_agreement":null},{"id":"W3126046128","doi":"10.1007/s10479-017-2725-7","title":"Negative dependence in matrix arrangement problems","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Eidgenössische Technische Hochschule Zürich; Swiss Finance Institute","keywords":"Theory of computation; Mathematical optimization; Maximization; Computer science; Minification; Matrix (chemical analysis); Scheduling (production processes); Mathematics; Algorithm","score_opus":0.2819698716354554,"score_gpt":0.49960532239658373,"score_spread":0.21763545076112834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126046128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9139485,0.0005877567,0.04679272,0.0050723,0.00017655356,0.0013538122,0.000030889903,0.00011140183,0.03192608],"genre_scores_gemma":[0.97104543,0.00038106524,0.027827764,0.000007918999,0.000027967188,0.000078097175,0.000002724252,0.000015169343,0.00061387644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998866,0.00016276432,0.00023148757,0.00013318933,0.00034408597,0.00026246946],"domain_scores_gemma":[0.9989236,0.00010704354,0.000015107032,0.00045860198,0.00044476683,0.000050901028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020995338,0.00006519233,0.000114917835,0.00023689706,0.00028716834,0.00016812255,0.0003936951,0.000048697628,0.000104280734],"category_scores_gemma":[0.0009796474,0.000066594745,0.000022840846,0.00022151353,0.00010528726,0.00036812818,0.00009280262,0.0002480221,0.000036622416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036621664,0.0000324533,0.0017955967,0.00004547051,0.000013388247,0.000002495419,0.000838235,0.98625743,0.005358641,0.0015984038,0.0003762782,0.0036779277],"study_design_scores_gemma":[0.00029743035,0.000054524455,0.018136598,0.00012019197,0.0000013203115,0.0000010393364,0.00022946084,0.92419845,0.055701613,0.0006235642,0.0005076228,0.00012818218],"about_ca_topic_score_codex":0.0003947052,"about_ca_topic_score_gemma":0.00067730126,"teacher_disagreement_score":0.062058996,"about_ca_system_score_codex":0.000024126854,"about_ca_system_score_gemma":0.000050339553,"threshold_uncertainty_score":0.2715655},"labels":[],"label_agreement":null},{"id":"W3127734891","doi":"10.1007/s10479-021-03945-0","title":"Disclosure of quality preference-revealing information in a supply chain with competitive products","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Supply chain; Business; Quality (philosophy); Incentive; Upstream (networking); Downstream (manufacturing); Preference; Product (mathematics); Industrial organization; Information quality; Marketing; Microeconomics; Computer science; Economics; Information system","score_opus":0.23998252262428793,"score_gpt":0.38696439698909657,"score_spread":0.14698187436480864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127734891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95588326,0.00009915411,0.00013376154,0.013748714,0.000043993587,0.00064295356,0.000022354387,0.000013423577,0.029412376],"genre_scores_gemma":[0.9984383,0.000058181464,0.00025622497,0.00035640772,0.00008437982,0.00006537254,0.00022245437,0.0000062581285,0.0005124003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9984521,0.00011578604,0.00042744877,0.00016765857,0.00060582004,0.00023113261],"domain_scores_gemma":[0.99719995,0.00005280941,0.000070736955,0.0002813818,0.0023843732,0.00001074668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019467637,0.00008369459,0.00018834896,0.00048252527,0.00011455167,0.0001530552,0.0001795853,0.000032331107,0.00022754639],"category_scores_gemma":[0.0007000456,0.00007111159,0.000028321463,0.0013961969,0.00012095178,0.001565562,0.00017536698,0.00016146444,0.000025415671],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024273217,0.00088256976,0.04100311,0.0023011384,0.00010199583,0.000010129922,0.0029196264,0.01184643,0.0031772628,0.9271034,0.005769936,0.00464165],"study_design_scores_gemma":[0.005427044,0.0005026581,0.60646343,0.0032856842,0.000050109706,0.000003539449,0.08254212,0.04039587,0.097589076,0.0058040577,0.1566244,0.0013119786],"about_ca_topic_score_codex":0.0017701987,"about_ca_topic_score_gemma":0.0020707666,"teacher_disagreement_score":0.92129934,"about_ca_system_score_codex":0.000014827099,"about_ca_system_score_gemma":0.00014890956,"threshold_uncertainty_score":0.28998467},"labels":[],"label_agreement":null},{"id":"W3135374780","doi":"10.1007/s10479-021-03983-8","title":"A collective investment problem in a stochastic volatility environment: The impact of sharing rules","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Actua","funders":"Deutsche Forschungsgemeinschaft","keywords":"Volatility (finance); Delegate; Economics; Pension; Financial market; Stochastic volatility; Investment (military); Microeconomics; Investment strategy; Financial economics; Finance; Computer science","score_opus":0.21118872137209588,"score_gpt":0.38888529789255827,"score_spread":0.1776965765204624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135374780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87762314,0.0038805783,0.10297605,0.0018567033,0.000012800764,0.0011164857,0.0006084026,0.0000057878246,0.011920066],"genre_scores_gemma":[0.9983337,0.000085796564,0.00092720275,0.000022187884,0.000013787068,0.000292824,0.000017231776,0.000007008032,0.00030028692],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989645,0.000019712625,0.00046608647,0.00025710097,0.00007846394,0.00021412256],"domain_scores_gemma":[0.9991914,0.00013139055,0.000063251544,0.00033833683,0.00023521377,0.000040382223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096441736,0.00006774786,0.000215085,0.0001952448,0.00017141226,0.00003853606,0.00022173871,0.00004247183,0.0001513762],"category_scores_gemma":[0.00048769708,0.000059196387,0.00007819177,0.00074669946,0.00016066917,0.0001050194,0.00015277864,0.0001731514,0.00003187905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024297731,0.0005595826,0.003920063,0.000024929865,0.0000593054,7.6452153e-7,0.00323732,0.031368725,0.00029829476,0.9601182,0.00008953967,0.00029897783],"study_design_scores_gemma":[0.0002990143,0.0001876671,0.10793234,0.000043012446,0.000001997548,0.0000016875383,0.0002994441,0.12281749,0.0005465057,0.7676704,0.00009452678,0.0001059236],"about_ca_topic_score_codex":0.0019788502,"about_ca_topic_score_gemma":0.00013395865,"teacher_disagreement_score":0.1924478,"about_ca_system_score_codex":0.0001144074,"about_ca_system_score_gemma":0.0003784614,"threshold_uncertainty_score":0.2991443},"labels":[],"label_agreement":null},{"id":"W314897481","doi":"10.1007/s10479-015-1881-x","title":"Units invariant DEA when weight restrictions are present: ecological performance of US electricity industry","year":2015,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Concern Foundation; Tongji University; National Science Foundation","keywords":"Data envelopment analysis; Electricity; Theory of computation; Environmental economics; A priori and a posteriori; Invariant (physics); Ecological efficiency; Computer science; Operations research; Environmental science; Econometrics; Mathematical optimization; Economics; Mathematics; Ecology; Engineering","score_opus":0.5686259960029576,"score_gpt":0.5056468731964749,"score_spread":0.06297912280648266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W314897481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868298,0.00026418376,0.0003129774,0.0063609956,0.00006379083,0.00028909073,0.00003417328,0.000015128018,0.0058298423],"genre_scores_gemma":[0.9962473,0.000116992356,0.00040814248,0.000082880266,0.000086805274,0.000029332004,0.00000880714,0.00000778924,0.0030119377],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99301165,0.0016585839,0.0010060844,0.00047913403,0.003343515,0.000501019],"domain_scores_gemma":[0.98613685,0.001552578,0.00017388843,0.00096634286,0.010887403,0.00028291467],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.011695314,0.00012675881,0.00038696796,0.0015405715,0.00055805343,0.00021707195,0.0013885027,0.00029409982,0.00041477339],"category_scores_gemma":[0.02315962,0.0000927179,0.000086899505,0.008241785,0.00051254337,0.00062442926,0.00038812272,0.000950512,0.00014298201],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025032225,0.0031027878,0.3943436,0.000028430219,0.00017667416,0.000040901257,0.0029616628,0.3455443,0.002933982,0.011832611,0.23276877,0.006015937],"study_design_scores_gemma":[0.0008067453,0.0017306608,0.46855035,0.00011195297,0.000035104284,0.00002306151,0.0020760405,0.452089,0.04544033,0.004747209,0.023976061,0.00041347093],"about_ca_topic_score_codex":0.0011588171,"about_ca_topic_score_gemma":0.0005531736,"teacher_disagreement_score":0.2087927,"about_ca_system_score_codex":0.000050539766,"about_ca_system_score_gemma":0.0012479536,"threshold_uncertainty_score":0.98506874},"labels":[],"label_agreement":null},{"id":"W3183082635","doi":"10.1007/s10479-021-04114-z","title":"Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Undersampling; Computer science; Oversampling; Machine learning; Artificial intelligence; Support vector machine; Artificial neural network; Resampling; Algorithm; Statistical classification; Data mining","score_opus":0.19784569491076648,"score_gpt":0.4008726326045339,"score_spread":0.2030269376937674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183082635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86308616,0.00064653927,0.13305777,0.0014472257,0.00038473267,0.00041284642,0.00010057003,0.00006905828,0.0007950977],"genre_scores_gemma":[0.996613,0.0002675652,0.0009824979,0.000116477444,0.0015137289,0.000032332668,0.00042853554,0.00001698726,0.000028870028],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984691,0.00013378379,0.00034535347,0.00034643282,0.00040391125,0.0003013922],"domain_scores_gemma":[0.9969287,0.00008206097,0.000074228206,0.00026829698,0.0026163259,0.000030425756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008142991,0.00011806264,0.0001638265,0.00024693488,0.0008360209,0.0006601992,0.00015579975,0.00010808376,0.00015961214],"category_scores_gemma":[0.00090096,0.00011235673,0.000047221092,0.0010840269,0.00020516648,0.0018437175,0.00014483677,0.00038238039,0.000007209168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022425062,0.0009015417,0.0069957916,0.000084887455,0.00010921395,0.000040388186,0.00029147448,0.1249395,0.002823588,0.039595813,0.001893274,0.8221003],"study_design_scores_gemma":[0.00012434939,0.00004326526,0.03327008,0.000026725835,0.000020276864,0.000002422606,0.0011232928,0.962969,0.00024386593,0.0007401445,0.0013352267,0.00010135829],"about_ca_topic_score_codex":0.0019234932,"about_ca_topic_score_gemma":0.00091577106,"teacher_disagreement_score":0.8380295,"about_ca_system_score_codex":0.000015927908,"about_ca_system_score_gemma":0.00008758242,"threshold_uncertainty_score":0.6430082},"labels":[],"label_agreement":null},{"id":"W3184121575","doi":"10.1007/s10479-021-04185-y","title":"The benefit of manufacturer encroachment considering consumer’s environmental awareness and product competition","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Competition (biology); Product (mathematics); Theory of computation; Business; Industrial organization; Computer science; Environmental economics; Commerce; Economics; Mathematics; Ecology","score_opus":0.09864746607738467,"score_gpt":0.3500846095302755,"score_spread":0.2514371434528908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184121575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98455566,0.0017512348,0.00008850915,0.010490748,0.00007102095,0.0005340354,0.000011357222,0.000011377177,0.0024860646],"genre_scores_gemma":[0.99769956,0.0007467727,0.00013149965,0.00020601209,0.00009334098,0.000060212435,0.00006234956,0.000011651139,0.0009886095],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986314,0.000055428885,0.0002816227,0.00024926095,0.00050245435,0.00027981735],"domain_scores_gemma":[0.9989609,0.00013930874,0.000045845496,0.00035594933,0.00048447467,0.00001353128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011820982,0.00009518717,0.0001410293,0.00019454076,0.0006583769,0.00026783365,0.00016362961,0.00002492819,0.00025605084],"category_scores_gemma":[0.0002412971,0.00007790523,0.00003700923,0.00027962495,0.00034318506,0.00039305983,0.00046846163,0.00012789159,0.0000151046925],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021988078,0.0014270454,0.10544384,0.0024087643,0.00074395025,0.00013113515,0.001383958,0.032894526,0.042199317,0.7411956,0.017874362,0.054077595],"study_design_scores_gemma":[0.0019333599,0.000109901295,0.17190766,0.0003449293,0.00010500513,0.00002027871,0.046336472,0.021062087,0.25250635,0.019415889,0.48541403,0.00084403803],"about_ca_topic_score_codex":0.00061778986,"about_ca_topic_score_gemma":0.00033178783,"teacher_disagreement_score":0.7217797,"about_ca_system_score_codex":0.000020113093,"about_ca_system_score_gemma":0.000059940572,"threshold_uncertainty_score":0.5063769},"labels":[],"label_agreement":null},{"id":"W3185611158","doi":"10.1007/s10479-021-04202-0","title":"Multi-echelon fulfillment warehouse rent and production allocation for online direct selling","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Renting; Warehouse; Computer science; Solver; Operations research; Interdependence; Profit (economics); Business; Integer programming; Production (economics); Marketing; Economics; Microeconomics","score_opus":0.37888953100476397,"score_gpt":0.4353396041343588,"score_spread":0.056450073129594824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185611158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92374194,0.002353567,0.0060603125,0.062828064,0.00065306365,0.0024814992,0.000032641066,0.0001273094,0.0017215895],"genre_scores_gemma":[0.98263407,0.00204505,0.006579009,0.00081956934,0.0009005331,0.00026325893,0.0005137605,0.000033119923,0.006211605],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987621,0.000047374528,0.00026985887,0.00033301744,0.000348139,0.00023953931],"domain_scores_gemma":[0.9980091,0.000043800585,0.000035486537,0.0002623632,0.001631714,0.000017530776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014082147,0.00009247241,0.00013083927,0.00032379103,0.00037054348,0.00021988325,0.00010703463,0.000039380622,0.00007762081],"category_scores_gemma":[0.0007578393,0.00008946422,0.00004616568,0.0005162999,0.00006010896,0.00056802825,0.00013879481,0.00010169918,0.000016243557],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005170316,0.009750468,0.005323207,0.0053838897,0.0008045299,0.00002645893,0.0029261264,0.14809233,0.23485003,0.057996277,0.2662461,0.26808354],"study_design_scores_gemma":[0.0011738477,0.000117619435,0.005373679,0.00032858673,0.000053478445,0.0000017574711,0.003677216,0.38175064,0.08338753,0.0008408155,0.52285117,0.00044364727],"about_ca_topic_score_codex":0.00026536576,"about_ca_topic_score_gemma":0.0006197086,"teacher_disagreement_score":0.26763988,"about_ca_system_score_codex":0.000021484799,"about_ca_system_score_gemma":0.00004696769,"threshold_uncertainty_score":0.3648245},"labels":[],"label_agreement":null},{"id":"W3191852971","doi":"10.1007/s10479-022-04947-2","title":"A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sports Performance and Training","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Western Sydney University","keywords":"Computer science; Work (physics); Balance (ability); Energy balance; Predictive modelling; Experimental data; Econometrics; Statistics; Machine learning; Mathematics; Engineering; Physical medicine and rehabilitation","score_opus":0.26557756007436406,"score_gpt":0.4259751696559553,"score_spread":0.16039760958159122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191852971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915465,0.0005250919,0.0030787291,0.0021796112,0.000084196465,0.0009394148,0.00014028838,0.000031664436,0.0014744693],"genre_scores_gemma":[0.9922821,0.00058895577,0.0033767489,0.00041384832,0.000119638156,0.00078369584,0.00027307487,0.000032308155,0.0021296619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981106,0.000019714786,0.00043319995,0.00030536175,0.00070919236,0.00042190906],"domain_scores_gemma":[0.99873686,0.00007627613,0.000038641614,0.00042907658,0.0006005156,0.00011861513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009889245,0.0001140871,0.00028336738,0.00031999883,0.00044885324,0.000041737316,0.00021621695,0.00005198596,0.000120134435],"category_scores_gemma":[0.00011116451,0.00010438579,0.00012507373,0.00043975876,0.000081498445,0.0002931996,0.0001875902,0.0004733135,0.000005134262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009968348,0.0004802404,0.0060370946,0.0000664027,0.00008391242,0.000009187269,0.004043139,0.9613404,0.001289254,0.00014290471,0.0038525173,0.021658076],"study_design_scores_gemma":[0.0006978113,0.0007652398,0.0026540116,0.00026870696,0.000024413785,0.000004787152,0.0014131728,0.9901978,0.0028016411,0.0006112459,0.00044976897,0.00011143294],"about_ca_topic_score_codex":0.00013722735,"about_ca_topic_score_gemma":0.000013037977,"teacher_disagreement_score":0.028857332,"about_ca_system_score_codex":0.00005577662,"about_ca_system_score_gemma":0.00028092792,"threshold_uncertainty_score":0.42567292},"labels":[],"label_agreement":null},{"id":"W3200189330","doi":"10.1007/s10479-021-04310-x","title":"The linearization problem of a binary quadratic problem and its applications","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Linearization; Mathematics; Bounding overwatch; Quadratic equation; Upper and lower bounds; Quadratic function; Quadratic programming; Mathematical optimization; Nonlinear system; Computer science; Mathematical analysis","score_opus":0.12424349566759454,"score_gpt":0.39427121713691393,"score_spread":0.2700277214693194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200189330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3926018,0.10008007,0.21485434,0.0768369,0.0004335843,0.018642668,0.0006527063,0.0011097076,0.19478823],"genre_scores_gemma":[0.9825804,0.0070620477,0.007925372,0.000022494936,0.000031515792,0.00030464918,0.000072962604,0.000023089047,0.001977445],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990319,0.00012212644,0.000308894,0.00011771693,0.00025051885,0.00016887112],"domain_scores_gemma":[0.9982215,0.00018627191,0.000016933769,0.00020621154,0.0013192963,0.000049750164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006494521,0.00006359022,0.000101807374,0.00011608409,0.00029930184,0.000091044094,0.000116479,0.00005125157,0.000039219718],"category_scores_gemma":[0.00010479227,0.00005281261,0.000023715385,0.0008609913,0.00008247365,0.00014595623,0.000051957777,0.0001541023,0.000010842159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006223484,0.00012512943,0.00010194236,0.00050031015,0.000069797854,8.1144185e-7,0.0011649878,0.8367328,0.051635895,0.10135517,0.0019116206,0.006395283],"study_design_scores_gemma":[0.0002635527,0.00012338028,0.00027770485,0.0001595685,0.000009635222,0.0000070477367,0.00047447623,0.89401263,0.07891929,0.0018764847,0.023710685,0.00016554813],"about_ca_topic_score_codex":0.000011340323,"about_ca_topic_score_gemma":0.000066368164,"teacher_disagreement_score":0.58997864,"about_ca_system_score_codex":0.0000062522963,"about_ca_system_score_gemma":0.00012896518,"threshold_uncertainty_score":0.23020181},"labels":[],"label_agreement":null},{"id":"W3206010544","doi":"10.1007/s10479-021-04317-4","title":"Equilibrium reinsurance-investment strategies with partial information and common shock dependence","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Higher Education Discipline Innovation Project; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Reinsurance; Theory of computation; Shock (circulatory); Complete information; Bellman equation; Mathematical economics; Economics; Investment strategy; Mathematical optimization; Investment (military); Partial equilibrium; Computer science; Mathematics; General equilibrium theory; Microeconomics; Actuarial science","score_opus":0.1302855867825303,"score_gpt":0.35447690881632116,"score_spread":0.22419132203379086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206010544","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.954637,0.0015913713,0.0017214265,0.00281081,0.000056800498,0.00028435708,0.000089677094,0.000011934662,0.038796645],"genre_scores_gemma":[0.9967764,0.0016492495,0.0006694743,0.000275971,0.000032708915,0.000058791284,0.00004062095,0.0000062500394,0.0004905555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9989433,0.000041412346,0.0004258734,0.00019059873,0.00013330039,0.00026545997],"domain_scores_gemma":[0.9991932,0.000031381096,0.000054675285,0.00028730617,0.00037812997,0.000055296307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082374405,0.00007973524,0.00020196289,0.0001876106,0.00017312793,0.00029018262,0.00013017663,0.000047831512,0.00008058083],"category_scores_gemma":[0.0001015749,0.000080952785,0.000028687129,0.00042668314,0.0001363672,0.0014004239,0.000096524986,0.00015686697,0.00009006877],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004897656,0.00008848633,0.0127302455,0.00007708116,0.00003575937,0.000009963351,0.0008479562,0.006213011,0.00011279652,0.9771564,0.00067241414,0.0020068793],"study_design_scores_gemma":[0.0033735798,0.0025425886,0.42727432,0.000486372,0.00001665908,0.00004049293,0.009054166,0.062227547,0.054474507,0.10904108,0.330005,0.001463686],"about_ca_topic_score_codex":0.00086260407,"about_ca_topic_score_gemma":0.00055128784,"teacher_disagreement_score":0.86811537,"about_ca_system_score_codex":0.000016480402,"about_ca_system_score_gemma":0.00013232669,"threshold_uncertainty_score":0.33011588},"labels":[],"label_agreement":null},{"id":"W3208326940","doi":"10.1007/s10479-021-04284-w","title":"Green channel coordination under asymmetric information","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Greening; Information asymmetry; Incentive; Business; Product (mathematics); Supply chain; Industrial organization; Channel coordination; Microeconomics; Economics; Marketing; Supply chain management; Finance","score_opus":0.20046134866448112,"score_gpt":0.3828892129875882,"score_spread":0.1824278643231071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208326940","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2193156,0.0006898934,0.01100482,0.15158503,0.00086953986,0.0015013168,0.000026176136,0.00017769748,0.61482996],"genre_scores_gemma":[0.9910725,0.000061005197,0.00006656788,0.0030539788,0.00031862926,0.00004884302,0.0002514712,0.000008862633,0.0051181493],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99864745,0.000044798413,0.00028159935,0.0001378144,0.0006362808,0.000252059],"domain_scores_gemma":[0.99714726,0.00004093808,0.000037306447,0.0002527723,0.0025067704,0.000014937551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012370701,0.00007646753,0.000105735475,0.0011170539,0.0003171641,0.0004056652,0.00019542481,0.000046888214,0.00057094824],"category_scores_gemma":[0.00048752307,0.00007628671,0.000054251752,0.002373725,0.00005729023,0.0027473213,0.0002364064,0.000133548,0.00065886736],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026474056,0.0003793822,0.0005450263,0.00036324016,0.000095228126,0.0000066672037,0.00026407331,0.015658673,0.00051426375,0.72808546,0.2222322,0.031829316],"study_design_scores_gemma":[0.0011981174,0.00009104115,0.019348426,0.00011322034,0.000025997744,0.000002473894,0.0073759784,0.20678239,0.005445709,0.018329296,0.74081445,0.00047292837],"about_ca_topic_score_codex":0.0014272803,"about_ca_topic_score_gemma":0.0002584833,"teacher_disagreement_score":0.7717569,"about_ca_system_score_codex":0.000020561782,"about_ca_system_score_gemma":0.00006450091,"threshold_uncertainty_score":0.8468627},"labels":[],"label_agreement":null},{"id":"W3215588167","doi":"10.1007/s10479-021-04353-0","title":"The high-frequency impact of macroeconomic news on jumps and co-jumps in the cryptocurrency markets","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Brock University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Cryptocurrency; Liberian dollar; Economics; Unemployment rate; Jump; Monetary economics; Us dollar; Price formation; Currency; Unemployment; Finance; Macroeconomics; Computer science","score_opus":0.0985957829309655,"score_gpt":0.43864422788552027,"score_spread":0.3400484449545548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215588167","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9710528,0.0011310161,0.0006407082,0.025122857,0.000019988862,0.00035035276,0.000024883757,0.000009893711,0.0016474971],"genre_scores_gemma":[0.9970446,0.0018909485,0.0007896519,0.000085083746,0.000013817661,0.000110516376,0.0000055336827,0.000003424468,0.000056396086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9984921,0.00045317496,0.00029787957,0.0002570616,0.00023704761,0.00026270567],"domain_scores_gemma":[0.9978825,0.0006209263,0.00003403142,0.0010071382,0.00041909216,0.000036350153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019985435,0.000076225464,0.0001321126,0.00019243221,0.00041100613,0.00013917408,0.0010423694,0.00007083189,0.00003193098],"category_scores_gemma":[0.0003184754,0.00004728861,0.00005382176,0.0007943095,0.00035431466,0.00014270443,0.00018725533,0.0003839992,0.000012276794],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001290746,0.00032715334,0.003851626,0.000011993997,0.000034357192,0.000005908728,0.0009203894,0.00018156419,0.002323531,0.9484475,0.006461591,0.037421457],"study_design_scores_gemma":[0.0013488476,0.0013574769,0.57939845,0.00012881009,0.0000075376847,0.00007304278,0.0017262497,0.053499453,0.054426,0.3010104,0.0065176175,0.0005061389],"about_ca_topic_score_codex":0.00076988095,"about_ca_topic_score_gemma":0.00074430596,"teacher_disagreement_score":0.64743716,"about_ca_system_score_codex":0.000017931343,"about_ca_system_score_gemma":0.00032918103,"threshold_uncertainty_score":0.31611684},"labels":[],"label_agreement":null},{"id":"W381406155","doi":"10.1023/a:1018935031580","title":"Scheduling the flying squad nurses of a hospital using a multi-objective programming model","year":2000,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Computer science; Programming language","score_opus":0.20011221527984288,"score_gpt":0.44096406525828014,"score_spread":0.24085184997843725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W381406155","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8051301,0.00043085462,0.19206384,0.00023755788,0.000039432638,0.0008402589,0.000008188994,0.00007946955,0.001170268],"genre_scores_gemma":[0.87182415,0.000099346806,0.12782829,0.000007534266,0.000020567466,0.000057696725,0.0000031225838,0.000023008974,0.00013628963],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988147,0.00006961549,0.0003249168,0.00013014665,0.0003448502,0.00031578972],"domain_scores_gemma":[0.9990393,0.00009668869,0.000014390264,0.00022471196,0.0005643254,0.000060566923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067717244,0.000096445525,0.00016113851,0.00015141365,0.00032075445,0.00009157518,0.00019586715,0.00005655774,0.00007785032],"category_scores_gemma":[0.00029004013,0.0000763191,0.00007277326,0.0005911337,0.00018811498,0.0002650075,0.000033156746,0.00024568988,0.000008610014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000043699165,0.00015331482,0.000015073473,0.0000651413,0.000036494133,4.873653e-7,0.003938305,0.9633105,0.0013282329,0.0013158559,0.000009858473,0.029822396],"study_design_scores_gemma":[0.00012550777,0.00005476073,0.000010518316,0.00009331265,0.0000060913526,8.9445166e-7,0.0016352573,0.9921304,0.0056803813,0.000115243216,0.00006643812,0.00008118794],"about_ca_topic_score_codex":0.000068447334,"about_ca_topic_score_gemma":0.0000136010385,"teacher_disagreement_score":0.066694014,"about_ca_system_score_codex":0.000017329086,"about_ca_system_score_gemma":0.000067642584,"threshold_uncertainty_score":0.31122023},"labels":[],"label_agreement":null},{"id":"W4200461915","doi":"10.1007/s10479-021-04480-8","title":"Residential choice from a multiple criteria sustainable perspective","year":2021,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Universidad de Oviedo; Ministerio de Ciencia, Innovación y Universidades","keywords":"TOPSIS; Ranking (information retrieval); Multiple-criteria decision analysis; Neighbourhood (mathematics); Computer science; Operations research; Sustainability; Ideal solution; Theory of computation; Management science; Environmental economics; Mathematics; Economics; Artificial intelligence","score_opus":0.22937354757841852,"score_gpt":0.5296157549876085,"score_spread":0.30024220740918994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200461915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9619914,0.0008991683,0.000091252055,0.013684672,0.00006340084,0.0002485774,0.000054514614,0.00001962828,0.022947377],"genre_scores_gemma":[0.98427576,0.00014201111,0.00031044267,0.00006849079,0.00032581927,0.00002824077,0.000038205126,0.0000065053887,0.014804519],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977328,0.00066113035,0.00020157546,0.00030228175,0.00067594013,0.00042623826],"domain_scores_gemma":[0.9941107,0.00040529482,0.000013687799,0.00029289298,0.0050573116,0.00012013299],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014870248,0.000058864527,0.00013401714,0.00011477443,0.0011930416,0.00032786207,0.00030128667,0.0000757477,0.003383501],"category_scores_gemma":[0.0046417997,0.000059153324,0.00007391322,0.00085482176,0.0004379721,0.0007044998,0.00008226531,0.00021764106,0.000030167253],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003283264,0.0028160177,0.44558865,0.00012869654,0.00035163053,0.0004086867,0.20641324,0.00031477393,0.040894542,0.23076352,0.070571445,0.0014204534],"study_design_scores_gemma":[0.00079535996,0.00011168415,0.5856412,0.00006578662,0.000019266932,2.176118e-7,0.20616128,0.0005974395,0.07566364,0.030811328,0.09978304,0.00034977327],"about_ca_topic_score_codex":0.2556314,"about_ca_topic_score_gemma":0.16342899,"teacher_disagreement_score":0.1999522,"about_ca_system_score_codex":0.000060352017,"about_ca_system_score_gemma":0.0013374953,"threshold_uncertainty_score":0.99752754},"labels":[],"label_agreement":null},{"id":"W4205183153","doi":"10.1007/s10479-021-04481-7","title":"The analysis of serve decisions in tennis using Bayesian hierarchical models","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Salient; Computer science; Adversary; Bayesian probability; Preference; Operations research; Data science; Artificial intelligence; Engineering; Mathematics; Statistics; Computer security","score_opus":0.4159646112100356,"score_gpt":0.4319273711165202,"score_spread":0.015962759906484603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205183153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9903767,0.0012334763,0.0031361624,0.0021919229,0.000033618533,0.00016103868,0.0003119558,0.000002033302,0.0025530828],"genre_scores_gemma":[0.99800456,0.0010843587,0.00027735252,0.000047146586,0.000011355855,0.000028215589,0.000024869849,0.0000073871483,0.0005147449],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859214,0.000070087495,0.0006914123,0.0002037002,0.00018288779,0.00025977715],"domain_scores_gemma":[0.99900186,0.00022500328,0.00007131323,0.0004325669,0.00021934956,0.000049932678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037286158,0.000055517507,0.0002793755,0.001333317,0.0006294305,0.000057310117,0.00039664487,0.000028201082,0.00046267922],"category_scores_gemma":[0.00018515676,0.000050233,0.00014633029,0.0031723406,0.00013064177,0.00014849401,0.00021039837,0.00029733003,0.0000028837203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014489535,0.000099923236,0.017587528,0.0000017046673,0.0001206662,0.0000013140582,0.0004638965,0.82536006,0.000016017355,0.15563163,0.00013046719,0.00057232374],"study_design_scores_gemma":[0.00007312831,0.000045397894,0.019546859,0.0000036886904,0.0000063479283,3.9310115e-7,0.000325872,0.96579915,0.000028617249,0.01177175,0.0023449396,0.000053827072],"about_ca_topic_score_codex":0.0038669035,"about_ca_topic_score_gemma":0.0016466242,"teacher_disagreement_score":0.14385988,"about_ca_system_score_codex":0.000035844252,"about_ca_system_score_gemma":0.00009952039,"threshold_uncertainty_score":0.5845627},"labels":[],"label_agreement":null},{"id":"W4212773160","doi":"10.1007/s10479-022-04559-w","title":"Joint robust optimization of bed capacity, nurse staffing, and care access under uncertainty","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Science Foundation","keywords":"Staffing; Robustness (evolution); Robust optimization; Computer science; Flexibility (engineering); Ellipsoid; Mathematical optimization; Health care; Resource allocation; Operations research; Operations management; Medicine; Mathematics; Economics; Statistics; Nursing","score_opus":0.556376839376147,"score_gpt":0.5228452868946046,"score_spread":0.03353155248154238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212773160","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96708024,0.0005448887,0.02316604,0.004574327,0.00013154269,0.00069738907,0.00025993914,0.000016023498,0.003529592],"genre_scores_gemma":[0.995554,0.00064798177,0.0029515184,0.00006564149,0.000025157944,0.000056312838,0.000089898625,0.000011573619,0.0005979458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99568105,0.0009217835,0.00067374296,0.0003673113,0.0021047532,0.00025135736],"domain_scores_gemma":[0.9946792,0.00033704852,0.000121554345,0.0005206608,0.0042384756,0.00010303966],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004121626,0.000093903036,0.00024879348,0.0009420872,0.00083919894,0.00031846322,0.0006288187,0.00005159634,0.0012476841],"category_scores_gemma":[0.0015535249,0.000080868645,0.0000658919,0.002064997,0.00029246925,0.0006426476,0.00042510335,0.00025911405,0.000003634884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032015865,0.000097236516,0.0012806663,0.0000059814365,0.000012531013,7.890821e-7,0.0029069323,0.9852222,0.00016462787,0.003511986,0.0042902306,0.0024747907],"study_design_scores_gemma":[0.00049686636,0.00047287974,0.0037124678,0.000020029742,0.000009164804,0.000005625806,0.029972535,0.9572747,0.004048,0.002053858,0.0017464742,0.00018740565],"about_ca_topic_score_codex":0.0014544072,"about_ca_topic_score_gemma":0.0004449055,"teacher_disagreement_score":0.028473713,"about_ca_system_score_codex":0.000037122867,"about_ca_system_score_gemma":0.0003779976,"threshold_uncertainty_score":0.9996653},"labels":[],"label_agreement":null},{"id":"W4214562182","doi":"10.1007/s10479-022-04578-7","title":"Unlocking the black box: Non-parametric option pricing before and during COVID-19","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Moneyness; Valuation of options; Economics; Financial economics; Coronavirus disease 2019 (COVID-19); Black–Scholes model; Crash; Econometrics; Volatility (finance); Actuarial science; Computer science","score_opus":0.18380669859702733,"score_gpt":0.37908392859374174,"score_spread":0.1952772299967144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214562182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837813,0.0009218201,0.00028997526,0.008111581,0.00005885345,0.00040977352,0.00006502562,0.000009621123,0.0063520544],"genre_scores_gemma":[0.997445,0.00074793,0.00012328684,0.0003393046,0.000051489304,0.00010244032,0.000013756746,0.000011213363,0.001165583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99885005,0.00008649688,0.00037614536,0.00026320847,0.00013388519,0.00029019426],"domain_scores_gemma":[0.99938625,0.00011108669,0.00006588392,0.0002642298,0.000098218894,0.00007435161],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0024834555,0.00007684092,0.00016837592,0.00060227903,0.001706083,0.00017968964,0.0002500709,0.00003150954,0.00027045948],"category_scores_gemma":[0.00069250015,0.00007143712,0.00004718133,0.0011278902,0.00021315936,0.00027914898,0.000269753,0.00030370234,0.000019368637],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046836518,0.00014916236,0.023425879,0.00012866144,0.00004875246,0.00000564724,0.0042213346,0.059114993,0.00023519984,0.9095231,0.0024917047,0.00060872786],"study_design_scores_gemma":[0.0015913753,0.0016421718,0.58504444,0.0000507149,0.000009446864,0.00002753814,0.011505477,0.18944335,0.0014644599,0.12771751,0.08081349,0.00069004524],"about_ca_topic_score_codex":0.001453954,"about_ca_topic_score_gemma":0.00010234736,"teacher_disagreement_score":0.7818056,"about_ca_system_score_codex":0.00007813018,"about_ca_system_score_gemma":0.000109058186,"threshold_uncertainty_score":0.99959356},"labels":[],"label_agreement":null},{"id":"W4220672502","doi":"10.1007/s10479-022-04543-4","title":"Optimal multi-stage group partition for efficient coronavirus screening","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Manitoba","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Wilfrid Laurier University","keywords":"Partition (number theory); Stage (stratigraphy); Economic shortage; Computer science; Coronavirus disease 2019 (COVID-19); Group testing; Scheme (mathematics); Group (periodic table); Coronavirus; Multi stage; Tree (set theory); Mathematical optimization; Operations research; Mathematics; Medicine; Engineering; Combinatorics; Industrial engineering","score_opus":0.8785268876190176,"score_gpt":0.6386875129358051,"score_spread":0.2398393746832126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220672502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76626605,0.00042826319,0.22392613,0.0068005626,0.000056732057,0.0017577466,0.0004789353,0.000063031664,0.0002225395],"genre_scores_gemma":[0.9419324,0.00004938112,0.05492074,0.00027408075,0.000047100984,0.0014867424,0.000057310837,0.00001746431,0.0012148147],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976389,0.00064163195,0.0004168975,0.0002984032,0.0005702933,0.0004338732],"domain_scores_gemma":[0.9959724,0.0030891385,0.000043914493,0.00028190666,0.00054076914,0.000071884446],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005939397,0.000097802396,0.00025029414,0.00015240762,0.001455486,0.000034900164,0.00027700549,0.0000364614,0.00048120538],"category_scores_gemma":[0.007251255,0.00008380641,0.0001255412,0.00037791612,0.00017053563,0.00006117647,0.0005164058,0.0003022342,0.0000088129345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032305229,0.0017471847,0.0009614321,0.00017847646,0.00013106398,0.000008242053,0.0014846968,0.7828289,0.005045745,0.18564308,0.017900798,0.003747332],"study_design_scores_gemma":[0.00128777,0.0017076782,0.0052101207,0.00004194278,0.000017942648,0.0000022627084,0.00386345,0.9262044,0.0035680882,0.0033737372,0.05439928,0.0003233144],"about_ca_topic_score_codex":0.0003452398,"about_ca_topic_score_gemma":0.00014132378,"teacher_disagreement_score":0.18226933,"about_ca_system_score_codex":0.00005609864,"about_ca_system_score_gemma":0.000055023786,"threshold_uncertainty_score":0.9998445},"labels":[],"label_agreement":null},{"id":"W4223928586","doi":"10.1007/s10479-022-04656-w","title":"Stochastic dominance spanning and augmenting the human development index with institutional quality","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; Edge Hill University","keywords":"Stochastic dominance; Human Development Index; Welfare; Index (typography); Composite index; Economics; Corporate governance; Dominance (genetics); Econometrics; Human development (humanity); Quality (philosophy); Composite indicator; Measure (data warehouse); Mathematics; Public economics; Welfare economics; Computer science; Economic growth; Data mining; Management","score_opus":0.3365755104872686,"score_gpt":0.5067608231956406,"score_spread":0.17018531270837206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223928586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899627,0.000109969136,0.0008978575,0.0027679126,0.000034597226,0.00029148767,0.000007454996,0.000008132868,0.0059198844],"genre_scores_gemma":[0.99821544,0.000010500353,0.00014416805,0.00013871944,0.00006881336,0.00011449329,0.000008206113,0.0000033794825,0.0012962777],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9973967,0.0008521032,0.00023507525,0.00016040864,0.0010806693,0.0002750197],"domain_scores_gemma":[0.999087,0.00020552299,0.000034978653,0.00013715314,0.0004845245,0.000050847713],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008204288,0.000050838487,0.00009307854,0.00009424305,0.00816909,0.00011420921,0.0002555195,0.000019619381,0.0001713429],"category_scores_gemma":[0.00041374014,0.000038307426,0.000016306349,0.0004390169,0.0007006644,0.00021112713,0.00021872758,0.0002881187,0.0000023056066],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007116149,0.00027469423,0.023642078,0.00003215524,0.000053337648,0.0000027036424,0.08552334,0.018453108,0.00027514395,0.86786693,0.0010391542,0.0027662092],"study_design_scores_gemma":[0.0020018106,0.00064528635,0.73382676,0.00017437313,0.00001150041,0.0000073396986,0.1286556,0.0037880351,0.0012168834,0.0061974814,0.122740716,0.00073419354],"about_ca_topic_score_codex":0.006860739,"about_ca_topic_score_gemma":0.0048121684,"teacher_disagreement_score":0.8616694,"about_ca_system_score_codex":0.00007239985,"about_ca_system_score_gemma":0.0008579615,"threshold_uncertainty_score":0.99975264},"labels":[],"label_agreement":null},{"id":"W4224239365","doi":"10.1007/s10479-022-04673-9","title":"A flexible robust model for blood supply chain network design problem","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Supply chain; Robustness (evolution); Supply chain network; Facility location problem; Network planning and design; Computer science; Robust optimization; Blood supply; Coronavirus disease 2019 (COVID-19); Risk analysis (engineering); Operations research; Supply chain risk management; Supply chain management; Operations management; Service management; Mathematical optimization; Business; Engineering; Computer network; Medicine","score_opus":0.3244326607639991,"score_gpt":0.398151544860401,"score_spread":0.07371888409640187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224239365","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04289546,0.001915284,0.71600574,0.17755805,0.0004460497,0.010300699,0.00019758887,0.00042244417,0.05025868],"genre_scores_gemma":[0.9531707,0.00014049157,0.031951774,0.0028029094,0.0004580788,0.0020049869,0.00015755836,0.00004473333,0.009268739],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826217,0.00011068521,0.00030788622,0.00026654007,0.000657299,0.00039543852],"domain_scores_gemma":[0.99833333,0.00022546081,0.000052353225,0.00022620402,0.0011432158,0.000019407116],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0045625046,0.000095223935,0.00014356324,0.00043928612,0.0016463867,0.00034267505,0.00036923843,0.0000352212,0.0010634972],"category_scores_gemma":[0.00022267867,0.00009551875,0.00007400344,0.0012118372,0.00005652349,0.001075436,0.00020917774,0.00028218958,0.000027012906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010652357,0.00038300754,0.00007123788,0.000050215236,0.000041284162,0.0000011486022,0.000107255415,0.79906803,0.00032024222,0.15353033,0.045125876,0.0011948618],"study_design_scores_gemma":[0.0006646686,0.00008463656,0.00003726387,0.000013504096,0.000024874245,0.0000014157393,0.00031147464,0.9480292,0.00047826066,0.009679021,0.040550757,0.00012488109],"about_ca_topic_score_codex":0.00034175345,"about_ca_topic_score_gemma":0.00016801676,"teacher_disagreement_score":0.9102753,"about_ca_system_score_codex":0.0000066371013,"about_ca_system_score_gemma":0.0001863927,"threshold_uncertainty_score":0.9998497},"labels":[],"label_agreement":null},{"id":"W4224294234","doi":"10.1007/s10479-022-04686-4","title":"Stochastic weekly operating room planning with an exponential number of scenarios","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Mathematical optimization; Theory of computation; Variable (mathematics); State variable; Computer science; Exponential function; Random variable; Stochastic programming; Function (biology); Mathematics; Algorithm; Statistics","score_opus":0.3910185297094651,"score_gpt":0.5812675020821944,"score_spread":0.19024897237272925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224294234","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97686267,0.000075334254,0.016496597,0.003650946,0.00012277788,0.0011995446,0.00010760901,0.000031445335,0.0014530855],"genre_scores_gemma":[0.9866254,0.000012256418,0.0105556855,0.0002240333,0.00013990629,0.00059926935,0.00025253242,0.000036993963,0.0015539397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948177,0.0024577968,0.0008099544,0.00033746433,0.0010112603,0.00056582893],"domain_scores_gemma":[0.99634,0.00038651616,0.000095187475,0.00048017353,0.0025152205,0.0001829497],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004105691,0.00012529574,0.00029121994,0.00035407674,0.00444831,0.000042235974,0.00032394665,0.00009204655,0.0025157647],"category_scores_gemma":[0.0005607157,0.000113203285,0.000038864346,0.0009889044,0.000107614855,0.00042774476,0.00022690458,0.0011513241,0.000026004242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017147665,0.0003287046,0.004827166,0.00008077852,0.000033028882,0.000004854169,0.013941964,0.97117394,0.0016821441,0.006405974,0.00094664196,0.00040332586],"study_design_scores_gemma":[0.0014574246,0.0022608913,0.0037128057,0.0004197871,0.00001538279,0.000017133356,0.0654448,0.92475986,0.00057748955,0.000094681774,0.0008877771,0.00035198315],"about_ca_topic_score_codex":0.0026626082,"about_ca_topic_score_gemma":0.00034141756,"teacher_disagreement_score":0.051502835,"about_ca_system_score_codex":0.00006950333,"about_ca_system_score_gemma":0.0019607109,"threshold_uncertainty_score":0.9983961},"labels":[],"label_agreement":null},{"id":"W4224296565","doi":"10.1007/s10479-022-04706-3","title":"A note on scheduling coupled tasks for minimum total completion time","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Zhàng; Computer science; Theory of computation; Scheduling (production processes); Mathematical optimization; Algorithm; Mathematics","score_opus":0.12244127384344361,"score_gpt":0.397452736203805,"score_spread":0.2750114623603614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224296565","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86341274,0.00034425466,0.12714203,0.004615699,0.00039594603,0.0013626488,0.00040370328,0.00025266726,0.0020702954],"genre_scores_gemma":[0.96140975,0.000028671035,0.036558066,0.00009872556,0.00012360195,0.00036244845,0.00031128837,0.000036942558,0.0010705112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879515,0.000090622314,0.00022837459,0.00015633026,0.0004667389,0.00026275677],"domain_scores_gemma":[0.9990154,0.00023094741,0.000010271433,0.0002036752,0.00047585572,0.00006387228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010598437,0.000078977384,0.0001343596,0.00030844187,0.0005411356,0.00006019336,0.00015751508,0.00003701991,0.00052153657],"category_scores_gemma":[0.00027057435,0.0000882769,0.00006046885,0.0004644607,0.00004078624,0.000078858015,0.000050693186,0.00027415447,0.000060000537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034503726,0.00006904744,0.0000021217877,0.000015041795,0.0000194522,6.93745e-7,0.000265188,0.9880578,0.008619325,0.0007087256,0.0016032198,0.000604869],"study_design_scores_gemma":[0.00031817108,0.0002508985,0.000037235077,0.000011278875,0.000002272354,0.0000021975932,0.00015931595,0.9937703,0.0044520274,0.000035221674,0.0008713095,0.00008977781],"about_ca_topic_score_codex":0.000019512696,"about_ca_topic_score_gemma":0.0000031640755,"teacher_disagreement_score":0.09799699,"about_ca_system_score_codex":0.000039811985,"about_ca_system_score_gemma":0.00007183047,"threshold_uncertainty_score":0.571046},"labels":[],"label_agreement":null},{"id":"W4224298152","doi":"10.1007/s10479-022-04661-z","title":"Sustainable closed-loop supply chain with energy efficiency: Lagrangian relaxation, reformulations and heuristics","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":113,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"University of Melbourne","keywords":"Supply chain; Lagrangian relaxation; Heuristics; Remanufacturing; Computer science; Profit (economics); Environmental economics; Operations research; Supply chain management; Theory of computation; Mathematical optimization; Business; Economics; Manufacturing engineering; Microeconomics; Marketing; Mathematics; Engineering","score_opus":0.04350973340699243,"score_gpt":0.3126777133944018,"score_spread":0.2691679799874094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224298152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89959776,0.00088667753,0.0049652904,0.047955077,0.00011606318,0.0023200407,0.000042240128,0.0001866938,0.043930154],"genre_scores_gemma":[0.97584105,0.00005836224,0.00023165163,0.00075005315,0.00015583799,0.00035408972,0.0001927672,0.00003630511,0.022379864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974621,0.00012597047,0.0003468356,0.0003827851,0.0010240554,0.00065828377],"domain_scores_gemma":[0.9971463,0.00012206586,0.00009941276,0.000466174,0.002133139,0.000032872533],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0025928682,0.00015275058,0.00018275983,0.0014380569,0.0023456146,0.00042499136,0.00039807608,0.00003754483,0.0004293993],"category_scores_gemma":[0.00064605824,0.00014202866,0.000039704995,0.0029056654,0.00021550783,0.00089454296,0.0007919714,0.0002796205,0.000010678765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000982077,0.00031172426,0.003938153,0.00021874468,0.000048749254,0.0000618911,0.00048356003,0.09595618,0.000068493006,0.88057584,0.016616391,0.0016220605],"study_design_scores_gemma":[0.0018967467,0.0005893875,0.013996753,0.000056404366,0.00006291748,0.000012194003,0.0849174,0.28885853,0.00030696532,0.01955905,0.58894235,0.0008012857],"about_ca_topic_score_codex":0.0086631905,"about_ca_topic_score_gemma":0.0006548236,"teacher_disagreement_score":0.8610168,"about_ca_system_score_codex":0.00009147032,"about_ca_system_score_gemma":0.00020902876,"threshold_uncertainty_score":0.9989532},"labels":[],"label_agreement":null},{"id":"W4225279906","doi":"10.1007/s10479-022-04689-1","title":"Smart supply chain management in Industry 4.0: the review, research agenda and strategies in North America","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":205,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Windsor; National Science Foundation","keywords":"Supply chain; Information and Communications Technology; Supply chain management; Smart manufacturing; Business; Industry 4.0; Systematic review; Knowledge management; Process management; Industrial organization; Computer science; Engineering management; Marketing; Engineering; Manufacturing engineering; Political science","score_opus":0.20845475903748611,"score_gpt":0.4274458321997248,"score_spread":0.2189910731622387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225279906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86052054,0.0070021725,0.000025725105,0.0132220555,0.00006216452,0.0019832766,0.00016720234,0.000039724902,0.11697716],"genre_scores_gemma":[0.9886404,0.009380263,0.000050495073,0.00014649986,0.0000132198975,0.00092394213,0.000047534882,0.000015627356,0.0007819607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976665,0.00050108496,0.00040103402,0.00016160538,0.00084106403,0.0004287353],"domain_scores_gemma":[0.99927974,0.00016952648,0.000008004255,0.00031834675,0.00017384379,0.000050514303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029819342,0.00008474087,0.00013972053,0.000691411,0.00026511197,0.00013867507,0.00041484233,0.000048475795,0.00032488958],"category_scores_gemma":[0.00007676269,0.00007678748,0.00002156282,0.0028844713,0.00022123112,0.00043227765,0.000219753,0.001844421,0.000015748761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037903752,0.00037003073,0.006260451,0.0017406708,0.00010115755,0.00010892462,0.007983536,0.7690135,0.00010895967,0.01733807,0.14355801,0.05337875],"study_design_scores_gemma":[0.0013622894,0.0006818766,0.11063556,0.0013887533,0.000009023122,0.0000311741,0.15834978,0.05829799,0.000781938,0.0015044729,0.6661289,0.00082826614],"about_ca_topic_score_codex":0.00034884736,"about_ca_topic_score_gemma":0.000899253,"teacher_disagreement_score":0.71071553,"about_ca_system_score_codex":0.00006474096,"about_ca_system_score_gemma":0.0001109086,"threshold_uncertainty_score":0.8013194},"labels":[],"label_agreement":null},{"id":"W4225691621","doi":"10.1007/s10479-022-04658-8","title":"Optimization of the technician routing and scheduling problem for a telecommunication industry","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Technician; Computer science; Scheduling (production processes); Operations research; Job shop scheduling; Metaheuristic; Service provider; Time horizon; Routing (electronic design automation); Service (business); Mathematical optimization; Computer network; Operations management; Artificial intelligence; Engineering; Business","score_opus":0.1611433904965729,"score_gpt":0.4261114328978416,"score_spread":0.2649680424012687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225691621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49505594,0.0007099957,0.4939414,0.0055016056,0.0000773316,0.0023510573,0.000080562386,0.00012764343,0.0021544637],"genre_scores_gemma":[0.78556263,0.000060210954,0.21408893,0.000016724243,0.000010986323,0.00017468803,0.000011402502,0.000016903085,0.00005753664],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988769,0.00032302388,0.000291764,0.00009697616,0.0002523445,0.00015898305],"domain_scores_gemma":[0.99896854,0.00019744581,0.000032958924,0.00029983546,0.00047804235,0.000023175759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002731756,0.00005267732,0.00009672324,0.00018079215,0.0005944839,0.000030738818,0.000282993,0.000064900414,0.000024758814],"category_scores_gemma":[0.0005510121,0.000050384755,0.000029051362,0.0008470341,0.00007417463,0.00011155772,0.00022002256,0.00048300254,9.2635254e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035415742,0.000022056614,0.00025946085,0.00003647546,0.000011917375,1.5660989e-8,0.00040926097,0.9899687,0.004684906,0.0023092115,0.000060012535,0.00223445],"study_design_scores_gemma":[0.00010978488,0.000043252796,0.00020272822,0.00003013426,0.0000030734607,0.000001418024,0.000665357,0.9849743,0.013674464,0.000097505545,0.00015024819,0.00004772158],"about_ca_topic_score_codex":0.000032748478,"about_ca_topic_score_gemma":0.00000828128,"teacher_disagreement_score":0.2905067,"about_ca_system_score_codex":0.000027982298,"about_ca_system_score_gemma":0.000084196145,"threshold_uncertainty_score":0.45723495},"labels":[],"label_agreement":null},{"id":"W4226133331","doi":"10.1007/s10479-022-04676-6","title":"Measuring individual efficiency and unit influence in centrally managed systems","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Data envelopment analysis; Ranking (information retrieval); Computer science; Set (abstract data type); Measure (data warehouse); Projection (relational algebra); Efficient frontier; Mathematical optimization; Production–possibility frontier; Production (economics); Data mining; Mathematics; Algorithm; Economics; Artificial intelligence","score_opus":0.5510430726362899,"score_gpt":0.5103237528431546,"score_spread":0.04071931979313537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226133331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952702,0.0009013949,0.00024273999,0.0017053101,0.000048745125,0.00032840203,0.000030608688,0.000010124566,0.0014625111],"genre_scores_gemma":[0.99894845,0.000051217725,0.000082868166,0.000068128444,0.000011533646,0.000053439402,0.0000048248403,0.0000070927613,0.0007724244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99121195,0.0025066333,0.00081211876,0.0005080314,0.004474191,0.00048708866],"domain_scores_gemma":[0.9964229,0.0012906393,0.000066532615,0.0006376554,0.0014719589,0.000110323424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027805477,0.000093172275,0.0002565678,0.0021962938,0.001122543,0.00063864596,0.001388851,0.00003552226,0.00014685279],"category_scores_gemma":[0.007041089,0.000082480896,0.00004921393,0.0059300843,0.00032047214,0.00046837068,0.0008097933,0.0005461504,0.00003161196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015751306,0.0001973452,0.030343901,0.000008932674,0.00001385482,0.00001993019,0.0024423073,0.95613825,0.0013031235,0.0077935336,0.0003966127,0.0013264479],"study_design_scores_gemma":[0.00078169804,0.00058622257,0.42822927,0.00010163768,0.000013404269,0.000032577034,0.024965104,0.53548044,0.0015031967,0.0021936253,0.0056516156,0.00046117508],"about_ca_topic_score_codex":0.001337678,"about_ca_topic_score_gemma":0.00043375607,"teacher_disagreement_score":0.42065778,"about_ca_system_score_codex":0.000031307503,"about_ca_system_score_gemma":0.0003145354,"threshold_uncertainty_score":0.9636879},"labels":[],"label_agreement":null},{"id":"W4229025461","doi":"10.1007/s10479-022-04713-4","title":"Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Healthcare and Environmental Waste Management","field":"Medicine","cited_by":114,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Supply chain network; Mathematical optimization; Heuristic; Pareto principle; Supply chain; Pareto optimal; Variable neighborhood search; Operations research; Supply chain management; Metaheuristic; Multi-objective optimization; Artificial intelligence; Machine learning; Engineering; Mathematics","score_opus":0.37494176839330917,"score_gpt":0.4543444267938807,"score_spread":0.07940265840057154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229025461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84488666,0.0006664522,0.13416655,0.01759338,0.00014481954,0.0021087332,0.00004613744,0.000043696054,0.00034354578],"genre_scores_gemma":[0.98404986,0.000053775246,0.01414005,0.0007838748,0.00008797451,0.00012456768,0.00015818517,0.000028184319,0.0005735378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99651456,0.0011422168,0.00066887966,0.0003268171,0.0007977068,0.0005498309],"domain_scores_gemma":[0.99866056,0.00019837244,0.000060600472,0.00043804778,0.00045286652,0.00018953341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004402989,0.00013138742,0.0002986586,0.0006545311,0.0006754981,0.000034559926,0.00025910995,0.00005938303,0.00075888255],"category_scores_gemma":[0.00026828842,0.00013126658,0.00008947511,0.0013285993,0.00014404501,0.000182564,0.00030603982,0.00061991485,0.0000101552505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031726721,0.0025897503,0.0021068212,0.00029328367,0.0002902113,0.00014041078,0.0055229273,0.74407387,0.13031825,0.01620382,0.0048195487,0.0904684],"study_design_scores_gemma":[0.0003537517,0.0047149607,0.0006931265,0.0003347028,0.000041855717,0.000013466463,0.012292789,0.8939687,0.08262567,0.00037884837,0.0043568844,0.00022523665],"about_ca_topic_score_codex":0.0053971517,"about_ca_topic_score_gemma":0.000294606,"teacher_disagreement_score":0.14989482,"about_ca_system_score_codex":0.00018667986,"about_ca_system_score_gemma":0.0005105148,"threshold_uncertainty_score":0.83092314},"labels":[],"label_agreement":null},{"id":"W4229366107","doi":"10.1007/s10479-022-04710-7","title":"Supplier selection in closed loop pharma supply chain: a novel BWM–GAIA framework","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Selection (genetic algorithm); Supply chain; Hierarchy; Circular economy; Supply chain management; Theory of computation; Process management; Operations research; Risk analysis (engineering); Business; Marketing; Artificial intelligence; Algorithm; Engineering; Economics","score_opus":0.12178857584760718,"score_gpt":0.3897344587921001,"score_spread":0.26794588294449295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229366107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9364308,0.00027859773,0.0038950406,0.0445695,0.0004092321,0.0031870508,0.000044030356,0.00013698747,0.011048755],"genre_scores_gemma":[0.9907585,0.000039427086,0.0005678426,0.0021977222,0.00048342123,0.0009307639,0.000119888886,0.00004790284,0.0048545413],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99684477,0.00013830377,0.00047673602,0.00048365502,0.001256725,0.00079979305],"domain_scores_gemma":[0.99842787,0.00016318916,0.000060419945,0.0003461546,0.00097551564,0.000026859827],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038458928,0.00017951537,0.00024126993,0.0021915927,0.0009652644,0.00038833715,0.00065397774,0.000067027664,0.0055172374],"category_scores_gemma":[0.0006577948,0.00020185225,0.00008621023,0.0046078265,0.000113171016,0.0009672611,0.0009541027,0.00086051034,0.00012022883],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007731862,0.003310014,0.023421895,0.00068003114,0.00019863514,0.00010321044,0.0016461334,0.30708703,0.01093742,0.4415445,0.20090501,0.009392915],"study_design_scores_gemma":[0.0026798414,0.00024372165,0.022828888,0.00010237372,0.000028833216,0.0000060897637,0.018747073,0.34804592,0.0022547469,0.01103696,0.5931817,0.0008438404],"about_ca_topic_score_codex":0.0037322815,"about_ca_topic_score_gemma":0.0004719929,"teacher_disagreement_score":0.43050754,"about_ca_system_score_codex":0.00015110512,"about_ca_system_score_gemma":0.00017423638,"threshold_uncertainty_score":0.99539185},"labels":[],"label_agreement":null},{"id":"W4230776514","doi":"10.1023/a:1020719714437","title":"Recent Developments in the Theory and Applications of Location Models: A Preview","year":2002,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Theory of computation; Mathematics; Computer science; Mathematical economics; Algorithm","score_opus":0.36558002536392603,"score_gpt":0.4124520385444206,"score_spread":0.046872013180494554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230776514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44712546,0.07318389,0.035055112,0.10103086,0.00021548712,0.016187547,0.000029815466,0.00011826267,0.32705358],"genre_scores_gemma":[0.98592883,0.0124890115,0.00010352546,0.00059011596,0.00003090755,0.00038687285,0.00001829867,0.000004419375,0.00044803426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892414,0.00011787839,0.0003280428,0.00014272747,0.0003509868,0.00013621092],"domain_scores_gemma":[0.9988061,0.000049135386,0.000018806886,0.00026111954,0.0008581799,0.0000066635025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033587678,0.00005652274,0.00009132772,0.0003216066,0.00015793323,0.00006109163,0.00024908312,0.000021962796,0.0002547505],"category_scores_gemma":[0.00027920722,0.000043190732,0.00001618372,0.001390053,0.00009499334,0.0004956106,0.00009170597,0.000086045875,0.00006455698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014529272,0.0004426625,0.00029457817,0.0004778272,0.000018966874,1.5765914e-7,0.00097199867,0.012974653,0.00002156766,0.759079,0.004180637,0.22152343],"study_design_scores_gemma":[0.0006927813,0.000052870346,0.02287879,0.00037017802,0.00003205451,0.0000010751409,0.007725616,0.33778903,0.00015513596,0.037938476,0.59198207,0.0003819083],"about_ca_topic_score_codex":0.00035760656,"about_ca_topic_score_gemma":0.00065795926,"teacher_disagreement_score":0.7211405,"about_ca_system_score_codex":0.0000067647916,"about_ca_system_score_gemma":0.000017894663,"threshold_uncertainty_score":0.27893394},"labels":[],"label_agreement":null},{"id":"W4233423259","doi":"10.1023/a:1026113019438","title":"Foreword","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Theory of computation; Computer science; Mathematics; Algorithm","score_opus":0.5635493581751287,"score_gpt":0.5722512263841881,"score_spread":0.008701868209059382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233423259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87522465,0.000558745,0.00019202834,0.002197253,0.00003944446,0.00051771477,0.00007256138,0.00009327077,0.121104315],"genre_scores_gemma":[0.98845655,0.000049122165,0.0014919317,0.000067131536,0.000025464426,0.00007104007,0.000009195347,0.000078350975,0.009751237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978359,0.0005895509,0.00023236171,0.00018970568,0.0007096178,0.00044286947],"domain_scores_gemma":[0.9973647,0.00014039603,0.000009589171,0.0004887483,0.001876881,0.00011967187],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032418433,0.000067081855,0.00011401869,0.00044261827,0.00024143941,0.00005423944,0.00023451018,0.000049880226,0.0027292604],"category_scores_gemma":[0.0021874942,0.00006173548,0.00005331526,0.0012348152,0.00024652592,0.00028095322,0.000039665316,0.00024697045,0.011117685],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027024313,0.0003645598,0.0010922137,0.000014410073,0.000042500953,0.0000042620563,0.00049899454,0.002816677,0.0325991,0.49382755,0.4681153,0.000597402],"study_design_scores_gemma":[0.00057723024,0.00048842444,0.0042134426,0.000049353977,0.0000044271965,0.000012206062,0.0010558668,0.0059692697,0.5832547,0.005064905,0.39902905,0.00028112403],"about_ca_topic_score_codex":0.00016056738,"about_ca_topic_score_gemma":0.00025229144,"teacher_disagreement_score":0.5506556,"about_ca_system_score_codex":0.000015375059,"about_ca_system_score_gemma":0.00023070366,"threshold_uncertainty_score":0.99818236},"labels":[],"label_agreement":null},{"id":"W4241323324","doi":"10.1007/s10479-005-2136-z","title":"Foreword","year":2005,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; HEC Montréal; University of New Brunswick","funders":"","keywords":"Theory of computation; Computer science; Algorithm","score_opus":0.5365404960915995,"score_gpt":0.5822936487901746,"score_spread":0.04575315269857516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241323324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9394382,0.0005388516,0.00010351891,0.017674746,0.00001826751,0.00043252722,0.000096686075,0.00012022443,0.04157697],"genre_scores_gemma":[0.98537344,0.00006163864,0.0024090132,0.00014603593,0.00016544132,0.0000666398,0.000016398546,0.00007767032,0.011683697],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981177,0.00025330504,0.00025297218,0.0001847717,0.0007551024,0.0004361587],"domain_scores_gemma":[0.99753904,0.000112542075,0.000009926068,0.00047191817,0.0017468567,0.00011972249],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0022575592,0.000066288914,0.00011071289,0.00048010866,0.00022270295,0.000056804063,0.0003294357,0.00004938869,0.002758752],"category_scores_gemma":[0.00068298273,0.000060998234,0.00005460142,0.00095026765,0.00024017943,0.0004613836,0.00009503867,0.00025898134,0.02492925],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053084892,0.00043562302,0.0004512318,0.000010733533,0.000040688305,0.0000019374481,0.00079291756,0.013605263,0.03669779,0.06746647,0.8703603,0.010083917],"study_design_scores_gemma":[0.00048895745,0.00035603053,0.0062957834,0.000045883215,0.000003658697,0.000006648304,0.0004681773,0.06808777,0.33421582,0.00061545346,0.5891824,0.00023344973],"about_ca_topic_score_codex":0.00021048637,"about_ca_topic_score_gemma":0.0009302672,"teacher_disagreement_score":0.29751804,"about_ca_system_score_codex":0.000023044098,"about_ca_system_score_gemma":0.00015423205,"threshold_uncertainty_score":0.99815285},"labels":[],"label_agreement":null},{"id":"W4251066204","doi":"10.1007/s10479-019-03467-w","title":"Correction to: Measuring short-term risk of initial public offering of equity securities: a hybrid Bayesian and Data-Envelopment-Analysis-based approach","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Equity (law); Term (time); Data envelopment analysis; Theory of computation; Bayesian probability; Computer science; Econometrics; Actuarial science; Financial economics; Economics; Statistics; Artificial intelligence; Mathematics; Algorithm; Political science","score_opus":0.5480317419842528,"score_gpt":0.5527443417719992,"score_spread":0.004712599787746408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251066204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9202558,0.00012620557,0.07604765,0.00028194563,0.00008734786,0.0003966464,0.00018291594,0.000009829149,0.0026116997],"genre_scores_gemma":[0.99738854,0.000044961773,0.0022201275,0.000019573445,0.000022691114,0.000017080338,0.00008405837,0.000010143963,0.0001927963],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9928374,0.0012713183,0.0012432229,0.0007798158,0.0034636268,0.00040460823],"domain_scores_gemma":[0.9928671,0.0016979645,0.00016975215,0.0017094176,0.0033788162,0.00017691427],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.022779813,0.00014111033,0.0006567163,0.003094923,0.00034709892,0.00039920065,0.0015631297,0.00005538624,0.0002238954],"category_scores_gemma":[0.010136262,0.00012023675,0.0001778689,0.004878931,0.00035608016,0.0007826462,0.001013849,0.00033419463,0.000010858494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032416036,0.0018820649,0.3182759,0.00024750008,0.0021596972,0.000005437635,0.005372937,0.5722018,0.021606285,0.0014570474,0.0032406428,0.073226556],"study_design_scores_gemma":[0.0001817467,0.00019856698,0.03014403,0.00006395168,0.00009893076,0.0000016640029,0.0014455543,0.9406007,0.026876487,0.00010618229,0.00012404392,0.00015813025],"about_ca_topic_score_codex":0.0008919962,"about_ca_topic_score_gemma":0.00091581047,"teacher_disagreement_score":0.36839893,"about_ca_system_score_codex":0.000031345222,"about_ca_system_score_gemma":0.00059683906,"threshold_uncertainty_score":0.9982018},"labels":[],"label_agreement":null},{"id":"W4254458964","doi":"10.1023/a:1014557624540","title":"Topological Design of Survivable Mesh-Based Transport Networks","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Mathematical optimization; Heuristic; Spare part; Network topology; Integer programming; Topology (electrical circuits); Routing (electronic design automation); Mesh networking; Network planning and design; Algorithm; Mathematics; Computer network; Telecommunications","score_opus":0.2338737876707419,"score_gpt":0.4078046797955178,"score_spread":0.17393089212477592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254458964","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14414524,0.00086583395,0.8509604,0.0007164102,0.000034607663,0.00036277613,0.000007143412,0.00019020113,0.0027174454],"genre_scores_gemma":[0.96457434,0.0016673274,0.033519626,0.000016904936,0.000024083904,0.00004863237,0.000009807055,0.000015673995,0.00012360731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987799,0.00008723263,0.00029821886,0.00013885669,0.00029475873,0.00040104988],"domain_scores_gemma":[0.99886185,0.0003545949,0.000007790588,0.0003212501,0.00039735268,0.00005715802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000801522,0.00009157298,0.00021067669,0.00017490372,0.000086314256,0.0000101166115,0.0002955009,0.00014560713,0.00020118938],"category_scores_gemma":[0.00021190397,0.00008105647,0.00004838291,0.0008406167,0.00035517957,0.00011675444,0.000024716035,0.00033284235,0.0000073124233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028545077,0.000059479175,0.00037980874,0.0000125294255,0.000016207401,0.000007806076,0.000010185861,0.9880733,0.0015371109,0.0073684077,0.0004857151,0.0020208887],"study_design_scores_gemma":[0.00014343041,0.00024606855,0.0008111628,0.000030131501,0.000002596912,0.0000013651947,0.000066423796,0.9832582,0.0135571305,0.0011207573,0.0006572224,0.000105496365],"about_ca_topic_score_codex":0.0000289052,"about_ca_topic_score_gemma":0.000029751978,"teacher_disagreement_score":0.8204291,"about_ca_system_score_codex":0.000012036369,"about_ca_system_score_gemma":0.000035999296,"threshold_uncertainty_score":0.33053866},"labels":[],"label_agreement":null},{"id":"W4282983271","doi":"10.1007/s10479-022-04758-5","title":"Dynamic collaborative optimization for disaster relief supply chains under information ambiguity","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Office for Philosophy and Social Sciences","keywords":"Emergency management; Supply chain; Ambiguity; Computer science; Operations research; Ranking (information retrieval); Fuzzy logic; Interval (graph theory); Business; Engineering","score_opus":0.11663716459423903,"score_gpt":0.38864304116681625,"score_spread":0.27200587657257724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282983271","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5221467,0.00024692548,0.29140356,0.1504967,0.001264366,0.008595176,0.00090007245,0.0002398864,0.024706608],"genre_scores_gemma":[0.99230754,0.00007145638,0.0010828975,0.001964734,0.00005669814,0.0008584779,0.0015967849,0.000011971972,0.0020494387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848276,0.000067529116,0.00038997593,0.00017568197,0.00062132877,0.00026274982],"domain_scores_gemma":[0.99763715,0.000028286197,0.000034932964,0.00027169418,0.0020134596,0.00001448558],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016821265,0.000092178474,0.00011707439,0.00061392516,0.0010795415,0.00025861282,0.0002722765,0.000028010376,0.0016081681],"category_scores_gemma":[0.0003155222,0.00009668761,0.000053475753,0.00141257,0.00007470201,0.0019225073,0.00029087826,0.0001387667,0.00007437955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065731794,0.00015043556,0.000040536404,0.00008675611,0.000022429764,8.4609425e-8,0.00042255758,0.90218544,0.00003780505,0.073092625,0.022720266,0.0011753252],"study_design_scores_gemma":[0.00033900706,0.00006332395,0.00087318884,0.0000068075956,0.000006228149,1.092552e-7,0.0060994653,0.9372355,0.000027602071,0.0004576916,0.054780442,0.00011064257],"about_ca_topic_score_codex":0.0010921059,"about_ca_topic_score_gemma":0.0011832485,"teacher_disagreement_score":0.47016084,"about_ca_system_score_codex":0.000056043682,"about_ca_system_score_gemma":0.00010000919,"threshold_uncertainty_score":0.9993045},"labels":[],"label_agreement":null},{"id":"W4283160339","doi":"10.1007/s10479-022-04798-x","title":"On horizon-consistent mean-variance portfolio allocation","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"European Research Council; Fonds de Recherche du Québec-Société et Culture","keywords":"Theory of computation; Variance (accounting); Portfolio; Horizon; Portfolio allocation; Mathematical economics; Computer science; Econometrics; Mathematics; Economics; Financial economics; Algorithm","score_opus":0.20625023236364798,"score_gpt":0.3758405606478733,"score_spread":0.16959032828422532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283160339","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2780119,0.006598092,0.48695958,0.04315743,0.00079090946,0.002851237,0.002188153,0.000113850205,0.17932886],"genre_scores_gemma":[0.9963463,0.00014583296,0.0006723901,0.00029793227,0.000063103085,0.0007051776,0.00006645438,0.000014884799,0.0016879009],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987178,0.00002293656,0.00047226646,0.00034398603,0.00017185646,0.0002711519],"domain_scores_gemma":[0.9989751,0.00010302321,0.000075175405,0.00043670947,0.00034448144,0.00006553864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001429248,0.00007768457,0.00018990305,0.00041343897,0.00076317467,0.000053252093,0.00035811856,0.00003521058,0.00077833765],"category_scores_gemma":[0.00037976136,0.000095377334,0.00006986509,0.0010025363,0.000088814515,0.00011847083,0.0001395661,0.0002808682,0.0002888303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018320548,0.0002556491,0.000040074246,0.000007757087,0.000016163136,8.9897736e-7,0.00020836257,0.0049904464,0.00009246291,0.9893444,0.0038440216,0.0011814319],"study_design_scores_gemma":[0.0005744463,0.0015814588,0.0044656987,0.000021529968,0.000004256519,0.000009003495,0.00073894934,0.021284174,0.001331718,0.8711104,0.09846322,0.0004151545],"about_ca_topic_score_codex":0.0006334398,"about_ca_topic_score_gemma":0.00004216459,"teacher_disagreement_score":0.71833444,"about_ca_system_score_codex":0.00005578295,"about_ca_system_score_gemma":0.00013349768,"threshold_uncertainty_score":0.8522252},"labels":[],"label_agreement":null},{"id":"W4292423539","doi":"10.1007/s10479-022-04909-8","title":"Reverse supply chain management with dual channel and collection disruptions: supply chain coordination and game theory approaches","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Chromatin structure remodeling (RSC) complex; Channel coordination; Supply chain; Incentive; Data collection; Dual (grammatical number); Channel (broadcasting); Business; Computer science; Competition (biology); Industrial organization; Microeconomics; Operations research; Supply chain management; Economics; Marketing; Telecommunications; Engineering","score_opus":0.09263071883780824,"score_gpt":0.3182420939870701,"score_spread":0.22561137514926186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292423539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89570826,0.0012882248,0.0041699647,0.07393459,0.00019872464,0.007263004,0.00007823017,0.00018656986,0.017172446],"genre_scores_gemma":[0.98536456,0.0002485142,0.000276712,0.00054223044,0.00015443028,0.0014969133,0.00019951277,0.000039610746,0.011677549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974602,0.00029450556,0.00032193295,0.0005324671,0.0008833816,0.0005075382],"domain_scores_gemma":[0.99888766,0.0001271441,0.00007616488,0.00034838883,0.00052536005,0.00003526617],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0047131856,0.00020092254,0.00022128543,0.0016898052,0.0015589617,0.00046118023,0.00022261907,0.00004286915,0.00026071942],"category_scores_gemma":[0.00017650472,0.00019445282,0.000038921,0.0019976194,0.00031135234,0.0010321157,0.00090718083,0.00031312898,0.0000091918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089597696,0.0009568839,0.003624824,0.0012714032,0.000393274,0.00011553145,0.003446304,0.037253562,0.000118844786,0.9028691,0.033162218,0.015892068],"study_design_scores_gemma":[0.005917136,0.0011756637,0.04790049,0.00027679646,0.00024264828,0.0000628673,0.3116344,0.4717028,0.0002416041,0.040715285,0.11861131,0.0015189798],"about_ca_topic_score_codex":0.0008878034,"about_ca_topic_score_gemma":0.000260399,"teacher_disagreement_score":0.8621538,"about_ca_system_score_codex":0.000089725945,"about_ca_system_score_gemma":0.000050901974,"threshold_uncertainty_score":0.9997409},"labels":[],"label_agreement":null},{"id":"W4296123388","doi":"10.1007/s10479-022-04961-4","title":"RETRACTED ARTICLE: Periapical dental X-ray image classification using deep neural networks","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":19,"is_retracted":true,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Deep learning; Artificial neural network; Population; Pattern recognition (psychology); Medicine","score_opus":0.17440988700512516,"score_gpt":0.4461366084309839,"score_spread":0.27172672142585874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296123388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946136,0.00035620655,0.0030083577,0.0005223324,0.00028503337,0.00029707473,0.000040140272,0.00003363662,0.0008436292],"genre_scores_gemma":[0.9985467,0.000020993835,0.0007532907,0.00010559176,0.00016189605,0.00006139061,0.00010263502,0.000022857246,0.00022461853],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99712473,0.00075839506,0.0003967366,0.00031026956,0.00095739507,0.00045249143],"domain_scores_gemma":[0.99885666,0.00011801573,0.00003882247,0.0003779328,0.00048259163,0.00012596298],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013192701,0.00010166798,0.00014874991,0.0004002803,0.0012496208,0.00029642,0.00037926235,0.000062453546,0.0018086033],"category_scores_gemma":[0.0002448411,0.00011081133,0.00013179427,0.0015500748,0.00029005326,0.00063935,0.0002490193,0.00097286794,0.00003208602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044511692,0.0016855985,0.06602698,0.000039371575,0.00018044746,0.00029670482,0.0011501478,0.14789388,0.7577744,0.0045608114,0.0081949765,0.011751568],"study_design_scores_gemma":[0.00024314011,0.00009137735,0.12782055,0.0000051148136,0.000007787262,0.00009203523,0.0023538638,0.86614275,0.002865234,0.000030106956,0.00023965735,0.00010836785],"about_ca_topic_score_codex":0.0002482442,"about_ca_topic_score_gemma":0.000079047764,"teacher_disagreement_score":0.75490916,"about_ca_system_score_codex":0.000057070683,"about_ca_system_score_gemma":0.000051648545,"threshold_uncertainty_score":0.9991039},"labels":[],"label_agreement":null},{"id":"W4297200123","doi":"10.1007/s10479-022-04956-1","title":"Location of organ procurement and distribution organisation decisions and their impact on kidney allocations: a developing country perspective","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Organ Donation and Transplantation","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Equity (law); Deliberation; Computer science; Procurement; Perspective (graphical); Resource allocation; Theory of computation; Operations research; Organ procurement; Term (time); Microeconomics; Economics; Business; Risk analysis (engineering); Transplantation; Marketing","score_opus":0.1420152940502252,"score_gpt":0.45418507049591694,"score_spread":0.31216977644569177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297200123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9774127,0.0003781458,0.005627744,0.015133313,0.000021893007,0.00094992685,0.00026702217,0.000016293183,0.00019298258],"genre_scores_gemma":[0.9981046,0.00052661606,0.000246433,0.00023602255,0.00001805915,0.00007323068,0.00071876653,0.000010766932,0.00006553666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.998705,0.00017918528,0.00027071405,0.00020024719,0.0005141814,0.00013061977],"domain_scores_gemma":[0.9973791,0.0001812194,0.00004372008,0.00015162659,0.0021488352,0.00009546365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009285969,0.00008846781,0.00014744025,0.00032279466,0.00048170975,0.000030527535,0.00005460769,0.000035140005,0.00009297968],"category_scores_gemma":[0.0009637035,0.00007089447,0.000019225543,0.0009899097,0.000117134536,0.00014984468,0.000039884126,0.00019306775,0.0000017591193],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027215357,0.0036197936,0.035103682,0.001035362,0.00097591087,0.000008357137,0.05667494,0.0070872046,0.2551145,0.6185456,0.00835495,0.010758166],"study_design_scores_gemma":[0.0039441977,0.0044136196,0.6060555,0.0009325861,0.000096165415,0.00013792152,0.047246877,0.017865287,0.31362015,0.0030261674,0.0022345197,0.00042697706],"about_ca_topic_score_codex":0.00024203231,"about_ca_topic_score_gemma":0.00002606341,"teacher_disagreement_score":0.6155194,"about_ca_system_score_codex":0.0001950084,"about_ca_system_score_gemma":0.0010595828,"threshold_uncertainty_score":0.37049708},"labels":[],"label_agreement":null},{"id":"W4300865761","doi":"10.1007/s10479-022-04991-y","title":"ORESTE-SORT: a novel multiple criteria sorting method for sorting port group competitiveness","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Sorting; sort; Theory of computation; Computer science; Port (circuit theory); Sorting algorithm; ELECTRE; Operations research; Generalization; Mathematical optimization; Mathematics; Algorithm; Engineering; Information retrieval; Multiple-criteria decision analysis","score_opus":0.25668775079262823,"score_gpt":0.4617255908704096,"score_spread":0.20503784007778136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300865761","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1275624,0.00036832396,0.8590274,0.0011388257,0.0004162669,0.0016721251,0.0010817422,0.00019082177,0.008542081],"genre_scores_gemma":[0.95286417,0.000027152302,0.045451913,0.000068136185,0.00012312381,0.00056241296,0.000301195,0.00004528,0.000556636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981734,0.0001368845,0.0005291968,0.00023618732,0.00045440655,0.000469934],"domain_scores_gemma":[0.9985227,0.0005034202,0.000032345146,0.00026874736,0.0005860409,0.00008675626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034250065,0.000116761046,0.0002413224,0.00025301313,0.0007469525,0.000095378986,0.00026172484,0.000042455616,0.00079494383],"category_scores_gemma":[0.0009187728,0.00012747878,0.0000883222,0.00038537694,0.00006656617,0.00013555882,0.00020934617,0.00033957182,0.0000023048635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000747182,0.0004843079,0.003379755,0.00049188745,0.00014844224,0.000022911441,0.0012934171,0.8452232,0.0799761,0.051081594,0.0032845156,0.014539144],"study_design_scores_gemma":[0.00036662442,0.00015870044,0.0023113168,0.000028526116,0.00000757196,0.000011625985,0.0008607926,0.965066,0.0059927246,0.0003163765,0.024686452,0.00019328027],"about_ca_topic_score_codex":0.00054578745,"about_ca_topic_score_gemma":0.00023021697,"teacher_disagreement_score":0.82530177,"about_ca_system_score_codex":0.000031496365,"about_ca_system_score_gemma":0.000086320026,"threshold_uncertainty_score":0.8704077},"labels":[],"label_agreement":null},{"id":"W4304203128","doi":"10.1007/s10479-022-04595-6","title":"Optimal pricing in the presence of IoT investment and quality-dependent demand","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; American University of Sharjah","keywords":"Stackelberg competition; Supply chain; Context (archaeology); Revenue; Quality (philosophy); Computer science; Internet of Things; Investment (military); Supply chain management; Business; Industrial organization; Marketing; Microeconomics; Computer security; Economics; Finance","score_opus":0.2587012909470079,"score_gpt":0.41643591644433464,"score_spread":0.15773462549732675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304203128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9815987,0.00036540485,0.000049542294,0.006483743,0.00003923297,0.000600656,0.00000440548,0.0000054562665,0.01085289],"genre_scores_gemma":[0.99778426,0.00005373192,0.00008510942,0.0012615914,0.00006181876,0.0001589285,0.000010190036,0.000006173728,0.0005782048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817324,0.00026005995,0.00032297848,0.00017976564,0.0008479034,0.00021608164],"domain_scores_gemma":[0.9993247,0.0001429959,0.00004621118,0.0002637814,0.00021366475,0.000008681244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059512574,0.000064600004,0.00012229728,0.00044577007,0.0003808012,0.00012145413,0.00039051916,0.000013926512,0.00026257115],"category_scores_gemma":[0.00029729586,0.000051503404,0.000028475408,0.0006897627,0.00012965592,0.00026576978,0.0006450252,0.00020353196,0.0000047212584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015075492,0.0012572708,0.024349857,0.0006359204,0.00008025038,0.000018951527,0.0066460115,0.20809154,0.00420417,0.7321238,0.020279242,0.002162251],"study_design_scores_gemma":[0.0043021124,0.0010096622,0.189914,0.0003324119,0.000059981132,0.000008432847,0.17883877,0.34486958,0.007869925,0.010850496,0.2608511,0.0010935412],"about_ca_topic_score_codex":0.0028653909,"about_ca_topic_score_gemma":0.00033728252,"teacher_disagreement_score":0.7212733,"about_ca_system_score_codex":0.000013964521,"about_ca_system_score_gemma":0.000034244553,"threshold_uncertainty_score":0.4331633},"labels":[],"label_agreement":null},{"id":"W4306359307","doi":"10.1007/s10479-022-04993-w","title":"Robust multivariate adaptive regression splines under cross-polytope uncertainty: an application in a natural gas market","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Robustification; Multivariate adaptive regression splines; Computer science; Robust optimization; Mathematical optimization; Curse of dimensionality; Interpretability; Uncertainty quantification; Mars Exploration Program; Univariate; Multivariate statistics; Exploit; Nonparametric regression; Regression analysis; Machine learning; Mathematics; Artificial intelligence; Outlier","score_opus":0.4183602756074331,"score_gpt":0.5421433808573288,"score_spread":0.12378310524989572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306359307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803088,0.00046568664,0.009454942,0.005605661,0.00018771974,0.0010570948,0.00012285734,0.000027978238,0.0027692884],"genre_scores_gemma":[0.9914051,0.00028253844,0.0022747118,0.00013670692,0.0000727643,0.00026430658,0.00012941408,0.000016208623,0.0054182243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941353,0.0017997038,0.000787994,0.00063739624,0.0022399956,0.0003995995],"domain_scores_gemma":[0.9959175,0.0007437966,0.00011998159,0.0007911515,0.0023068364,0.0001207165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009927142,0.00013632553,0.0002546232,0.0011197458,0.0010330998,0.00034913418,0.0009164354,0.00007408554,0.0008571007],"category_scores_gemma":[0.001593566,0.0001056358,0.00007504711,0.0031367696,0.00022997057,0.0009414436,0.0004243393,0.0005525182,0.000030998955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044867903,0.00027799123,0.0040282696,0.0000013889959,0.000008313987,0.0000043411633,0.00087011117,0.96368,0.0011084233,0.0051037045,0.004167893,0.020300847],"study_design_scores_gemma":[0.00040414237,0.00021847757,0.034833882,0.000011204924,0.0000014801991,0.000004570777,0.0030078113,0.95266926,0.0005989648,0.0051041273,0.0030117987,0.00013426834],"about_ca_topic_score_codex":0.003430735,"about_ca_topic_score_gemma":0.002354318,"teacher_disagreement_score":0.030805614,"about_ca_system_score_codex":0.000070859016,"about_ca_system_score_gemma":0.0003861922,"threshold_uncertainty_score":0.9384652},"labels":[],"label_agreement":null},{"id":"W4308261395","doi":"10.1007/s10479-022-05009-3","title":"Pricing decisions of organic and conventional products in a dual-channel competitive food supply chain","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Supply chain; Channel (broadcasting); Dual (grammatical number); Business; Revenue; Industrial organization; Organic product; Channel coordination; Product (mathematics); Supply chain management; Agriculture; Environmental economics; Computer science; Marketing; Economics; Telecommunications; Mathematics","score_opus":0.16977889928062778,"score_gpt":0.35191420047887007,"score_spread":0.18213530119824228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308261395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98390085,0.00035676715,0.000099519195,0.009215813,0.00010618959,0.0008675619,0.000027767011,0.000013152356,0.005412382],"genre_scores_gemma":[0.9986486,0.000112039554,0.00008252827,0.0003121932,0.000097382734,0.00013703061,0.00008119039,0.000013778262,0.00051524973],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983732,0.000109344655,0.00035347856,0.00026184838,0.00064450933,0.0002576266],"domain_scores_gemma":[0.99899703,0.00015129041,0.000053189582,0.00020552603,0.0005788794,0.000014067773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023407233,0.00008540733,0.00017156216,0.0010439679,0.00039070097,0.00007598395,0.00016120939,0.00001951711,0.0009104577],"category_scores_gemma":[0.000775987,0.00008883996,0.000035618392,0.0014708582,0.00014033754,0.0004006056,0.0006953369,0.0002134231,0.00001209447],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025058523,0.002484958,0.012052677,0.00056860544,0.00019864764,0.000045861034,0.0025949306,0.010717007,0.0103756515,0.93577826,0.022363316,0.0025695288],"study_design_scores_gemma":[0.013311355,0.0036101404,0.19013047,0.0016308342,0.000120852084,0.00005380627,0.1808412,0.21262023,0.026299486,0.057183444,0.31169736,0.0025008263],"about_ca_topic_score_codex":0.00037400186,"about_ca_topic_score_gemma":0.00059330434,"teacher_disagreement_score":0.8785948,"about_ca_system_score_codex":0.00002424875,"about_ca_system_score_gemma":0.00009217675,"threshold_uncertainty_score":0.9968873},"labels":[],"label_agreement":null},{"id":"W4308967276","doi":"10.1007/s10479-022-05059-7","title":"Co-movements, option pricing and risk management: an application to WTI versus Brent spread options","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Università della Calabria","keywords":"Econometrics; Greeks; Portfolio; Skewness; Volatility (finance); Bivariate analysis; Risk management; Economics; Project portfolio management; Probability distribution; Value at risk; Financial economics; Mathematics; Finance; Statistics","score_opus":0.21671117350521446,"score_gpt":0.41618152219634086,"score_spread":0.1994703486911264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308967276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9494358,0.00072749524,0.043871053,0.0006271611,0.00007633955,0.0007941188,0.00039356528,0.000017297523,0.004057187],"genre_scores_gemma":[0.9940239,0.0022223378,0.002793768,0.000047903788,0.000039837018,0.00036958884,0.00012587893,0.000012711741,0.000364035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987484,0.00008867166,0.0004001584,0.00037188435,0.00014517183,0.00024571322],"domain_scores_gemma":[0.9993263,0.000041833508,0.0000540656,0.00036236047,0.00012780055,0.0000876651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022578966,0.00007333833,0.00014494748,0.000542912,0.0009967061,0.000089820554,0.00021024194,0.000028453956,0.00010459483],"category_scores_gemma":[0.00009206678,0.0000966387,0.00003473109,0.0005670775,0.000040275903,0.00028565427,0.00015569414,0.00021495986,0.000055581506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018368078,0.00050204404,0.010576222,0.000036252277,0.000073180854,7.7956184e-7,0.0021361737,0.19914693,0.00025807606,0.7487607,0.00055450684,0.037771452],"study_design_scores_gemma":[0.0015163228,0.0015796233,0.08437115,0.000023686745,0.000012551125,9.988161e-7,0.0032639445,0.79819405,0.00075899914,0.025467427,0.08433188,0.00047934343],"about_ca_topic_score_codex":0.0025321753,"about_ca_topic_score_gemma":0.00025927112,"teacher_disagreement_score":0.7232933,"about_ca_system_score_codex":0.00006930373,"about_ca_system_score_gemma":0.000020323783,"threshold_uncertainty_score":0.7665958},"labels":[],"label_agreement":null},{"id":"W4309231192","doi":"10.1007/s10479-022-05051-1","title":"Theory, computation, and practice of multiobjective optimisation","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Computation; Computer science; Mathematical optimization; Multi-objective optimization; Mathematical economics; Mathematics; Algorithm","score_opus":0.15642541301236748,"score_gpt":0.4730439202187418,"score_spread":0.3166185072063743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309231192","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003762915,0.00022164322,0.9900854,0.0027654872,0.00005337499,0.00048658825,0.00002261217,0.000025314348,0.0025766403],"genre_scores_gemma":[0.59180653,0.00010299983,0.40756777,0.00012853791,0.000011198388,0.00009923083,0.000013404142,0.00000813693,0.00026217184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969598,0.0015761781,0.00029688003,0.00029338032,0.0006976895,0.00017604078],"domain_scores_gemma":[0.99499625,0.0015559279,0.00008315506,0.0002813209,0.003028128,0.00005522506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033327362,0.00007240698,0.00013009651,0.00043515113,0.00060222804,0.00006262018,0.00034887763,0.00002296695,0.000039635604],"category_scores_gemma":[0.002644317,0.00007755129,0.000027890203,0.0011820613,0.00020998668,0.0010317358,0.0004886177,0.00022883575,0.0000027225412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005170589,0.00027189424,0.000016657848,0.000007780975,0.000031077823,0.0000019915672,0.0052075023,0.85670286,0.0014577765,0.11752149,0.0001390881,0.018590195],"study_design_scores_gemma":[0.00049579644,0.0004769642,0.0006802368,0.000007852172,0.0000034088723,0.000030587722,0.00426658,0.97968817,0.008062981,0.0054052696,0.0007660051,0.00011613152],"about_ca_topic_score_codex":0.000093955365,"about_ca_topic_score_gemma":0.0000044013227,"teacher_disagreement_score":0.58804363,"about_ca_system_score_codex":0.00003879579,"about_ca_system_score_gemma":0.00021110498,"threshold_uncertainty_score":0.4631912},"labels":[],"label_agreement":null},{"id":"W4311730047","doi":"10.1007/s10479-022-05120-5","title":"A Stackelberg order execution game","year":2022,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Stackelberg competition; Nash equilibrium; Trading strategy; Computer science; Mathematical economics; Theory of computation; Order (exchange); Algorithmic trading; Portfolio; Sequential game; Price of anarchy; Game theory; Economics; Price of stability; Finance","score_opus":0.30203348473901453,"score_gpt":0.3929325921101922,"score_spread":0.09089910737117768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311730047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81370425,0.0027383238,0.00038581953,0.010357829,0.0002163515,0.0004624597,0.00039924314,0.000021353573,0.17171437],"genre_scores_gemma":[0.99129313,0.00053481513,0.00022512893,0.0002876243,0.000044189772,0.0001760789,0.000048431375,0.000010891142,0.007379729],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893194,0.00008503101,0.00036474346,0.0002229142,0.0001232578,0.0002721199],"domain_scores_gemma":[0.999371,0.000040014238,0.00003920851,0.0002621757,0.00024418888,0.00004339935],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017029392,0.00006106324,0.000158999,0.00039255616,0.00047142067,0.00007659042,0.0002305059,0.000027342236,0.003858149],"category_scores_gemma":[0.0002797627,0.00007146584,0.00005055047,0.0008241262,0.00011451696,0.00027100113,0.00015697749,0.00022969491,0.00016162703],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020796193,0.00017206802,0.00073627545,0.0000099584395,0.000015822348,0.0000015647637,0.00045644262,0.0033138173,0.00011975436,0.97270244,0.022144645,0.00030643743],"study_design_scores_gemma":[0.00050057255,0.0010138726,0.021814879,0.000010918079,0.0000015069472,0.0000036693539,0.0014895031,0.016022168,0.00087486854,0.13110697,0.8268528,0.00030828756],"about_ca_topic_score_codex":0.0012531036,"about_ca_topic_score_gemma":0.00006256578,"teacher_disagreement_score":0.8415955,"about_ca_system_score_codex":0.000035418572,"about_ca_system_score_gemma":0.00010699967,"threshold_uncertainty_score":0.99705243},"labels":[],"label_agreement":null},{"id":"W4317207528","doi":"10.1007/s10479-023-05171-2","title":"Continuous review (s, Q) inventory system at a service facility with positive order lead times","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"National Board for Higher Mathematics","keywords":"Lead time; Operations research; Poisson distribution; Computer science; Random variable; Markov chain; Queueing theory; Joint probability distribution; Service (business); Exponential distribution; Queue; Stockout; Mathematical optimization; Operations management; Statistics; Mathematics; Business; Economics; Computer network; Marketing","score_opus":0.1318013077925689,"score_gpt":0.391614083969483,"score_spread":0.2598127761769141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317207528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89753705,0.0057398314,0.00059160945,0.04729348,0.00009103663,0.0027781026,0.00015737326,0.0005899729,0.045221556],"genre_scores_gemma":[0.9829358,0.0008183292,0.00011311401,0.002714632,0.00017226374,0.00023602248,0.00054069696,0.000033940116,0.012435201],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823946,0.00017388912,0.0003121018,0.00031444774,0.0006058295,0.00035429164],"domain_scores_gemma":[0.99570906,0.00012326363,0.000063976404,0.0004555099,0.0036275925,0.000020569261],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0026254924,0.00012707054,0.00031260474,0.00040943502,0.0005274466,0.00010867856,0.00030438026,0.000041007894,0.00034547594],"category_scores_gemma":[0.0006212195,0.00010268001,0.00006221119,0.003608102,0.00014090478,0.00075523654,0.00031455187,0.00017984898,0.002324591],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017525823,0.0012962903,0.013885715,0.052401707,0.002847137,0.0005163605,0.0024284357,0.12623586,0.010725878,0.29455635,0.47456577,0.018787943],"study_design_scores_gemma":[0.003945598,0.0006009163,0.008655052,0.03190393,0.0010455798,0.0000502561,0.022503205,0.5305516,0.0103583615,0.003945069,0.3828216,0.0036188406],"about_ca_topic_score_codex":0.0010661402,"about_ca_topic_score_gemma":0.001073387,"teacher_disagreement_score":0.40431577,"about_ca_system_score_codex":0.000038307702,"about_ca_system_score_gemma":0.00006772562,"threshold_uncertainty_score":0.9984522},"labels":[],"label_agreement":null},{"id":"W4319224593","doi":"10.1007/s10479-023-05208-6","title":"Innovation in humanitarian logistics and supply chain management: a systematic review","year":2023,"lang":"en","type":"review","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Red Cross Society","funders":"","keywords":"Supply chain; Business; Humanitarian Logistics; Beneficiary; Supply chain management; Context (archaeology); Humanitarian aid; Position (finance); Industrial organization; Knowledge management; Marketing; Economics; Economic growth; Computer science","score_opus":0.49426457206077196,"score_gpt":0.4857105513754828,"score_spread":0.008554020685289154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319224593","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000057958573,0.9892394,0.00007285904,0.0013202265,0.000096674004,0.005474113,0.00002492702,0.00004739455,0.0037186313],"genre_scores_gemma":[0.00008989027,0.99401546,0.00003430004,0.0004392403,0.00009175791,0.0013445282,0.0006186139,0.00003850884,0.003327721],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9964284,0.00021192407,0.0018255352,0.00044426895,0.00070353225,0.00038639706],"domain_scores_gemma":[0.9981528,0.00008231173,0.00011937722,0.0006434205,0.0009887415,0.000013350695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070806486,0.00026404695,0.0012277738,0.0033123016,0.00023775377,0.00027199896,0.0005315027,0.00011037363,0.00014501231],"category_scores_gemma":[0.0018598699,0.00023124859,0.000112051865,0.006006867,0.00011301927,0.0004438329,0.0005257139,0.0003578826,0.00076088123],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.67742e-7,0.00006469858,8.211462e-7,0.7854795,0.000091221955,0.000008007182,0.000018671168,0.000071645096,1.8449683e-8,0.19918203,0.004779775,0.010302722],"study_design_scores_gemma":[0.0001375276,0.000020134737,0.000020899752,0.6144471,0.00045256873,0.00000130141,0.00033890095,0.0029488048,5.0688033e-8,0.001121367,0.38009557,0.00041572694],"about_ca_topic_score_codex":0.0012562794,"about_ca_topic_score_gemma":0.0020684171,"teacher_disagreement_score":0.37531582,"about_ca_system_score_codex":0.000041044328,"about_ca_system_score_gemma":0.00006465046,"threshold_uncertainty_score":0.97798425},"labels":[],"label_agreement":null},{"id":"W4323048157","doi":"10.1007/s10479-023-05225-5","title":"RETRACTED ARTICLE: Assessment of airline industry using a new double-frontier cross-efficiency method based on prospect theory","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":10,"is_retracted":true,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Viewpoints; Ranking (information retrieval); Frontier; Data envelopment analysis; Pairwise comparison; Computer science; Theory of computation; Efficient frontier; Operations research; Pessimism; Econometrics; Microeconomics; Management science; Economics; Artificial intelligence; Mathematics; Mathematical optimization; Algorithm; Political science; Financial economics; Epistemology","score_opus":0.5773306934951713,"score_gpt":0.6540406258013872,"score_spread":0.07670993230621592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323048157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90686446,0.0000461801,0.085295506,0.0036150245,0.00010481033,0.0005298763,0.000035788133,0.000041933097,0.0034664297],"genre_scores_gemma":[0.9790407,0.000006551903,0.015542093,0.00011576743,0.00008369463,0.000017284945,0.000011751632,0.000020289717,0.005161892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.990202,0.0019715468,0.0013545208,0.0007513533,0.005079799,0.00064075505],"domain_scores_gemma":[0.99047524,0.0030978231,0.00019108265,0.0014609236,0.0045530456,0.00022190517],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04223083,0.00017137658,0.0004813888,0.0024369885,0.0006313916,0.000504099,0.0011919766,0.00031046045,0.0011481125],"category_scores_gemma":[0.011918558,0.00013019204,0.00022027534,0.012779277,0.00051625405,0.0004730982,0.00024422616,0.0011875706,0.000084025116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014526742,0.0005947612,0.012531772,0.000009468459,0.000035210698,0.000009342681,0.00035138775,0.9497682,0.020697275,0.008957188,0.0030720155,0.0038281288],"study_design_scores_gemma":[0.00052774954,0.0002878205,0.04536012,0.000060945462,0.000011169423,0.0000011438319,0.0004314533,0.9094848,0.041122362,0.002397892,0.00018983251,0.00012472768],"about_ca_topic_score_codex":0.00038176516,"about_ca_topic_score_gemma":0.00005122203,"teacher_disagreement_score":0.072176225,"about_ca_system_score_codex":0.000063209234,"about_ca_system_score_gemma":0.0021033117,"threshold_uncertainty_score":0.999765},"labels":[],"label_agreement":null},{"id":"W4353084216","doi":"10.1007/s10479-023-05273-x","title":"Evaluating the optimal timing and capacity of investments in flexible combined heat and power generation for energy-intensive industries","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Hellenic Academic Libraries Link; Egg Farmers of Canada","keywords":"Flexibility (engineering); Electricity; Computer science; Grid; Investment (military); Electric power system; Environmental economics; Electricity generation; Operations research; Economics; Risk analysis (engineering); Operations management; Business; Industrial organization; Power (physics); Engineering","score_opus":0.6164744142417679,"score_gpt":0.462111851786936,"score_spread":0.15436256245483188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353084216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945211,0.0019523724,0.00005610765,0.003025425,0.000021801015,0.0002266348,0.000066766894,0.0000035477924,0.00012625993],"genre_scores_gemma":[0.99699634,0.0016859854,0.00032200848,0.00012142457,0.00001671413,0.00007400245,0.00004871382,0.000006283983,0.00072851544],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991834,0.00006620096,0.0003412128,0.00017615341,0.00007251458,0.00016052139],"domain_scores_gemma":[0.9992242,0.00017832735,0.000035950703,0.00012995956,0.00039961716,0.000031976026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020857854,0.0000563941,0.00018367553,0.00044310917,0.00022100337,0.00006715401,0.00006890402,0.00004982348,0.000020034884],"category_scores_gemma":[0.0008716047,0.000048521648,0.000030162482,0.0005788985,0.00019964042,0.00018620926,0.00007272713,0.00008270968,0.000002427417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085975575,0.000100653415,0.0102595575,0.000031689513,0.00016092925,5.6575544e-7,0.0057965205,0.023444567,0.009759778,0.945554,0.0041712318,0.00063449435],"study_design_scores_gemma":[0.0005781085,0.0005742101,0.012468898,0.000026039308,0.0000061025085,5.067643e-7,0.0020722651,0.9482253,0.024017956,0.011690811,0.00023448977,0.00010530396],"about_ca_topic_score_codex":0.0016399275,"about_ca_topic_score_gemma":0.00020091934,"teacher_disagreement_score":0.9338632,"about_ca_system_score_codex":0.000012080031,"about_ca_system_score_gemma":0.00003348149,"threshold_uncertainty_score":0.24790907},"labels":[],"label_agreement":null},{"id":"W4367044514","doi":"10.1007/s10479-023-05344-z","title":"Editorial: Big data and data science in sport","year":2023,"lang":"en","type":"editorial","venue":"Annals of Operations Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Theory of computation; Big data; Computer science; Data science; Sports science; Political science; Data mining; Algorithm","score_opus":0.5460397729967867,"score_gpt":0.5238002129400025,"score_spread":0.02223956005678429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367044514","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058594876,0.0002297801,0.00001700851,0.0014621281,0.99469453,0.00034624804,0.0015519268,0.00003605855,0.0010763989],"genre_scores_gemma":[0.00192815,0.0034115566,0.00004388703,0.000026597663,0.98102367,0.000022836555,0.012918837,0.000041688116,0.00058279093],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99433124,0.000023583321,0.00057612703,0.0013229479,0.0030962862,0.0006498298],"domain_scores_gemma":[0.9904825,0.0005483672,0.00010384309,0.0042927163,0.0045357333,0.00003686073],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.013990562,0.00020791369,0.00037210935,0.0019958708,0.0004982293,0.0016649503,0.007168839,0.00034646978,0.000055811754],"category_scores_gemma":[0.022351755,0.00019023163,0.000016148875,0.004519108,0.0010324307,0.006046849,0.012620369,0.001065631,0.00026775134],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022845987,0.00007190203,0.00016590265,0.00025326398,0.000008448203,0.0000068540594,0.000010928939,0.000017938875,0.00003798114,0.00045475873,0.99338275,0.005566423],"study_design_scores_gemma":[0.00009422728,0.0000084562935,0.00019701553,0.0002682317,0.000008717625,1.1999823e-7,0.00009054691,0.0055845384,0.000013141586,0.00014584455,0.99339825,0.00019088542],"about_ca_topic_score_codex":0.015381372,"about_ca_topic_score_gemma":0.008085001,"teacher_disagreement_score":0.013670846,"about_ca_system_score_codex":0.000017905493,"about_ca_system_score_gemma":0.0015477514,"threshold_uncertainty_score":0.9993714},"labels":[],"label_agreement":null},{"id":"W4376635848","doi":"10.1007/s10479-023-05386-3","title":"Assessing the potential of plastic waste management in the circular economy: a longitudinal case study in an emerging economy","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Natural Science Foundation of China","keywords":"Circular economy; Theory of computation; Business management; Economics; Economy; Business; Computer science","score_opus":0.19658187252923973,"score_gpt":0.43893425368662053,"score_spread":0.2423523811573808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376635848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997693,0.000012710775,0.0004775096,0.0003871913,0.000028685532,0.00046758234,0.000005057086,0.0000026709642,0.00092560455],"genre_scores_gemma":[0.9998242,0.000015696953,0.000031949956,0.000014635148,0.000018170971,0.000060767066,0.0000049859523,0.0000050916547,0.00002447568],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985556,0.00043033357,0.0003053587,0.00020755254,0.0002327875,0.00026835085],"domain_scores_gemma":[0.99940497,0.00024148918,0.000026320247,0.00026358364,0.00003244603,0.000031218053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030023833,0.00006692449,0.00009779174,0.00025636284,0.00028526658,0.0001471818,0.00028747445,0.000021140626,0.00015094977],"category_scores_gemma":[0.000073754876,0.00004689118,0.000029404528,0.0007994975,0.00015006878,0.00034511797,0.00019392557,0.00018271759,0.00003219646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014869908,0.0005676373,0.057408225,0.000034185694,0.000038947113,0.0008517513,0.0043650554,0.9324728,0.0013324866,0.000677927,0.0002686407,0.0019674269],"study_design_scores_gemma":[0.0004520795,0.000245945,0.35007536,0.000030246134,0.000014195523,0.00004836517,0.06345994,0.58486456,0.00018190635,0.00041186452,0.00010369335,0.00011181749],"about_ca_topic_score_codex":0.0020636865,"about_ca_topic_score_gemma":0.0025997404,"teacher_disagreement_score":0.34760827,"about_ca_system_score_codex":0.00003429919,"about_ca_system_score_gemma":0.000033780656,"threshold_uncertainty_score":0.31196904},"labels":[],"label_agreement":null},{"id":"W4380153691","doi":"10.1007/s10479-023-05397-0","title":"Integrated optimal scheduling and routing of repair crew and relief vehicles after disaster: a novel hybrid solution approach","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Crew; Computer science; Scheduling (production processes); Mathematical optimization; Benders' decomposition; Integer programming; Theory of computation; Routing (electronic design automation); Vehicle routing problem; Heuristic; Decomposition; Operations research; Algorithm; Engineering; Mathematics; Computer network","score_opus":0.17577220313584024,"score_gpt":0.36339388753366053,"score_spread":0.1876216843978203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380153691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99281555,0.0001933096,0.003329565,0.002285231,0.000031049876,0.0003273103,0.0000118397675,0.00006416158,0.00094199076],"genre_scores_gemma":[0.99697334,0.00019438061,0.0021091108,0.000092533395,0.000062709165,0.00005996482,0.00007774739,0.000010962074,0.00041923634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987275,0.000035368565,0.00035625513,0.00027379446,0.00035052336,0.00025655134],"domain_scores_gemma":[0.99902356,0.000028783865,0.000022177299,0.00020722554,0.00069928274,0.000018997636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001968985,0.000094407165,0.00014894597,0.0005098979,0.00026295622,0.00014366573,0.00010884855,0.000034148517,0.00003779077],"category_scores_gemma":[0.00049952616,0.000087311084,0.00004317262,0.0008779081,0.00018284496,0.000685959,0.0003406625,0.00013973918,0.000022572138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015487447,0.0035936118,0.05259718,0.010593882,0.0010283483,0.00002490665,0.010021826,0.5612902,0.06431728,0.2047396,0.028731924,0.061512485],"study_design_scores_gemma":[0.00021740393,0.000026174712,0.016540755,0.00009256896,0.000010055206,6.2409174e-7,0.002631445,0.9787917,0.00028525712,0.00005470271,0.0012499039,0.00009938825],"about_ca_topic_score_codex":0.00242863,"about_ca_topic_score_gemma":0.00020729171,"teacher_disagreement_score":0.4175015,"about_ca_system_score_codex":0.0000069395346,"about_ca_system_score_gemma":0.000028244127,"threshold_uncertainty_score":0.36713782},"labels":[],"label_agreement":null},{"id":"W4384662317","doi":"10.1007/s10479-023-05500-5","title":"Cryptocurrency markets, macroeconomic news announcements and energy consumption","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Brock University","funders":"","keywords":"Cryptocurrency; Liberian dollar; Consumption (sociology); Volume (thermodynamics); Economics; Monetary economics; Carbon footprint; Index (typography); Footprint; Financial economics; Econometrics; Computer science; Finance; Computer security","score_opus":0.15509522910243845,"score_gpt":0.41539369290387507,"score_spread":0.2602984638014366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384662317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9229324,0.0013899158,0.041937333,0.029614674,0.00012338553,0.0004034356,0.00007053316,0.0002876785,0.0032406808],"genre_scores_gemma":[0.99022967,0.0060838023,0.0024518294,0.00014069316,0.000020879905,0.00022276375,0.000035778237,0.0000056070267,0.00080900086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988692,0.00012542264,0.00022271548,0.00030707082,0.00019485701,0.0002807516],"domain_scores_gemma":[0.9989664,0.00010443234,0.000020134343,0.00052342215,0.00032166185,0.000063944135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000982142,0.000067293586,0.0001037601,0.0004825039,0.0003768709,0.00011016281,0.00053910277,0.0000753077,0.000055745913],"category_scores_gemma":[0.00007388846,0.00006811855,0.000022967379,0.0007738474,0.00022392138,0.00026157007,0.00041328353,0.00014869666,0.0001059709],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005619262,0.00009709434,0.0017109799,0.000019724295,0.00002412659,0.0000024043024,0.00024994943,0.000083943516,0.0022860218,0.8218321,0.027192665,0.14649533],"study_design_scores_gemma":[0.0009008818,0.0004064235,0.046537727,0.00007253749,0.000005125128,0.00002233904,0.00033508328,0.59546256,0.018729694,0.095551744,0.24142328,0.000552599],"about_ca_topic_score_codex":0.00019512336,"about_ca_topic_score_gemma":0.00012560863,"teacher_disagreement_score":0.7262804,"about_ca_system_score_codex":0.0000098169685,"about_ca_system_score_gemma":0.00008485706,"threshold_uncertainty_score":0.28986245},"labels":[],"label_agreement":null},{"id":"W4385271570","doi":"10.1007/s10479-023-05525-w","title":"Extended replacement policy for a system under shocks effect","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Shock (circulatory); Generalization; Unit (ring theory); Theory of computation; Catastrophic failure; Minor (academic); Computer science; Mathematics; Physics; Mathematical analysis; Algorithm; Thermodynamics","score_opus":0.1204904495290139,"score_gpt":0.4389525915870206,"score_spread":0.3184621420580067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385271570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82675606,0.00040557247,0.13486128,0.011525613,0.000455096,0.0056501646,0.00018568234,0.0010664893,0.019094046],"genre_scores_gemma":[0.99686056,0.0002546852,0.00051941903,0.000018992478,0.000079968326,0.0005851842,0.00006520699,0.000021224296,0.001594734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998967,0.00009835537,0.00021205713,0.00014430839,0.00025623426,0.00032203065],"domain_scores_gemma":[0.9989531,0.00021303921,0.0000058320948,0.00029111616,0.00048072674,0.000056195884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018044258,0.00006958536,0.00012894711,0.00037949637,0.00017111683,0.000053917334,0.00012161876,0.000058180573,0.000014908605],"category_scores_gemma":[0.00048647885,0.00006175839,0.00005688802,0.0008348505,0.000046319587,0.00011831948,0.00003540003,0.000098521996,0.00004924653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046430527,0.000019274556,0.0000140106995,0.00042752016,0.000040328898,5.257967e-7,0.00019286305,0.94313914,0.003122269,0.035815254,0.015778806,0.0014035902],"study_design_scores_gemma":[0.00032573834,0.00033251694,0.00038511446,0.00009402991,0.0000031038305,0.0000011588792,0.00044563613,0.9721918,0.02394815,0.00043947695,0.0017495062,0.00008378207],"about_ca_topic_score_codex":0.00009043972,"about_ca_topic_score_gemma":0.000027392309,"teacher_disagreement_score":0.17010452,"about_ca_system_score_codex":0.000068942165,"about_ca_system_score_gemma":0.00008031926,"threshold_uncertainty_score":0.2518434},"labels":[],"label_agreement":null},{"id":"W4385970884","doi":"10.1007/s10479-023-05464-6","title":"Modeling the impact of IoT technology on food supply chain operations","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Product (mathematics); Business; Food waste; Environmental economics; Investment (military); Internet of Things; Quality (philosophy); Sustainability; Industrial organization; Supply chain management; Resilience (materials science); Food chain; Computer science; Marketing; Economics; Computer security; Waste management; Engineering","score_opus":0.24903448744701578,"score_gpt":0.44969558985383157,"score_spread":0.20066110240681578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385970884","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96743125,0.00006575333,0.000004521648,0.031772546,0.000016288865,0.00036827743,0.00007565494,0.000029088389,0.0002366066],"genre_scores_gemma":[0.99933535,0.00012051739,0.000015090152,0.000019294816,0.000050652845,0.00006423834,0.0000314892,9.329797e-7,0.00036244455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875194,0.0002403074,0.00023272555,0.00017697598,0.00031454416,0.000283495],"domain_scores_gemma":[0.99860513,0.00014188347,0.000008783225,0.00014661333,0.0010483502,0.000049255377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012726351,0.00006827553,0.00012224657,0.0001369169,0.000540474,0.000045284665,0.00031191987,0.00007721603,0.0001218072],"category_scores_gemma":[0.00069344725,0.000022760416,0.00010586179,0.002306906,0.00022161454,0.00006175729,0.000098730765,0.00022418109,0.000013778452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044351134,0.00032006614,0.0005818669,0.000008957506,0.000050888597,7.046554e-7,0.00049147184,0.84579927,0.091812514,0.018051405,0.0015226903,0.041315798],"study_design_scores_gemma":[0.0002246228,0.0070129177,0.023750128,0.000051702555,0.0000042262677,0.000006077268,0.074367635,0.8456598,0.04304362,0.005252302,0.00039140703,0.00023554442],"about_ca_topic_score_codex":0.0014865658,"about_ca_topic_score_gemma":0.0009977302,"teacher_disagreement_score":0.073876165,"about_ca_system_score_codex":0.000018330826,"about_ca_system_score_gemma":0.00008796567,"threshold_uncertainty_score":0.4156944},"labels":[],"label_agreement":null},{"id":"W4386689328","doi":"10.1007/s10479-023-05564-3","title":"The use of multi-criteria decision-making methods in project portfolio selection: a literature review and future research directions","year":2023,"lang":"en","type":"review","venue":"Annals of Operations Research","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Selection (genetic algorithm); Portfolio; Management science; Computer science; Project portfolio management; Operations research; Engineering; Artificial intelligence; Systems engineering; Business; Project management; Finance","score_opus":0.8088985225331905,"score_gpt":0.7092712999237242,"score_spread":0.09962722260946633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386689328","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011388159,0.9947883,0.00014727602,0.0010105484,0.00033069437,0.0031782202,0.00010814312,0.000021966427,0.00040346876],"genre_scores_gemma":[0.0000021725743,0.97997737,0.012494529,0.000029519064,0.000211828,0.0007684184,0.000021127327,0.000035675173,0.0064593633],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9849396,0.008516737,0.002476071,0.000927334,0.0024747644,0.00066554494],"domain_scores_gemma":[0.97807634,0.013746807,0.0002956594,0.0012650653,0.006531027,0.00008509441],"candidate_categories":["metaresearch","bibliometrics","sts","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04821091,0.00030489787,0.0014429064,0.00599344,0.0014014569,0.0015258677,0.0012842868,0.00030970285,0.00022803314],"category_scores_gemma":[0.022894762,0.00018224427,0.00036365737,0.028195836,0.0006299621,0.0009879944,0.0009529958,0.0018957903,0.00003545025],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014974427,0.00004948252,0.000012669708,0.00395262,0.00007602653,0.0000050811,0.00023558897,0.000005087094,5.671091e-7,0.0009917007,0.038403574,0.95625263],"study_design_scores_gemma":[0.000065244676,0.000080220605,0.000058233793,0.02407669,0.000039553346,0.000043875894,0.00028955098,0.0010682109,0.0000012223567,0.00030662282,0.9738175,0.00015304596],"about_ca_topic_score_codex":0.00017433696,"about_ca_topic_score_gemma":0.0013100256,"teacher_disagreement_score":0.95609957,"about_ca_system_score_codex":0.000057079375,"about_ca_system_score_gemma":0.0011928133,"threshold_uncertainty_score":0.9998986},"labels":[],"label_agreement":null},{"id":"W4387770819","doi":"10.1007/s10479-023-05630-w","title":"Two-stage nodal network interdiction under decision-dependent uncertainty","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; U.S. Department of Homeland Security","keywords":"Interdiction; Computer science; Operations research; Benchmark (surveying); Shortest path problem; Mathematical optimization; Theory of computation; Robust optimization; Constraint (computer-aided design); Plan (archaeology); Path (computing); Bottleneck; Computer network; Graph; Algorithm; Mathematics; Theoretical computer science","score_opus":0.11209678160355414,"score_gpt":0.4349335061352933,"score_spread":0.32283672453173917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387770819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9545429,0.00016904114,0.039511953,0.0008721342,0.00025045435,0.0002606998,0.00004103277,0.00016826193,0.004183568],"genre_scores_gemma":[0.9981723,0.00043093262,0.00037840178,0.000041194984,0.0001819211,0.000037039466,0.00004838243,0.000016219803,0.00069360493],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982246,0.00015340268,0.00033040787,0.00020579249,0.0006348736,0.000450919],"domain_scores_gemma":[0.9987159,0.00029050457,0.000008768715,0.00039136174,0.0005012555,0.000092224225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018402367,0.000100443736,0.00017231639,0.00043154662,0.00036199388,0.00010363697,0.000262245,0.00007575703,0.0006088687],"category_scores_gemma":[0.00021062445,0.00008978588,0.000097343,0.0017394864,0.00011873688,0.00023816088,0.000105281535,0.00037972178,0.00023344296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000130907465,0.000012775016,0.0002483488,0.000014510531,0.000053577347,0.0000030144793,0.00014196821,0.98223823,0.0015791021,0.0032424703,0.006642741,0.005810165],"study_design_scores_gemma":[0.00016406194,0.000060282495,0.0035575922,0.000039248247,0.0000057949496,0.000001595077,0.0010172586,0.986205,0.0037384708,0.003379553,0.0017048711,0.00012628525],"about_ca_topic_score_codex":0.0003522203,"about_ca_topic_score_gemma":0.0014512662,"teacher_disagreement_score":0.043629445,"about_ca_system_score_codex":0.000048766287,"about_ca_system_score_gemma":0.00007079947,"threshold_uncertainty_score":0.66666853},"labels":[],"label_agreement":null},{"id":"W4387970997","doi":"10.1007/s10479-023-05620-y","title":"Healthcare inventory management in the presence of supply disruptions and a reliable secondary supplier","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Economic shortage; Supply chain; Operations research; Theory of computation; Health care; Duration (music); Supply chain management; Inventory management; Operations management; Markov decision process; Computer science; Markov chain; Sensitivity (control systems); Business; Markov process; Economics; Marketing; Mathematics; Engineering","score_opus":0.17515398807690405,"score_gpt":0.4026356781810077,"score_spread":0.22748169010410366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387970997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90994984,0.0005611557,0.000012956753,0.048981994,0.00012988408,0.0016392069,0.0000264842,0.000040159746,0.038658317],"genre_scores_gemma":[0.99508864,0.0009990183,0.00005232844,0.0009465882,0.00010022649,0.00029961395,0.000089786765,0.000013295176,0.002410507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998278,0.000090889305,0.00036105007,0.00025170355,0.0006378482,0.00038050683],"domain_scores_gemma":[0.9991089,0.00008733362,0.000036924856,0.00042574122,0.00032366384,0.000017406752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029873783,0.000096000025,0.00014896193,0.0010362713,0.00029916747,0.00015534603,0.0004377619,0.00003890768,0.00026612225],"category_scores_gemma":[0.00011454952,0.000077409444,0.000045611632,0.001944849,0.00023198081,0.00063021475,0.00044579426,0.00022773915,0.000089228015],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006537752,0.00042186765,0.024559189,0.0018936329,0.00007858027,0.000040423816,0.0024042486,0.0024603864,0.0002055187,0.6380934,0.31992653,0.009850864],"study_design_scores_gemma":[0.0017270388,0.00021528784,0.33060285,0.000641955,0.000037312024,0.0000028019888,0.053446934,0.061841805,0.0003909299,0.03080048,0.5197597,0.0005328907],"about_ca_topic_score_codex":0.0023222063,"about_ca_topic_score_gemma":0.0011077465,"teacher_disagreement_score":0.6072929,"about_ca_system_score_codex":0.0000113873975,"about_ca_system_score_gemma":0.00003848834,"threshold_uncertainty_score":0.35104966},"labels":[],"label_agreement":null},{"id":"W4388303805","doi":"10.1007/s10479-023-05655-1","title":"Vulnerability analysis of China’s air and high-speed rail composite express network under different node attack strategies","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Vulnerability (computing); Computer science; Node (physics); Position (finance); Computer network; Vulnerability assessment; Topology (electrical circuits); Flow network; China; Computer security; Psychological resilience; Engineering; Business; Structural engineering; Geography; Mathematics","score_opus":0.15763595444865758,"score_gpt":0.4511901562351217,"score_spread":0.29355420178646413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388303805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99045193,0.00008917122,0.0069955024,0.0012314776,0.000012752931,0.0002529859,0.000104042934,0.000039462913,0.0008226761],"genre_scores_gemma":[0.9986839,0.000087698194,0.00038936987,0.000013292767,0.000093688905,0.00004129038,0.00039545223,0.000013528683,0.00028174795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9977316,0.00053362636,0.00048904674,0.00034925606,0.00049929623,0.0003971628],"domain_scores_gemma":[0.99827427,0.0003196363,0.00006151093,0.0006121598,0.0006379536,0.0000944517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011222229,0.00015507087,0.0005555162,0.00055020733,0.0003630316,0.00012360011,0.00030675493,0.000045143013,0.00038800685],"category_scores_gemma":[0.000014297613,0.00013393401,0.00021271687,0.0025687062,0.00030565576,0.00019867436,0.00032054982,0.00027035948,0.0000043420973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034378005,0.0002626088,0.053796876,0.000030016672,0.0015736733,4.8241185e-7,0.00040034327,0.9103254,0.004519959,0.024449214,0.0036344482,0.000972566],"study_design_scores_gemma":[0.00021311421,0.00009451261,0.6448741,0.000041450323,0.00019303692,5.6542333e-8,0.0006981309,0.33821252,0.006998117,0.008345006,0.00013567264,0.00019428947],"about_ca_topic_score_codex":0.0032075727,"about_ca_topic_score_gemma":0.00045394906,"teacher_disagreement_score":0.5910772,"about_ca_system_score_codex":0.0000110202,"about_ca_system_score_gemma":0.000066100794,"threshold_uncertainty_score":0.546167},"labels":[],"label_agreement":null},{"id":"W4388763558","doi":"10.1007/s10479-023-05660-4","title":"Integration of text-mining and telemedicine appointment optimization","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Computer science; Regret; Telemedicine; Health care; Profit (economics); Classifier (UML); Postponement; Operations research; Data mining; Artificial intelligence; Machine learning; Operations management","score_opus":0.5111778685502172,"score_gpt":0.6091961743106531,"score_spread":0.09801830576043591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388763558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92569536,0.00022558618,0.04405812,0.022700965,0.00016838583,0.0018733494,0.00005530172,0.00008164104,0.00514131],"genre_scores_gemma":[0.9699412,0.0021710848,0.025266359,0.00018189155,0.00011370145,0.00023464416,0.00032033512,0.00002081004,0.0017499847],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973538,0.0008187959,0.0007736896,0.0002182035,0.00048902724,0.00034649827],"domain_scores_gemma":[0.9963663,0.00059326866,0.00007120662,0.00026295224,0.0025947015,0.00011157459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045172535,0.00008738909,0.00022693696,0.0007492729,0.0009149967,0.000017062714,0.00010456768,0.0001353765,0.000269928],"category_scores_gemma":[0.0021423965,0.000074226744,0.000025966068,0.0015569193,0.00014846273,0.00023421797,0.00009336802,0.00029095451,0.000025527399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000158447,0.0002801329,0.007593615,0.00076042244,0.00008638615,0.0000039484135,0.034200728,0.8064868,0.019093094,0.042360514,0.021957222,0.067018695],"study_design_scores_gemma":[0.0005548361,0.00048064283,0.007448876,0.0004880716,0.000006733708,8.468055e-7,0.016320897,0.97145593,0.0020543041,0.00012600586,0.0009553654,0.000107511056],"about_ca_topic_score_codex":0.00053142174,"about_ca_topic_score_gemma":0.00032091892,"teacher_disagreement_score":0.16496912,"about_ca_system_score_codex":0.000027673988,"about_ca_system_score_gemma":0.0004817924,"threshold_uncertainty_score":0.7037507},"labels":[],"label_agreement":null},{"id":"W4389012055","doi":"10.1007/s10479-023-05672-0","title":"How do weather risks in Canada and the United States affect global commodity prices? Implications for the decarbonisation process","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Commodity; Vector autoregression; Crude oil; Futures contract; Economics; Agriculture; Extreme weather; Oil price; Natural resource economics; Agricultural economics; Environmental science; Climate change; Econometrics; Financial economics; Monetary economics; Finance","score_opus":0.26504908841384733,"score_gpt":0.4247105866794679,"score_spread":0.1596614982656206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389012055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9455191,0.0003780963,0.00092593837,0.050947618,0.000024137384,0.00088735274,0.0009937134,0.000004873869,0.00031918922],"genre_scores_gemma":[0.9981939,0.001110906,0.000023731163,0.00009177201,0.00001399096,0.00038119964,0.00011191197,0.0000054860743,0.00006707317],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992064,0.00009465875,0.00023841372,0.00017761314,0.000066352,0.00021651055],"domain_scores_gemma":[0.99835354,0.000970335,0.00005297008,0.00029696585,0.00029253526,0.000033681736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033781894,0.000059605234,0.00014147774,0.00012453637,0.00038841506,0.00020107071,0.00024907998,0.000030500903,0.000009302165],"category_scores_gemma":[0.00085164787,0.000041668023,0.000029020002,0.0010959475,0.00015136758,0.00010503096,0.00006172635,0.00012607207,7.438624e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068085734,0.000040984283,0.7467153,0.000051742478,0.000052044248,1.2696941e-7,0.0007736992,0.008951256,0.0000010639332,0.24023083,0.0014777391,0.0016370994],"study_design_scores_gemma":[0.00022888687,0.000012771348,0.4478766,0.0000038229928,0.0000011371471,1.4131336e-7,0.0004456096,0.5106858,0.0000027841384,0.039476234,0.0012296544,0.000036554826],"about_ca_topic_score_codex":0.735758,"about_ca_topic_score_gemma":0.84455097,"teacher_disagreement_score":0.50173455,"about_ca_system_score_codex":0.00007463128,"about_ca_system_score_gemma":0.00021182456,"threshold_uncertainty_score":0.29874137},"labels":[],"label_agreement":null},{"id":"W4389487793","doi":"10.1007/s10479-023-05698-4","title":"Enhancing the sustainability and robustness of critical material supply in electrical vehicle market: an AI-powered supplier selection approach","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Sustainability; Supply chain; Robustness (evolution); Dependability; Pace; Automotive industry; Supply and demand; Computer science; Environmental economics; Business; Risk analysis (engineering); Economics; Engineering; Marketing","score_opus":0.06839139924020661,"score_gpt":0.4207324229091003,"score_spread":0.3523410236688937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389487793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943642,0.000052996907,0.0026620138,0.0018687149,0.000038213147,0.00031320023,0.000013363242,0.000046274476,0.00064102863],"genre_scores_gemma":[0.99931544,0.000099894154,0.00018866346,0.000010019624,0.000043968066,0.000098029515,0.000022407336,0.000011761931,0.00020983368],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987183,0.00026583785,0.000301314,0.00015809404,0.00028417978,0.0002722676],"domain_scores_gemma":[0.99878573,0.00023952122,0.00000667331,0.00013718802,0.00077646156,0.000054436998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016926519,0.000067872155,0.00012831662,0.0003001365,0.0001668492,0.00009143967,0.00010647239,0.00007920719,0.0001701009],"category_scores_gemma":[0.00069052225,0.000057827543,0.000018148032,0.0011341948,0.00015058451,0.00039226003,0.000027311842,0.00026419977,0.0000017634139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004886487,0.000970051,0.0031509574,0.0014377399,0.00005144935,0.0000046262467,0.0042383675,0.68963146,0.26592267,0.020351762,0.009377224,0.004375071],"study_design_scores_gemma":[0.00014202403,0.00011679687,0.01650134,0.000008822529,0.0000022993486,0.0000042229617,0.0015353747,0.8628489,0.11805752,0.0004554102,0.00024522215,0.00008206949],"about_ca_topic_score_codex":0.000114010334,"about_ca_topic_score_gemma":0.00021623453,"teacher_disagreement_score":0.17321746,"about_ca_system_score_codex":0.00002763807,"about_ca_system_score_gemma":0.00013719809,"threshold_uncertainty_score":0.23581387},"labels":[],"label_agreement":null},{"id":"W4390269977","doi":"10.1007/s10479-023-05622-w","title":"Quality disclosure pattern options for competing refurbishers: blockchain vs online platform","year":2023,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Social Science Foundation of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Blockchain; Quality (philosophy); Duopoly; Product (mathematics); Business; Counterparty; Computer science; Microeconomics; Economics; Computer security; Actuarial science; Credit risk","score_opus":0.40830004685575005,"score_gpt":0.4662721342622861,"score_spread":0.05797208740653603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390269977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9563916,0.00006757481,0.00053867814,0.035208795,0.0002665793,0.0011981392,0.0001440686,0.0001715724,0.0060130088],"genre_scores_gemma":[0.99267256,0.000057567115,0.00024323346,0.0012364667,0.001057983,0.00024451895,0.00090101326,0.000033929628,0.0035527248],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979386,0.000058664096,0.0005038808,0.00032312467,0.00064774975,0.0005280076],"domain_scores_gemma":[0.9982306,0.00021709941,0.00006239584,0.00041103264,0.0010511118,0.00002778211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004018112,0.00013524464,0.00022301472,0.0007653127,0.0006390716,0.00036307526,0.00042428888,0.000063788306,0.00036537964],"category_scores_gemma":[0.0007814383,0.00012595726,0.00013690941,0.001328969,0.00012760109,0.0005474816,0.00037493784,0.00020941357,0.00022223456],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031294307,0.002170589,0.025339715,0.0028736754,0.0004844383,0.000022257462,0.0017762509,0.054015778,0.0030714788,0.32615596,0.52375495,0.060021948],"study_design_scores_gemma":[0.0020000497,0.00021900193,0.0423343,0.0003777223,0.000033720957,7.049951e-7,0.022804862,0.5022225,0.00068429665,0.008117524,0.4204304,0.00077496265],"about_ca_topic_score_codex":0.0012496747,"about_ca_topic_score_gemma":0.0017204229,"teacher_disagreement_score":0.4482067,"about_ca_system_score_codex":0.00002108441,"about_ca_system_score_gemma":0.000040755403,"threshold_uncertainty_score":0.5136388},"labels":[],"label_agreement":null},{"id":"W4390543445","doi":"10.1007/s10479-023-05765-w","title":"Short- and long-run cross-border European sustainability interdependences","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Economics; Equity (law); Financial crisis; Environmental Sustainability Index; Index (typography); European debt crisis; Corporate governance; International economics; Macroeconomics; European union; Finance; Political science","score_opus":0.1499951548090992,"score_gpt":0.4877545870474269,"score_spread":0.3377594322383277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390543445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9533667,0.0050015184,0.0018308967,0.0033221233,0.00009432571,0.0002597311,0.00013563379,0.000018280698,0.03597079],"genre_scores_gemma":[0.9919153,0.0006976466,0.000064535874,0.00003612309,0.000047895126,0.000016779857,0.000013594608,0.000013602022,0.0071945153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99863136,0.0001253691,0.00046356005,0.00041376663,0.00008775558,0.00027820407],"domain_scores_gemma":[0.99891454,0.00014841641,0.000013297786,0.00034015236,0.000499113,0.00008446772],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0054331785,0.00008376733,0.0001770416,0.00032695435,0.00022372692,0.0005706133,0.00019370767,0.000049958562,0.0016473709],"category_scores_gemma":[0.0008163508,0.00008455002,0.000063821935,0.00042100347,0.00032955554,0.0004024463,0.0002217757,0.0002907346,0.00005439083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004983651,0.00027214884,0.57400566,0.00068038475,0.00013700205,0.000039610408,0.0016010911,0.00040965842,0.000023623834,0.37058485,0.0018014079,0.050394703],"study_design_scores_gemma":[0.00012269008,0.0002168011,0.64307815,0.000060213413,0.0000022973952,0.000007348006,0.00028856547,0.27040315,0.00007238567,0.04339132,0.042081133,0.0002759517],"about_ca_topic_score_codex":0.0003356352,"about_ca_topic_score_gemma":0.00029228182,"teacher_disagreement_score":0.32719353,"about_ca_system_score_codex":0.000029605559,"about_ca_system_score_gemma":0.000067102475,"threshold_uncertainty_score":0.99926525},"labels":[],"label_agreement":null},{"id":"W4390878815","doi":"10.1007/s10479-023-05740-5","title":"Peer-evaluation in centrally managed systems","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperplane; Computer science; Theory of computation; Set (abstract data type); Projection (relational algebra); Feature (linguistics); Production (economics); Data envelopment analysis; Operations research; Mathematical optimization; Mathematics; Algorithm","score_opus":0.6121769435393668,"score_gpt":0.6076037708899307,"score_spread":0.00457317264943613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390878815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9150337,0.005283671,0.0033207063,0.042084318,0.00048198673,0.0009099831,0.000031729727,0.00003816143,0.032815747],"genre_scores_gemma":[0.98588336,0.000080090394,0.00013401263,0.000031916203,0.000059089518,0.000048030706,0.000014341565,0.000007940239,0.013741243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9893095,0.0021044032,0.0008096792,0.00050021755,0.006901913,0.00037431173],"domain_scores_gemma":[0.99189264,0.0015185528,0.000023265779,0.00066935865,0.0058186655,0.00007754876],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.057839464,0.00007757572,0.00020486525,0.0023579446,0.00022596835,0.0013637429,0.0007515813,0.00006703161,0.00053901866],"category_scores_gemma":[0.015858931,0.000059114653,0.00009316897,0.005946697,0.00016545146,0.0005908015,0.00011430016,0.00032623886,0.00077492435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001577747,0.00022454976,0.0010740529,0.000036040306,0.000046726942,0.000037495367,0.003222855,0.7905413,0.0034671822,0.08496078,0.08123455,0.035138708],"study_design_scores_gemma":[0.000074481235,0.000049667695,0.0038019198,0.00008327025,0.0000049258947,0.0000020397647,0.001714924,0.97485787,0.0006996883,0.0033804935,0.015259113,0.00007163093],"about_ca_topic_score_codex":0.00084751425,"about_ca_topic_score_gemma":0.00094148744,"teacher_disagreement_score":0.18431656,"about_ca_system_score_codex":0.000057838162,"about_ca_system_score_gemma":0.0005490013,"threshold_uncertainty_score":0.99967295},"labels":[],"label_agreement":null},{"id":"W4391254087","doi":"10.1007/s10479-024-05826-8","title":"Towards sustainable sustainability: exploring the impact of antecedents on industry 4.0 and sustainable performance of organizations—an empirical investigation","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Ministry of Higher Education","keywords":"Sustainability; Business; Sustainable development; Green computing; Empirical research; Empirical evidence; Environmental economics; Industrial organization; Knowledge management; Computer science; Economics; Political science","score_opus":0.14622293476208337,"score_gpt":0.42318090105664463,"score_spread":0.27695796629456126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391254087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922734,0.00017864726,0.00008160371,0.005046177,0.000032287444,0.0011228848,0.0000038404564,0.00004229202,0.001218866],"genre_scores_gemma":[0.9973405,0.000100709694,0.000030171046,0.00009387326,0.00015935785,0.00015199327,0.00003559349,0.000037488793,0.0020502955],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9974337,0.00017402455,0.0005166843,0.0003705502,0.0008087259,0.0006962661],"domain_scores_gemma":[0.9907158,0.00018112348,0.00006807364,0.00055977906,0.008432426,0.000042817694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004764042,0.0001861968,0.00025604246,0.0015574245,0.00061576365,0.00055835367,0.0004661755,0.000110699504,0.00012819756],"category_scores_gemma":[0.003579598,0.00013785007,0.00006244775,0.00586968,0.00046882275,0.0032071986,0.00069202395,0.0005242745,0.0000048965944],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045260368,0.0011258908,0.21264164,0.015071634,0.0004722454,0.00010548614,0.008908033,0.23730887,0.0008348668,0.49240002,0.01780532,0.012873358],"study_design_scores_gemma":[0.00088847015,0.0018147097,0.40145847,0.0006490384,0.000099147335,0.0000058055098,0.23799025,0.30638883,0.013298941,0.029416183,0.007273582,0.00071658863],"about_ca_topic_score_codex":0.008320967,"about_ca_topic_score_gemma":0.000028729386,"teacher_disagreement_score":0.46298385,"about_ca_system_score_codex":0.00021751216,"about_ca_system_score_gemma":0.0010820379,"threshold_uncertainty_score":0.99828273},"labels":[],"label_agreement":null},{"id":"W4391610463","doi":"10.1007/s10479-023-05814-4","title":"Optimization of inpatient care unit resources during COVID-19 pandemic","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Theory of computation; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Unit (ring theory); Computer science; Virology; Medicine; Mathematics; Outbreak; Algorithm; Infectious disease (medical specialty); Internal medicine","score_opus":0.3036018408446837,"score_gpt":0.5156244051412359,"score_spread":0.21202256429655214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391610463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776764,0.014709584,0.0002327435,0.003323043,0.00005677179,0.00035211028,0.000072821626,0.000034969064,0.0035415418],"genre_scores_gemma":[0.99007976,0.008357778,0.0002690908,0.00007292967,0.0000685565,0.00003808204,0.000074126445,0.000010908483,0.0010287535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","domain_scores_codex":[0.9988358,0.00011533994,0.00027322417,0.00016660315,0.00044128948,0.00016772412],"domain_scores_gemma":[0.9983289,0.000105818006,0.0000115774565,0.0001916386,0.0012669179,0.00009510027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044022914,0.0000640098,0.00015166918,0.00041519903,0.00025354195,0.000016873995,0.0000800683,0.00004878818,0.00028536638],"category_scores_gemma":[0.0008517357,0.000052247357,0.00006177636,0.000750934,0.00017602366,0.00009315349,0.00008292487,0.00019103625,0.0000062741774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074572576,0.0005641319,0.1537385,0.012782432,0.0011232644,0.00013116364,0.15832762,0.5837247,0.045132253,0.006328152,0.031042576,0.006359513],"study_design_scores_gemma":[0.005575427,0.008554773,0.070288,0.008096845,0.0004896759,0.00016495917,0.2877288,0.1037537,0.2415214,0.0005405051,0.2717601,0.0015258195],"about_ca_topic_score_codex":0.00032423972,"about_ca_topic_score_gemma":0.00011822327,"teacher_disagreement_score":0.47997096,"about_ca_system_score_codex":0.000030511748,"about_ca_system_score_gemma":0.0002959889,"threshold_uncertainty_score":0.31245616},"labels":[],"label_agreement":null},{"id":"W4391839143","doi":"10.1007/s10479-024-05834-8","title":"The impact of sparsity and entropy criteria on neural network performance","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Artificial neural network; Theory of computation; Computer science; Entropy (arrow of time); Artificial intelligence; Machine learning; Algorithm; Thermodynamics; Physics","score_opus":0.18792104234497645,"score_gpt":0.4748126505737744,"score_spread":0.286891608228798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391839143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989434,0.0009818255,0.0010317279,0.0077513377,0.00005974952,0.00019685106,0.000006968501,0.000016978449,0.00052055303],"genre_scores_gemma":[0.99810374,0.0011840777,0.00031592205,0.000029977948,0.00009446927,0.000017972356,0.0000017639604,0.000003252215,0.0002488361],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991282,0.000111759065,0.00014493201,0.0001597044,0.00022541214,0.00022997653],"domain_scores_gemma":[0.99907637,0.00028421025,0.0000092125865,0.0003396558,0.00023768007,0.000052903637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007346988,0.000052814517,0.00007291851,0.00005942464,0.0004448575,0.00029895536,0.0004011764,0.00001927165,0.000011313178],"category_scores_gemma":[0.000027808408,0.000031593892,0.000045124914,0.0006088821,0.0001464343,0.00025002885,0.0001714939,0.00017646496,0.000008646511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056421235,0.00015592917,0.0014773597,0.00005100442,0.00008848402,0.000005429434,0.0006126223,0.23530693,0.0074603274,0.47082743,0.13814668,0.14581136],"study_design_scores_gemma":[0.000028853558,0.000320577,0.016463479,0.000033806224,7.1734166e-7,0.0000032161781,0.000005627263,0.97878766,0.0016486763,0.0011525849,0.00151702,0.000037788377],"about_ca_topic_score_codex":0.00008499464,"about_ca_topic_score_gemma":0.000011722892,"teacher_disagreement_score":0.74348074,"about_ca_system_score_codex":0.0000060069556,"about_ca_system_score_gemma":0.000068175614,"threshold_uncertainty_score":0.34215292},"labels":[],"label_agreement":null},{"id":"W4391924232","doi":"10.1007/s10479-024-05860-6","title":"A polynomial-time approximation scheme for an arbitrary number of parallel identical multi-stage flow-shops","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Theory of computation; Scheme (mathematics); Flow (mathematics); Polynomial-time approximation scheme; Mathematics; Time complexity; Stage (stratigraphy); Computer science; Discrete mathematics; Algorithm; Geometry; Mathematical analysis","score_opus":0.2199977720889789,"score_gpt":0.4612305012646664,"score_spread":0.24123272917568753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391924232","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4220379,0.00082447706,0.57152337,0.0010538972,0.00023676059,0.0011898709,0.0003691845,0.00033347716,0.0024310874],"genre_scores_gemma":[0.15515953,0.00014509758,0.84185064,0.000024529607,0.00015180024,0.0001811837,0.00029584678,0.000054004155,0.0021373737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987982,0.00007259965,0.00038179907,0.00018678262,0.00031315934,0.0002474388],"domain_scores_gemma":[0.9990084,0.00014221991,0.000008343769,0.00023703197,0.00050835917,0.00009562328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009658328,0.00009594661,0.00016319132,0.00026227187,0.000098537545,0.00014150505,0.00016902403,0.00010010568,0.00027685723],"category_scores_gemma":[0.0002539574,0.00009573946,0.00008292501,0.00045867357,0.000081798535,0.00044179967,0.000028153509,0.00020455927,0.00008940902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007849202,0.00050729036,0.000095292155,0.0009771921,0.00027537876,0.0000047072026,0.0024153832,0.94105154,0.02963228,0.009913185,0.009738693,0.0053105387],"study_design_scores_gemma":[0.00021511588,0.00004740925,0.000048673417,0.000059369002,0.00000447313,0.0000018391066,0.00015134217,0.9856833,0.013209404,0.00006368259,0.00042315197,0.000092245784],"about_ca_topic_score_codex":0.000032764667,"about_ca_topic_score_gemma":0.000009307897,"teacher_disagreement_score":0.27032727,"about_ca_system_score_codex":0.000014474305,"about_ca_system_score_gemma":0.000108669825,"threshold_uncertainty_score":0.39041418},"labels":[],"label_agreement":null},{"id":"W4392345961","doi":"10.1007/s10479-024-05892-y","title":"Optimal production management when there is regime switching and production constraints","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Production (economics); Theory of computation; Computer science; Biochemical engineering; Economics; Microeconomics; Algorithm; Engineering","score_opus":0.20786573427900337,"score_gpt":0.375731544277729,"score_spread":0.1678658099987256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392345961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9218727,0.006142771,0.002693063,0.041938916,0.00046980404,0.00066305965,0.00006911959,0.000038508264,0.026112096],"genre_scores_gemma":[0.9795725,0.0033448546,0.0017043245,0.000050917355,0.00017326385,0.00005510945,0.000008261485,0.000016664206,0.015074118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988936,0.000028707569,0.00035113358,0.00045128242,0.00005250215,0.00022276597],"domain_scores_gemma":[0.9994985,0.000021239706,0.00002651569,0.00029042392,0.00011622758,0.000047099238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019655775,0.000080384496,0.00015479015,0.000359308,0.00022435181,0.00022377298,0.00011517587,0.000047213005,0.0004040035],"category_scores_gemma":[0.00008377104,0.000085362415,0.000043076205,0.00018622907,0.00016188197,0.00050767796,0.00008532959,0.0001807442,0.00015098852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001775801,0.000057048703,0.0001430631,0.00017604265,0.0001468374,0.0000031357952,0.0037497766,0.0023905544,0.00027781224,0.9598466,0.013370522,0.019820845],"study_design_scores_gemma":[0.0005837599,0.0005362762,0.0024213325,0.00074657245,0.000026018448,0.000081172024,0.0081180055,0.07391969,0.021522373,0.6487027,0.24237096,0.00097112934],"about_ca_topic_score_codex":0.00014791504,"about_ca_topic_score_gemma":0.000018035578,"teacher_disagreement_score":0.3111439,"about_ca_system_score_codex":0.000026710524,"about_ca_system_score_gemma":0.00002811254,"threshold_uncertainty_score":0.4423555},"labels":[],"label_agreement":null},{"id":"W4392614914","doi":"10.1007/s10479-024-05900-1","title":"A semi-supervised multi-criteria sorting approach to constructing social vulnerability composite indicators","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Vulnerability (computing); Sorting; Composite number; Computer science; Composite indicator; Artificial intelligence; Mathematics; Econometrics; Computer security; Algorithm","score_opus":0.2861971457010072,"score_gpt":0.5178721124146695,"score_spread":0.23167496671366228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392614914","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90773517,0.0001288105,0.0018672183,0.0054992307,0.00014206825,0.00069755095,0.000017478918,0.000077366894,0.08383512],"genre_scores_gemma":[0.9940975,0.000023118553,0.003530846,0.000093469775,0.00019394491,0.00006886337,0.000010584518,0.0000102466065,0.0019714464],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9972164,0.0007846289,0.000329949,0.00036304627,0.0008170471,0.00048895227],"domain_scores_gemma":[0.9991366,0.00016721967,0.000015301033,0.00016320284,0.0003713493,0.00014627964],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004365814,0.000087150576,0.00015759884,0.0005000316,0.0015136172,0.000697354,0.00045267763,0.000072752555,0.00014804545],"category_scores_gemma":[0.0005792582,0.00008101728,0.00007528625,0.0018939733,0.0007300021,0.00044037445,0.00022702837,0.00029613893,0.000046801015],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067927205,0.0013006554,0.012174288,0.0008053262,0.00025435645,0.00001643483,0.4572783,0.0016405479,0.03805498,0.31014243,0.018592447,0.15967232],"study_design_scores_gemma":[0.0014893409,0.00047887999,0.028988538,0.0009857154,0.00007861512,0.000005347066,0.662932,0.18806463,0.018551653,0.0033193184,0.093077414,0.0020285745],"about_ca_topic_score_codex":0.0010285834,"about_ca_topic_score_gemma":0.0003219574,"teacher_disagreement_score":0.3068231,"about_ca_system_score_codex":0.00003614526,"about_ca_system_score_gemma":0.00026858994,"threshold_uncertainty_score":0.99978626},"labels":[],"label_agreement":null},{"id":"W4392886271","doi":"10.1007/s10479-024-05852-6","title":"Sustainable supply chain coordination: extant literature, trends, and future research directions","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Toronto Metropolitan University","funders":"","keywords":"Extant taxon; Supply chain; Theory of computation; Computer science; Process management; Business; Management science; Economics; Marketing","score_opus":0.07910607517106488,"score_gpt":0.39619828862296,"score_spread":0.31709221345189514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392886271","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0851346,0.0802512,0.00019351493,0.5851084,0.0011396665,0.0036475034,0.00007978586,0.0006393861,0.24380592],"genre_scores_gemma":[0.8563902,0.003743699,0.00015184197,0.00031108648,0.0032794136,0.0005161628,0.0002047946,0.00006405923,0.13533875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99638844,0.00024084908,0.00039611314,0.00064406026,0.0012908967,0.001039652],"domain_scores_gemma":[0.9942458,0.00028600663,0.000022164042,0.0005327766,0.004860635,0.00005258194],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007487339,0.0002061383,0.00022933028,0.0059383237,0.0015816402,0.0036209878,0.00043518035,0.00013701743,0.0009410984],"category_scores_gemma":[0.0006975589,0.00018649419,0.0000903338,0.010723527,0.00036580456,0.0027394455,0.00070476905,0.0008342792,0.00011267219],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032462358,0.00013924361,0.00015371417,0.0009920312,0.00006641086,0.00019585202,0.0007859836,0.00012047677,0.00012246403,0.7477588,0.2054628,0.044169743],"study_design_scores_gemma":[0.00019085387,0.00006453563,0.0017881512,0.00016406922,0.000011200007,0.0000058436403,0.014170853,0.012966637,0.00012222033,0.010142217,0.9601778,0.00019564836],"about_ca_topic_score_codex":0.002286551,"about_ca_topic_score_gemma":0.00033890994,"teacher_disagreement_score":0.7712556,"about_ca_system_score_codex":0.00010066622,"about_ca_system_score_gemma":0.00018857002,"threshold_uncertainty_score":0.99997216},"labels":[],"label_agreement":null},{"id":"W4393068512","doi":"10.1007/s10479-024-05909-6","title":"Inventory models for non-instantaneous deteriorating items with expiration dates under the joined effect of preservation technology and linearly time-dependent holding cost when order-size linked to advance payment","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Theory of computation; Payment; Order (exchange); Expiration; Expiration date; Econometrics; Operations research; Operations management; Computer science; Actuarial science; Mathematics; Economics; Statistics; Business; Algorithm; Finance; Psychology","score_opus":0.08863915829385094,"score_gpt":0.356156053973911,"score_spread":0.26751689568006004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393068512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95143527,0.00040540012,0.0322404,0.011212791,0.00008982159,0.0038711498,0.000015861213,0.000070745155,0.0006585676],"genre_scores_gemma":[0.9967764,0.0000507041,0.00097569614,0.00028876192,0.00015546818,0.0007931434,0.00004372269,0.000030727388,0.000885361],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985201,0.000059689522,0.00036274557,0.00032297208,0.0004595338,0.00027495567],"domain_scores_gemma":[0.9984904,0.00028477336,0.000059519447,0.00030416265,0.00084275164,0.000018429328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018720379,0.00014411638,0.00020271528,0.00060302805,0.0003412842,0.00047966026,0.00025906795,0.000059634953,0.00003476876],"category_scores_gemma":[0.0003798246,0.000099540484,0.00003213453,0.00092935533,0.00010214834,0.0012789319,0.0002431266,0.00015332355,0.000009559724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015210918,0.00040967533,0.0019433281,0.004701078,0.00062566175,0.000024769946,0.0030885113,0.5556821,0.2873509,0.08068941,0.010318687,0.053644802],"study_design_scores_gemma":[0.0005309487,0.0005852183,0.00006511547,0.00047282336,0.000030626077,0.0000012578987,0.00091218523,0.9815312,0.008781399,0.0017140355,0.0052167485,0.0001584527],"about_ca_topic_score_codex":0.00023249745,"about_ca_topic_score_gemma":0.00032861173,"teacher_disagreement_score":0.42584908,"about_ca_system_score_codex":0.000032304026,"about_ca_system_score_gemma":0.000055557288,"threshold_uncertainty_score":0.4625375},"labels":[],"label_agreement":null},{"id":"W4393994304","doi":"10.1007/s10479-024-05940-7","title":"A scenario-based robust optimization model for the sustainable distributed permutation flow-shop scheduling problem","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Flow shop scheduling; Computer science; Scheduling (production processes); Distributed computing; Permutation (music); Mathematical optimization; Job shop scheduling; Parallel computing; Mathematics; Embedded system","score_opus":0.1292306165847016,"score_gpt":0.3796719194277512,"score_spread":0.25044130284304955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393994304","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008547986,0.0011611993,0.99257517,0.0039874325,0.0000675203,0.000894084,0.00011025805,0.00020675757,0.00014278566],"genre_scores_gemma":[0.41920632,0.00030669407,0.5777353,0.000043369466,0.000116672156,0.000695303,0.0007569915,0.00006685528,0.0010724787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998614,0.0000630366,0.0003159593,0.00021886146,0.00038278307,0.00040532643],"domain_scores_gemma":[0.99751896,0.0003356636,0.000009649996,0.00024291678,0.0018225246,0.00007025955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014492316,0.00012271578,0.00012231155,0.0003411908,0.0005739023,0.0005141468,0.00021022325,0.000096532756,0.000050837352],"category_scores_gemma":[0.0004540303,0.000100202335,0.00007954745,0.0011521284,0.00007826938,0.00038843587,0.000029119796,0.00027762094,0.0000072708367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013492745,0.000031158354,0.0000015988497,0.00024886715,0.000044456636,0.0000012107888,0.00054568006,0.9934199,0.00006288715,0.0038529546,0.0010464027,0.00073142047],"study_design_scores_gemma":[0.00018376639,0.00003748277,0.0000013030535,0.00008492079,0.000013782596,8.478425e-7,0.0008041032,0.9976472,0.000795089,0.00014927874,0.0001705414,0.0001116345],"about_ca_topic_score_codex":0.00003229306,"about_ca_topic_score_gemma":0.00001739708,"teacher_disagreement_score":0.41835153,"about_ca_system_score_codex":0.00006871864,"about_ca_system_score_gemma":0.00038543364,"threshold_uncertainty_score":0.49579298},"labels":[],"label_agreement":null},{"id":"W4394917640","doi":"10.1007/s10479-024-05930-9","title":"A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subject (documents); Process (computing); Production (economics); Computer science; Economics; Programming language","score_opus":0.14406912029629854,"score_gpt":0.41939483199546657,"score_spread":0.27532571169916803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394917640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18920793,0.000069324145,0.8072687,0.001362215,0.000100865815,0.0017221919,0.000023928647,0.00013428931,0.0001105537],"genre_scores_gemma":[0.98467916,0.000024494824,0.0131554,0.000014421941,0.00007967061,0.0016953499,0.000011513585,0.000034122833,0.00030586816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986456,0.00003388216,0.0003362978,0.00029134695,0.0003427703,0.00035007458],"domain_scores_gemma":[0.9983066,0.00010718234,0.00000640877,0.00023615496,0.0012397469,0.00010394771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015246586,0.00010420765,0.00017218165,0.0009062697,0.00014825797,0.0001942683,0.00014851992,0.000057126468,0.0000037916416],"category_scores_gemma":[0.0016726577,0.000093855735,0.00004959776,0.002152404,0.00003144936,0.00039635084,0.000029900972,0.00013353491,0.00004293538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032745826,0.000023049814,6.817565e-7,0.0010907494,0.000014664332,4.0887585e-7,0.001395789,0.98440474,0.0062122135,0.0037900019,0.001164885,0.0018700807],"study_design_scores_gemma":[0.000044912373,0.00012854274,0.000004499812,0.00061137875,0.0000043922014,0.0000048535044,0.0010176789,0.9921732,0.005351104,0.0005304272,0.000030072557,0.000098927805],"about_ca_topic_score_codex":0.000008798887,"about_ca_topic_score_gemma":0.000023417582,"teacher_disagreement_score":0.79547125,"about_ca_system_score_codex":0.000121255645,"about_ca_system_score_gemma":0.00014474071,"threshold_uncertainty_score":0.3827326},"labels":[],"label_agreement":null},{"id":"W4395452180","doi":"10.1007/s10479-024-05903-y","title":"Multi-item order quantity optimization through stochastic goal programing","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Qatar University","keywords":"Order (exchange); Computer science; Stochastic optimization; Stochastic programming; Mathematical optimization; Mathematics; Economics","score_opus":0.23686216625472759,"score_gpt":0.4645346067948513,"score_spread":0.22767244054012373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395452180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049875923,0.001042587,0.99156415,0.0004514192,0.00012395016,0.0005103125,0.000010099998,0.0003272954,0.0009825608],"genre_scores_gemma":[0.7306111,0.00023180539,0.2684081,0.000017507755,0.000057095254,0.000118438584,0.000048610847,0.000044637785,0.00046274223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987817,0.000066275104,0.00030077226,0.00017938342,0.00035659038,0.0003152923],"domain_scores_gemma":[0.9989485,0.0001718562,0.000005478963,0.00018999161,0.0006146053,0.0000695249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062307,0.00010333467,0.00013592464,0.00021862841,0.00017337895,0.00031609056,0.00013837687,0.00007706256,0.0002131233],"category_scores_gemma":[0.000590971,0.00009539467,0.000048448008,0.0011261195,0.000108051165,0.0005091166,0.00004757937,0.00027309108,0.00007941331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018623366,0.000080706115,0.000002785467,0.00023428578,0.000036351947,0.0000021266023,0.0006691761,0.9840409,0.00041111713,0.01031902,0.00049113255,0.00371051],"study_design_scores_gemma":[0.00008069588,0.00004352689,0.000008132578,0.0001225798,0.000004955914,0.00000233899,0.0002225229,0.99794185,0.0006332514,0.00009099211,0.00075145764,0.00009770272],"about_ca_topic_score_codex":0.00004359426,"about_ca_topic_score_gemma":0.000031428757,"teacher_disagreement_score":0.7256235,"about_ca_system_score_codex":0.000020927962,"about_ca_system_score_gemma":0.000067757646,"threshold_uncertainty_score":0.3890082},"labels":[],"label_agreement":null},{"id":"W4395685700","doi":"10.1007/s10479-024-05989-4","title":"On robust estimation of hidden semi-Markov regime-switching models","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Theory of computation; Computer science; Hidden Markov model; Markov chain; Estimation; Markov model; Mathematical optimization; Econometrics; Mathematics; Artificial intelligence; Algorithm; Economics; Machine learning","score_opus":0.5266099326586466,"score_gpt":0.5509765792159146,"score_spread":0.024366646557267946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395685700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09684711,0.00022088861,0.88334644,0.0020443192,0.000060377326,0.00035010377,0.00006414706,0.000036039535,0.017030561],"genre_scores_gemma":[0.7666523,0.000085917745,0.23238665,0.000022426351,0.000028159533,0.000031606818,0.00000663412,0.000015694606,0.0007706302],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819446,0.00034625427,0.00039971157,0.00020955707,0.0006319213,0.00021810087],"domain_scores_gemma":[0.99547374,0.0034255711,0.000021795004,0.00034257525,0.0006689881,0.00006731078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025952642,0.000085753556,0.00020096019,0.0003169309,0.00012572971,0.00009754484,0.00019214221,0.000068992915,0.00025282716],"category_scores_gemma":[0.0058332873,0.00006941149,0.00005613125,0.0005016616,0.00009380309,0.00021462038,0.00006995058,0.0003240028,0.00002414226],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016903108,0.00009391941,9.961909e-7,0.00025028797,0.000028929077,0.000003123251,0.0006463897,0.030134989,0.0011851427,0.919917,0.006182858,0.041539486],"study_design_scores_gemma":[0.0000330721,0.00011978957,0.000009517645,0.0003092145,0.000004087709,9.424234e-7,0.00006547082,0.569812,0.0051979246,0.42438963,0.00001658529,0.000041770065],"about_ca_topic_score_codex":0.00014059254,"about_ca_topic_score_gemma":0.000013677151,"teacher_disagreement_score":0.66980517,"about_ca_system_score_codex":0.000016658165,"about_ca_system_score_gemma":0.00017358933,"threshold_uncertainty_score":0.6983411},"labels":[],"label_agreement":null},{"id":"W4396708953","doi":"10.1007/s10479-024-05986-7","title":"A robust, resilience machine learning with risk approach: a case study of gas consumption","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Gas consumption; Resilience (materials science); Consumption (sociology); Computer science; Artificial intelligence; Risk analysis (engineering); Economics; Business; Environmental economics; Sociology; Materials science","score_opus":0.1717904189902343,"score_gpt":0.38656119912955667,"score_spread":0.21477078013932235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396708953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99226373,0.0014335441,0.004774187,0.000033973727,0.00003057655,0.00051438995,0.000013558282,0.000092053815,0.0008439868],"genre_scores_gemma":[0.9989514,0.00025351474,0.00018311315,0.0000010927774,0.000025340727,0.00012680083,0.0000033836686,0.000017780649,0.00043757138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865955,0.0003458264,0.00025407993,0.00017614666,0.00038624005,0.00017816781],"domain_scores_gemma":[0.999331,0.00012375759,0.000010807392,0.00020567286,0.00027324515,0.000055500248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012190515,0.000080434584,0.00014955598,0.0003839528,0.00018904243,0.00009151687,0.00008958188,0.00003748288,0.000035891517],"category_scores_gemma":[0.00010363974,0.000064049374,0.000029167779,0.000641533,0.00006946696,0.00016308643,0.000021679074,0.00044023414,0.000015236255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002891275,0.00012267802,0.0013084952,0.0001720511,0.000104021885,0.00011614218,0.0032401371,0.9897423,0.0015094066,0.00007978983,0.00013803803,0.003438067],"study_design_scores_gemma":[0.00025813605,0.0005730166,0.00016399812,0.000060220675,0.000009849766,0.00023908871,0.0062774466,0.9914396,0.00063442416,0.0000018383043,0.00027657996,0.00006584469],"about_ca_topic_score_codex":0.004153431,"about_ca_topic_score_gemma":0.0025188497,"teacher_disagreement_score":0.0066876723,"about_ca_system_score_codex":0.000014619146,"about_ca_system_score_gemma":0.000038236434,"threshold_uncertainty_score":0.6278773},"labels":[],"label_agreement":null},{"id":"W4396739004","doi":"10.1007/s10479-024-06000-w","title":"Correction: A scenario-based robust optimization model for the sustainable distributed permutation flow-shop scheduling problem","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Flow shop scheduling; Permutation (music); Scheduling (production processes); Job shop scheduling; Distributed computing; Mathematical optimization; Operations research; Parallel computing; Mathematics; Embedded system; Routing (electronic design automation)","score_opus":0.11025586097731636,"score_gpt":0.37081598836369317,"score_spread":0.2605601273863768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396739004","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004591772,0.0009853516,0.99373984,0.0031745697,0.00024277768,0.00085456826,0.0000708563,0.00024289648,0.00022994415],"genre_scores_gemma":[0.47823673,0.00042614603,0.5153744,0.00005766763,0.00024064136,0.0010199117,0.0009865192,0.00009158508,0.0035664067],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986226,0.00006616068,0.00032231864,0.00022795776,0.00037954812,0.00038139286],"domain_scores_gemma":[0.9972654,0.0004128027,0.0000110858455,0.00023407668,0.002007659,0.00006897064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013323462,0.00012622542,0.00012406685,0.00034802206,0.0006811442,0.0005257084,0.00018579174,0.00010250242,0.00006306814],"category_scores_gemma":[0.0005390048,0.00010533155,0.0000823434,0.0013057218,0.00007893446,0.00040688482,0.00002610595,0.00031912662,0.000007753163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016622114,0.000032963064,0.0000021019873,0.00017817813,0.000044319077,0.0000011176534,0.0005451719,0.9927761,0.00003645151,0.0014603755,0.0038464211,0.0010601656],"study_design_scores_gemma":[0.00017439404,0.000045544937,0.0000019540385,0.00010266913,0.000015055945,0.0000017158526,0.0009963962,0.99742836,0.00078766944,0.00007667861,0.00025390912,0.000115681454],"about_ca_topic_score_codex":0.000040992403,"about_ca_topic_score_gemma":0.000025745701,"teacher_disagreement_score":0.47836545,"about_ca_system_score_codex":0.000084853,"about_ca_system_score_gemma":0.0004088038,"threshold_uncertainty_score":0.52388793},"labels":[],"label_agreement":null},{"id":"W4396760682","doi":"10.1007/s10479-024-06030-4","title":"On the Ordering of Dynamic Principal Components and the Implications for Portfolio Analysis","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; European Commission; Johns Hopkins University; Canadian Institute for Advanced Research","keywords":"Principal component analysis; Portfolio; Principal (computer security); Computer science; Econometrics; Economics; Financial economics; Artificial intelligence; Computer security","score_opus":0.30944715827190594,"score_gpt":0.43461702986794293,"score_spread":0.12516987159603699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396760682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9628368,0.00213315,0.020416556,0.012680641,0.000024207111,0.00044737908,0.00028695795,0.0000051759675,0.0011691146],"genre_scores_gemma":[0.9984293,0.00088809995,0.0002098982,0.00003688021,0.000011197878,0.00011220604,0.000019145973,0.0000061103506,0.0002871649],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924433,0.000034690245,0.0003652929,0.00017302569,0.000047748155,0.00013493818],"domain_scores_gemma":[0.9988778,0.000584549,0.00002898575,0.00028926102,0.0001997968,0.000019585672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024773309,0.00004641726,0.00017980231,0.00034992877,0.0002907345,0.000079457684,0.00017429389,0.000029226076,0.000033143035],"category_scores_gemma":[0.00054558297,0.000031540527,0.00011369147,0.00075488706,0.00017728235,0.00007389625,0.00005536439,0.00012367486,0.0000057815046],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021142523,0.000030151838,0.0010443643,0.000021464482,0.00013852197,3.4232016e-8,0.00041876725,0.005302589,0.000076363045,0.99198365,0.000111902285,0.0008510343],"study_design_scores_gemma":[0.000114738585,0.000040644278,0.03867277,0.00001662491,0.000012723575,1.607585e-7,0.000057213692,0.88034594,0.00006718982,0.07947997,0.0011502462,0.000041790496],"about_ca_topic_score_codex":0.0006700456,"about_ca_topic_score_gemma":0.00020714702,"teacher_disagreement_score":0.9125037,"about_ca_system_score_codex":0.000009992433,"about_ca_system_score_gemma":0.00003323448,"threshold_uncertainty_score":0.2236124},"labels":[],"label_agreement":null},{"id":"W4399055331","doi":"10.1007/s10479-024-06059-5","title":"Multi-criteria decision aiding for built heritage value assessment: Model and application in Québec City, Canada","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval","funders":"","keywords":"Value (mathematics); Environmental planning; Computer science; Geography; Operations research; Environmental resource management; Engineering; Environmental science; Machine learning","score_opus":0.13651537722603693,"score_gpt":0.45953931698947564,"score_spread":0.3230239397634387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399055331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58321935,0.0014220441,0.4131142,0.0012256297,0.000052962394,0.00068723754,0.00004001633,0.000041997642,0.00019660304],"genre_scores_gemma":[0.9769275,0.0002619754,0.022172123,0.00002213879,0.000024968129,0.00031741773,0.000016425238,0.000022609065,0.00023485116],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990069,0.000041197356,0.00022842505,0.00019850352,0.0002632427,0.0002616898],"domain_scores_gemma":[0.9992714,0.0002663721,0.0000041881954,0.00016564192,0.00022947323,0.00006293426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010113873,0.00008374876,0.00011885477,0.00027037034,0.00014685203,0.00016928962,0.00013016384,0.00004458376,0.000007968366],"category_scores_gemma":[0.00010135504,0.00008509388,0.000021013733,0.00034553133,0.000029717567,0.00022396872,0.000053997886,0.00017428305,4.7025736e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009346856,0.000051628183,0.00030049746,0.00038697867,0.000027802344,0.000006707712,0.00036165948,0.9172052,0.052527763,0.008675508,0.0055549513,0.014891925],"study_design_scores_gemma":[0.00014287682,0.000024665605,0.00063406565,0.00009551,0.000002028761,8.908838e-7,0.00030703525,0.9934696,0.0028348875,0.00069213787,0.0017136236,0.000082662365],"about_ca_topic_score_codex":0.26719758,"about_ca_topic_score_gemma":0.5229739,"teacher_disagreement_score":0.39370817,"about_ca_system_score_codex":0.00022403293,"about_ca_system_score_gemma":0.0010735594,"threshold_uncertainty_score":0.7376822},"labels":[],"label_agreement":null},{"id":"W4399259176","doi":"10.1007/s10479-024-06042-0","title":"Migration to the quadruple bottom line framework for achieving sustainable development goals: the 4Ps of sustainability","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of New Brunswick","funders":"","keywords":"Sustainability; Sustainable development; Triple bottom line; Business; Line (geometry); Process management; Environmental resource management; Environmental planning; Economics; Political science; Environmental science; Ecology; Mathematics","score_opus":0.12760892899847245,"score_gpt":0.4277790237062915,"score_spread":0.3001700947078191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399259176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54687136,0.0013673791,0.114571795,0.32881546,0.00020137963,0.0071193846,0.000012493022,0.00009260768,0.0009481598],"genre_scores_gemma":[0.9897049,0.000037043097,0.0023204237,0.00080299017,0.00054828695,0.0013628211,0.000041133986,0.000034143926,0.0051482567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99739504,0.00014059947,0.00058044196,0.0003851555,0.0007966178,0.0007021581],"domain_scores_gemma":[0.99321014,0.001051855,0.000054235355,0.0007108554,0.004949254,0.000023636652],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.010103399,0.00016410329,0.00020654293,0.00073974166,0.001644971,0.0008329729,0.0008148258,0.00007392002,0.00010779607],"category_scores_gemma":[0.00744284,0.000104515166,0.00011627295,0.0028757777,0.00016772805,0.00082634686,0.0009235707,0.00036739575,0.000025714167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011533719,0.00020668615,0.0007886889,0.0030579893,0.00013071715,0.000007158149,0.0047779246,0.04752629,0.00007308347,0.8897358,0.040713646,0.012866646],"study_design_scores_gemma":[0.00011727858,0.000084477135,0.0020670607,0.00017336539,0.00002654893,2.7163446e-7,0.06900913,0.0559552,0.0012320939,0.032008212,0.8391341,0.00019224657],"about_ca_topic_score_codex":0.0030948222,"about_ca_topic_score_gemma":0.0009327225,"teacher_disagreement_score":0.85772765,"about_ca_system_score_codex":0.00014615247,"about_ca_system_score_gemma":0.00056855334,"threshold_uncertainty_score":0.99965477},"labels":[],"label_agreement":null},{"id":"W4399580936","doi":"10.1007/s10479-024-06097-z","title":"Solving the two-machine open shop problem with a single server with respect to the makespan","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep de Chicoutimi; Université du Québec à Chicoutimi","funders":"Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development","keywords":"Job shop scheduling; Integer programming; Open shop; Computer science; Completeness (order theory); Mathematical optimization; Integer (computer science); Mathematics; Flow shop scheduling; Computer network; Operating system; Routing (electronic design automation)","score_opus":0.13739894770600808,"score_gpt":0.4001093785665289,"score_spread":0.2627104308605208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399580936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38236514,0.009138811,0.2059953,0.27818006,0.00041982424,0.009638808,0.00019775888,0.0010113475,0.113052934],"genre_scores_gemma":[0.9636079,0.00006966732,0.031431966,0.00018898556,0.00011427901,0.00021358521,0.000016183094,0.00005434617,0.004303102],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987429,0.00013788206,0.00016828203,0.00019844325,0.00046595972,0.00028653082],"domain_scores_gemma":[0.9988326,0.00018378993,0.000005290903,0.00043799955,0.00046952543,0.000070825496],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015724289,0.00010411893,0.00010722089,0.00016550784,0.00038466338,0.0010881369,0.0005887984,0.00002463807,0.00014233337],"category_scores_gemma":[0.00008183457,0.000050416875,0.000022492644,0.0014037769,0.00007030231,0.000273764,0.00014119038,0.00036074378,0.00006807933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028097133,0.000027954868,0.000023480852,0.000025892814,0.000077363846,0.0000070342485,0.002063843,0.9890239,0.00033836756,0.0027169317,0.0033851503,0.0022819652],"study_design_scores_gemma":[0.00019084009,0.00033183707,0.000066254004,0.00027809964,0.000008966891,0.000019618905,0.0009720396,0.98034304,0.0052187266,0.00005154189,0.012381837,0.00013721362],"about_ca_topic_score_codex":0.00036851616,"about_ca_topic_score_gemma":0.0042038057,"teacher_disagreement_score":0.58124274,"about_ca_system_score_codex":0.000023759421,"about_ca_system_score_gemma":0.00014235152,"threshold_uncertainty_score":0.9999488},"labels":[],"label_agreement":null},{"id":"W4399915238","doi":"10.1007/s10479-024-06099-x","title":"Estimating and predicting the human development index with uncertain data: a common weight fuzzy benefit-of-the-doubt machine learning approach","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Human Development Index; Fuzzy logic; Rank (graph theory); Mathematics; Measure (data warehouse); Econometrics; Artificial neural network; Fuzzy set; Index (typography); Population; Statistics; Machine learning; Artificial intelligence; Data mining; Computer science; Human development (humanity); Economics","score_opus":0.5296110238330884,"score_gpt":0.541465042957517,"score_spread":0.011854019124428516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399915238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841853,0.0010215869,0.010552551,0.0020112253,0.00007470214,0.00059257296,0.000035572506,0.000025477337,0.0015010363],"genre_scores_gemma":[0.98133224,0.000014338475,0.017491745,0.000030660034,0.00006869749,0.000043137665,0.000029074845,0.000019747224,0.00097035995],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945275,0.000844823,0.00089566485,0.00062089425,0.0027692402,0.00034186864],"domain_scores_gemma":[0.99503267,0.0025763826,0.00010524107,0.0011849742,0.0010187957,0.00008193761],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01635366,0.00014544415,0.00027700374,0.0005083258,0.0017685618,0.0011602467,0.0018665714,0.000060340473,0.00005885727],"category_scores_gemma":[0.0036135965,0.00007230136,0.000039366987,0.0019314387,0.00042939134,0.0006219114,0.0018245034,0.00075203564,0.0000069728553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105035826,0.0003226955,0.17702395,0.00027101635,0.00027847305,0.000022954013,0.026129786,0.41452765,0.0033650617,0.015900418,0.003930881,0.35812205],"study_design_scores_gemma":[0.00018243332,0.000061255676,0.011539432,0.00032820262,0.00000549827,0.000018394892,0.001148717,0.9820797,0.00063846546,0.0012060679,0.0026970208,0.0000948424],"about_ca_topic_score_codex":0.000545497,"about_ca_topic_score_gemma":0.00070960814,"teacher_disagreement_score":0.56755203,"about_ca_system_score_codex":0.000020511648,"about_ca_system_score_gemma":0.0003078404,"threshold_uncertainty_score":0.9998766},"labels":[],"label_agreement":null},{"id":"W4400274616","doi":"10.1007/s10479-024-06136-9","title":"Hybrid metaheuristic for the dial-a-ride problem with private fleet and common carrier integrated with public transportation","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Metaheuristic; Transport engineering; Public transport; Business; Fleet management; Computer science; Operations research; Telecommunications; Engineering; Artificial intelligence","score_opus":0.10714165070929006,"score_gpt":0.36874486405725626,"score_spread":0.2616032133479662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400274616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91000235,0.00077427225,0.07962213,0.006574839,0.00004324963,0.0016100425,0.00091622124,0.00016282948,0.0002940466],"genre_scores_gemma":[0.99680734,0.00020579307,0.0016183599,0.000030722906,0.000018680945,0.000642048,0.0004712182,0.00002853584,0.00017728734],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904835,0.000037133283,0.00026476698,0.00016494344,0.00026965665,0.00021517232],"domain_scores_gemma":[0.998778,0.00023822502,0.00000814986,0.00019316676,0.0007242186,0.00005827817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006329015,0.0001042691,0.0001284576,0.0002416138,0.00023478911,0.00020618465,0.00010986609,0.000028595055,0.00003098377],"category_scores_gemma":[0.00003461737,0.00006402569,0.000026021855,0.0007501315,0.0001958139,0.00032102969,0.0000025202535,0.00024071845,0.0000016397095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042809252,0.00041083767,0.0045972364,0.0024514534,0.0024224364,0.00004669207,0.009772651,0.42579284,0.014744861,0.47601736,0.01650593,0.046809625],"study_design_scores_gemma":[0.0025664542,0.0018980392,0.06093523,0.00084925146,0.00038241709,0.000043016847,0.003115099,0.60108423,0.07595713,0.0030515771,0.24905446,0.0010630791],"about_ca_topic_score_codex":0.00019405104,"about_ca_topic_score_gemma":0.0034135967,"teacher_disagreement_score":0.47296578,"about_ca_system_score_codex":0.000012121705,"about_ca_system_score_gemma":0.00015217254,"threshold_uncertainty_score":0.26108918},"labels":[],"label_agreement":null},{"id":"W4400595039","doi":"10.1007/s10479-024-06131-0","title":"Requirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Selection (genetic algorithm); Quality function deployment; Uncertainty quantification; Computer science; Management science; Artificial intelligence; Engineering; Operations management; Machine learning","score_opus":0.6530890408517598,"score_gpt":0.5876089016102118,"score_spread":0.06548013924154794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400595039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27983397,0.001900766,0.7013203,0.013839329,0.00045965431,0.0013998077,0.00016445984,0.000120007106,0.00096170045],"genre_scores_gemma":[0.97633785,0.000032918553,0.01913165,0.00016741449,0.0001222981,0.0001587257,0.000025607495,0.000032877633,0.003990653],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99378395,0.0010432432,0.001014225,0.0009798248,0.0026045851,0.0005741954],"domain_scores_gemma":[0.99434453,0.0021496941,0.000049138875,0.00072785316,0.002518538,0.00021022379],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0079993885,0.00022094187,0.00039792072,0.001836617,0.0006771728,0.002167707,0.0007685754,0.00014114243,0.001330216],"category_scores_gemma":[0.0032225233,0.00017192203,0.00013041301,0.0024748254,0.00061214645,0.00077945576,0.0003434557,0.00045264454,0.00020711207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004909842,0.0011331908,0.0008397966,0.00038566574,0.0003144239,0.000042333715,0.0069434824,0.6484229,0.15004478,0.06950153,0.08213456,0.039746333],"study_design_scores_gemma":[0.0003803696,0.00015742738,0.00075166975,0.00014805347,0.000007855436,0.000019049523,0.001793994,0.98885626,0.0016419209,0.0034644753,0.0025836283,0.00019533026],"about_ca_topic_score_codex":0.00018822816,"about_ca_topic_score_gemma":0.00018145099,"teacher_disagreement_score":0.6965039,"about_ca_system_score_codex":0.00006897608,"about_ca_system_score_gemma":0.0005608311,"threshold_uncertainty_score":0.9995827},"labels":[],"label_agreement":null},{"id":"W4400907482","doi":"10.1007/s10479-024-06139-6","title":"Comparing groups of units through composite indicators in a non-convex approach: corporate social responsibility for the food and beverage manufacturing industry","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; European Regional Development Fund; Narodowe Centrum Nauki; Agencia Estatal de Investigación; Generalitat Valenciana","keywords":"Corporate social responsibility; Theory of computation; Composite number; Food industry; Beverage industry; Business; Industrial organization; Regular polygon; Marketing; Mathematics; Food science; Chemistry; Public relations; Algorithm; Political science","score_opus":0.5606742607487393,"score_gpt":0.5080849775656662,"score_spread":0.0525892831830731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400907482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99121696,0.0004008147,0.004684289,0.0024979366,0.000038556278,0.0005679461,0.00006264373,0.0000086664,0.0005221803],"genre_scores_gemma":[0.99918437,0.000023332037,0.00047879037,0.000048625738,0.000036686484,0.000046759003,0.000010134862,0.0000100665375,0.0001612059],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99617493,0.00088088744,0.000812652,0.00049401325,0.001314173,0.00032336262],"domain_scores_gemma":[0.99504083,0.0035276357,0.00010544185,0.00047600898,0.000796384,0.00005367314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015004079,0.00011563229,0.00037850364,0.0013456215,0.00062458933,0.00042505685,0.0007338792,0.00016133855,0.00001808537],"category_scores_gemma":[0.0018901144,0.00007877072,0.000088251814,0.0048750825,0.00081123714,0.0004504214,0.00033568288,0.0007798533,0.0000033403508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018516589,0.002831129,0.1959826,0.001311492,0.0015588329,0.000043935903,0.18191963,0.3437918,0.024588535,0.18941854,0.0136852795,0.043016568],"study_design_scores_gemma":[0.00075697136,0.00045277784,0.3234133,0.00021311802,0.00003670252,0.0000069957036,0.014963856,0.56812567,0.07104738,0.019824302,0.00082041946,0.00033850328],"about_ca_topic_score_codex":0.00021581678,"about_ca_topic_score_gemma":0.00026938212,"teacher_disagreement_score":0.22433387,"about_ca_system_score_codex":0.000026055286,"about_ca_system_score_gemma":0.0003430553,"threshold_uncertainty_score":0.5200144},"labels":[],"label_agreement":null},{"id":"W4402547446","doi":"10.1007/s10479-024-06241-9","title":"An updated survey of attended home delivery and service problems with a focus on applications","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Focus (optics); Theory of computation; Computer science; Service (business); Operations research; Management science; Mathematics; Business; Engineering; Marketing; Algorithm","score_opus":0.14443607513241238,"score_gpt":0.3954565609906834,"score_spread":0.25102048585827097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402547446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922395,0.00022677108,0.003967679,0.001566905,0.000011970501,0.0006199381,0.0005211497,0.0001008277,0.0007452844],"genre_scores_gemma":[0.99867374,0.00013487524,0.00036516748,0.00003138571,0.0000077413315,0.0001787567,0.00054720097,0.000016747801,0.000044360488],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9991812,0.00006249786,0.00023103891,0.00015509268,0.00023464163,0.0001355198],"domain_scores_gemma":[0.9983435,0.00007650274,0.000005905012,0.00025238984,0.0012661489,0.000055533365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005777035,0.00006919651,0.00010231899,0.00034954553,0.00008347161,0.000056968816,0.00010627726,0.000043019674,0.000057710222],"category_scores_gemma":[0.0000073886886,0.000060955874,0.000010958701,0.0016095617,0.00007929297,0.00021563978,0.000006234803,0.0001692563,0.000011126486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016627608,0.001187214,0.006698313,0.0014805741,0.000702457,0.000006554324,0.0055445964,0.7188722,0.12929974,0.10380293,0.008300874,0.023938296],"study_design_scores_gemma":[0.00090045674,0.001244971,0.58862954,0.00036880886,0.00003862102,0.000008160562,0.00091347634,0.33800763,0.06254688,0.0011150638,0.005629807,0.0005965897],"about_ca_topic_score_codex":0.0010068711,"about_ca_topic_score_gemma":0.007405089,"teacher_disagreement_score":0.58193123,"about_ca_system_score_codex":0.00000747147,"about_ca_system_score_gemma":0.00010884354,"threshold_uncertainty_score":0.41322136},"labels":[],"label_agreement":null},{"id":"W4402749525","doi":"10.1007/s10479-024-06267-z","title":"Mean-variance optimization with inferred regimes","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Variance (accounting); Computer science; Mathematical optimization; Mathematics; Algorithm; Economics","score_opus":0.19197773032523602,"score_gpt":0.38725637267958346,"score_spread":0.19527864235434744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402749525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022044557,0.0049652187,0.96362954,0.0067245997,0.000055038316,0.00029300226,0.000121978344,0.00003802744,0.021968132],"genre_scores_gemma":[0.98168355,0.0007317509,0.014742943,0.000082538085,0.00010902124,0.00022233828,0.00004484425,0.000021474058,0.0023615556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990967,0.0000076053448,0.00031172734,0.0002896873,0.00008389058,0.00021040234],"domain_scores_gemma":[0.9991787,0.00007858092,0.000024424528,0.00027331972,0.000394463,0.000050529216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066135323,0.00006996401,0.0001526211,0.00034713684,0.00020187539,0.00018346518,0.00019028214,0.000053811844,0.00017663484],"category_scores_gemma":[0.00020377374,0.000067488756,0.000034956232,0.0011896084,0.00012540365,0.00033313085,0.000040375686,0.00015933765,0.00024060174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008276417,0.000046792124,0.000035206325,0.000034995,0.000022588129,0.0000012791493,0.0003656659,0.03173471,0.000015793717,0.9660307,0.0009555683,0.0007484328],"study_design_scores_gemma":[0.0003277426,0.00045366326,0.001236089,0.00023251314,0.0000066042703,0.000011305129,0.00029297874,0.69045144,0.0010633218,0.23177843,0.07374695,0.0003989613],"about_ca_topic_score_codex":0.00037640575,"about_ca_topic_score_gemma":0.000054026958,"teacher_disagreement_score":0.9794791,"about_ca_system_score_codex":0.000016551261,"about_ca_system_score_gemma":0.00013613838,"threshold_uncertainty_score":0.3092529},"labels":[],"label_agreement":null},{"id":"W4403189043","doi":"10.1007/s10479-024-06281-1","title":"Dual dominance: how Harry Markowitz and William Ziemba impacted portfolio management","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Dual (grammatical number); Dominance (genetics); Project portfolio management; Portfolio; Economics; Computer science; Mathematical economics; Management; Financial economics; Philosophy; Biology; Linguistics; Project management; Programming language; Genetics","score_opus":0.16054421804847227,"score_gpt":0.36825736599534875,"score_spread":0.20771314794687648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403189043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7030034,0.025815437,0.0002859926,0.017426027,0.00043173335,0.00087897177,0.00043815642,0.000059762093,0.25166053],"genre_scores_gemma":[0.96160805,0.015257304,0.0004988588,0.00012437117,0.00011064857,0.00008539354,0.000033160257,0.000020426793,0.022261804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987235,0.000038681523,0.0003615773,0.00038072772,0.00011664734,0.00037883053],"domain_scores_gemma":[0.9994009,0.000058098798,0.00002894786,0.00028286,0.00014011728,0.00008904703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014857367,0.00012247855,0.00025385217,0.0006272446,0.00023292525,0.00056621304,0.00014676587,0.00007555893,0.00043805072],"category_scores_gemma":[0.00012867703,0.00012053325,0.00007177791,0.0006672343,0.00023174226,0.0006999295,0.00011823524,0.00020839287,0.00010009175],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002334538,0.0000719353,0.0007324189,0.00018041767,0.000096655094,0.000035557285,0.00023668088,0.000033328048,0.00011714969,0.91336715,0.08125644,0.003848891],"study_design_scores_gemma":[0.00061731995,0.000641722,0.17994481,0.00033598786,0.000011927298,0.000016817767,0.000789298,0.008639584,0.0011395335,0.06685238,0.74044716,0.00056344434],"about_ca_topic_score_codex":0.00019489738,"about_ca_topic_score_gemma":0.000030129831,"teacher_disagreement_score":0.84651476,"about_ca_system_score_codex":0.000024825204,"about_ca_system_score_gemma":0.0000601343,"threshold_uncertainty_score":0.54600054},"labels":[],"label_agreement":null},{"id":"W4403616496","doi":"10.1007/s10479-024-06351-4","title":"Migratory beekeeping routing: a combinatorial optimization problem in apiculture","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beekeeping; Theory of computation; Varroa; Computer science; Combinatorial optimization; Routing (electronic design automation); Mathematical optimization; Mathematics; Biology; Honey bee; Computer network; Ecology; Algorithm","score_opus":0.11323461520207793,"score_gpt":0.417617561499046,"score_spread":0.30438294629696805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403616496","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3999031,0.010537903,0.5426433,0.00855588,0.0023442826,0.003886622,0.00010096593,0.0020430908,0.029984893],"genre_scores_gemma":[0.9332458,0.0003875648,0.06586675,0.000017849068,0.00014728722,0.00008822259,0.00003924547,0.00004391221,0.00016339456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983387,0.00031419034,0.00039768152,0.00021716247,0.00039800513,0.0003342541],"domain_scores_gemma":[0.9990739,0.00017697118,0.000007768412,0.00019388266,0.00048068096,0.00006675823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022442841,0.00010226209,0.000160122,0.0005436646,0.00012483129,0.00021312981,0.00018273406,0.00013456045,0.00005425064],"category_scores_gemma":[0.0003619892,0.00011057158,0.000047406542,0.0017005232,0.000060510392,0.00038563908,0.000050202743,0.0005028763,0.000017711582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033631138,0.0000325568,0.00007783851,0.00012506919,0.000020992284,0.0000050764143,0.0014786606,0.98148584,0.0021924677,0.011544476,0.0011281213,0.0019055252],"study_design_scores_gemma":[0.00013816258,0.000035737852,0.00010602601,0.0002287859,0.0000023432856,0.0000020829978,0.0002284117,0.991545,0.006631266,0.0002106865,0.0007596763,0.00011181784],"about_ca_topic_score_codex":0.00006987034,"about_ca_topic_score_gemma":0.000029177352,"teacher_disagreement_score":0.5333427,"about_ca_system_score_codex":0.00006142162,"about_ca_system_score_gemma":0.0001293659,"threshold_uncertainty_score":0.45089778},"labels":[],"label_agreement":null},{"id":"W4404521915","doi":"10.1007/s10479-024-06397-4","title":"Should we keep the tradition or follow the trend? The optimal live-streaming e-commerce mode selection in a sustainable and circular supply chain under competition","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Humanities and Social Science Fund of Ministry of Education of China","keywords":"Competition (biology); Selection (genetic algorithm); Supply chain; Theory of computation; Mode (computer interface); E-commerce; Industrial organization; Supply chain management; Business; Computer science; Economics; Microeconomics; Marketing; Artificial intelligence; Algorithm; World Wide Web; Biology; Ecology","score_opus":0.12928893507350203,"score_gpt":0.37186213275549274,"score_spread":0.2425731976819907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404521915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6757759,0.0021802913,0.0037243972,0.31072986,0.00010621411,0.0030172672,0.000013852762,0.00010650681,0.00434574],"genre_scores_gemma":[0.99324465,0.0004794614,0.0000369312,0.0009221188,0.0003402231,0.00047956864,0.0000568758,0.000030301791,0.004409885],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979231,0.00028103832,0.00030610518,0.00033319887,0.0006261367,0.0005304488],"domain_scores_gemma":[0.99873984,0.00051407877,0.000031039814,0.0002862326,0.00041405018,0.00001478851],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0034989351,0.00016359509,0.00014903388,0.00069635455,0.0013027767,0.0015359636,0.000397186,0.000065615954,0.00023743285],"category_scores_gemma":[0.0002784633,0.00008994447,0.00007445087,0.0022806735,0.00026496325,0.0012125942,0.00025062115,0.0005250538,0.00001807255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001480696,0.0002512618,0.00045472983,0.0008709605,0.00017512498,0.00006649088,0.004992367,0.22036307,0.00046271298,0.74725133,0.013378037,0.0115858475],"study_design_scores_gemma":[0.0003631244,0.00007804926,0.0041347197,0.00018072002,0.00004443801,0.00000877301,0.117014155,0.82290614,0.00011054179,0.010791235,0.04417854,0.00018954706],"about_ca_topic_score_codex":0.007582704,"about_ca_topic_score_gemma":0.00413944,"teacher_disagreement_score":0.7364601,"about_ca_system_score_codex":0.00010371851,"about_ca_system_score_gemma":0.00012972267,"threshold_uncertainty_score":0.9999974},"labels":[],"label_agreement":null},{"id":"W4405070666","doi":"10.1007/s10479-024-06356-z","title":"Inflation differentials and the diversification benefits of small cap equities in emerging markets for US investors","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Diversification (marketing strategy); Emerging markets; Financial economics; Theory of computation; Economics; Monetary economics; Business; Finance; Computer science; Marketing","score_opus":0.28226950135851475,"score_gpt":0.3667586931506549,"score_spread":0.08448919179214015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405070666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98494655,0.006744465,0.0001454863,0.0030316985,0.0000810783,0.0004501168,0.00013692802,0.0000045678944,0.004459134],"genre_scores_gemma":[0.9954362,0.003689175,0.0001415877,0.000028981427,0.000032533608,0.000095933465,0.000023802455,0.000006705883,0.00054507924],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99916977,0.00005784555,0.0004106516,0.00016107668,0.000053110394,0.00014753437],"domain_scores_gemma":[0.99939966,0.00026927606,0.000042247346,0.00012609665,0.00014406057,0.000018635483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002066518,0.000056828238,0.00017448029,0.00044064203,0.00013686377,0.00011150293,0.000110145906,0.000043841457,0.00004204204],"category_scores_gemma":[0.00044758245,0.00004841087,0.00004459683,0.00029203985,0.00023123913,0.00027145128,0.000053156535,0.00008104601,0.0000029066957],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054161355,0.000023365556,0.0048237047,0.00015327235,0.000022287886,7.667026e-8,0.0016680543,0.0007238718,0.00010671264,0.99013346,0.00033817653,0.0019528563],"study_design_scores_gemma":[0.0010835083,0.0002368063,0.72285485,0.00030983065,0.00000907921,4.995019e-7,0.001752377,0.10082468,0.0025145842,0.1629277,0.007258977,0.00022710887],"about_ca_topic_score_codex":0.00093469286,"about_ca_topic_score_gemma":0.00033577377,"teacher_disagreement_score":0.8272058,"about_ca_system_score_codex":0.000013115743,"about_ca_system_score_gemma":0.00003902398,"threshold_uncertainty_score":0.1974138},"labels":[],"label_agreement":null},{"id":"W4405127688","doi":"10.1007/s10479-024-06410-w","title":"Joint scheduling optimization of production assembly considering testing groups in robot manufacturing","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Anhui Provincial Key Research and Development Plan; Natural Science Foundation of Tianjin Municipal Science and Technology Commission; Anhui Provincial Department of Education; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Theory of computation; Scheduling (production processes); Computer science; Mathematical optimization; Joint (building); Job shop scheduling; Production (economics); Industrial engineering; Manufacturing engineering; Mathematics; Engineering; Algorithm; Economics; Microeconomics; Embedded system; Structural engineering","score_opus":0.21988820941719225,"score_gpt":0.38741430787779163,"score_spread":0.16752609846059938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405127688","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38315213,0.00087640237,0.6138585,0.00031881675,0.00024423946,0.00036618632,0.0000061844544,0.0001851624,0.0009923616],"genre_scores_gemma":[0.88924783,0.00040176188,0.11016187,0.0000025359782,0.0000690123,0.000029988203,0.00001796041,0.00002978412,0.00003922222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998726,0.00006638903,0.00044373958,0.000220546,0.00027838646,0.00026492556],"domain_scores_gemma":[0.9992439,0.00017416324,0.000016639846,0.00019352513,0.00033199365,0.000039741753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009519675,0.00010728168,0.00017108844,0.0007115663,0.00009842045,0.00008059285,0.00008559173,0.00006886859,0.000015502439],"category_scores_gemma":[0.0009200848,0.00011388681,0.00003085597,0.00058097846,0.000068566114,0.00044394826,0.000045459914,0.00034300794,0.00000365804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032716125,0.00002155085,0.000019508712,0.00035435095,0.00001608016,0.000004106489,0.00028487958,0.9773553,0.018349571,0.0005926032,0.000020807664,0.0029779763],"study_design_scores_gemma":[0.00004002954,0.000025059702,0.00016583428,0.00031208433,0.0000022161935,0.0000035069,0.00012890073,0.6898211,0.30917695,0.00024260019,0.0000100706175,0.00007159109],"about_ca_topic_score_codex":0.00007971549,"about_ca_topic_score_gemma":0.000039949304,"teacher_disagreement_score":0.50609577,"about_ca_system_score_codex":0.000049286245,"about_ca_system_score_gemma":0.000060664748,"threshold_uncertainty_score":0.46441692},"labels":[],"label_agreement":null},{"id":"W4405231135","doi":"10.1007/s10479-024-06423-5","title":"Nonradial plant capacity concepts: proposals and attainability","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Inefficiency; Flexibility (engineering); Computer science; Set (abstract data type); Production (economics); Theory of computation; Mathematical optimization; Economics; Mathematics; Microeconomics; Algorithm","score_opus":0.5544661394034994,"score_gpt":0.5942163186117722,"score_spread":0.03975017920827273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405231135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9800369,0.001072599,0.0010601031,0.01495249,0.00009879328,0.00032689978,0.00012802391,0.00002574946,0.0022984254],"genre_scores_gemma":[0.9978627,0.00008143387,0.0005067224,0.00007801188,0.00007760853,0.000022895367,0.000006188005,0.0000065182358,0.0013579116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9950772,0.0012225647,0.00062160305,0.00058904523,0.0021342568,0.0003553123],"domain_scores_gemma":[0.9943679,0.0025735546,0.000020474079,0.00064575346,0.0022459642,0.00014636552],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.018329129,0.000094145835,0.0002553129,0.00075655984,0.00047887606,0.0009332849,0.0005421448,0.000076311175,0.0004585027],"category_scores_gemma":[0.012551516,0.00006493269,0.00009739994,0.0023305938,0.0012331187,0.0005345063,0.00019556074,0.0003474565,0.00019651907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020073945,0.0014735714,0.018957177,0.00033301418,0.00038308644,0.00017020974,0.033487,0.023200601,0.04019194,0.5428102,0.20416395,0.13462852],"study_design_scores_gemma":[0.00034082975,0.0010478788,0.019059254,0.00023334433,0.000029108633,0.00005409009,0.005344673,0.72977066,0.042938434,0.07595935,0.12465203,0.00057033176],"about_ca_topic_score_codex":0.0007196558,"about_ca_topic_score_gemma":0.00057238364,"teacher_disagreement_score":0.7065701,"about_ca_system_score_codex":0.00002603225,"about_ca_system_score_gemma":0.00054536475,"threshold_uncertainty_score":0.99576616},"labels":[],"label_agreement":null},{"id":"W4405272606","doi":"10.1007/s10479-024-06427-1","title":"Correction: Should we keep the tradition or follow the trend? The optimal live-streaming e-commerce mode selection in a sustainable and circular supply chain under competition","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Theory of computation; Competition (biology); Selection (genetic algorithm); Supply chain; Mode (computer interface); Computer science; Operations research; Industrial organization; Mathematical economics; Economics; Microeconomics; Mathematical optimization; Business; Marketing; Artificial intelligence; Mathematics; Algorithm; Biology","score_opus":0.16501313812711402,"score_gpt":0.35409052640716626,"score_spread":0.18907738828005224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405272606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79432124,0.015346944,0.10944763,0.066994056,0.00082473125,0.003145133,0.00019809583,0.0004045698,0.009317625],"genre_scores_gemma":[0.9951835,0.0021015932,0.000054090055,0.000059055597,0.000117994794,0.00014698005,0.000049161874,0.00002106573,0.002266557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885833,0.00019398151,0.00021291344,0.00015864977,0.0002907346,0.00028537065],"domain_scores_gemma":[0.99922687,0.00044216486,0.0000063734537,0.0001555097,0.00013491116,0.000034188004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088980765,0.0001074095,0.00010678023,0.00020444032,0.00053338846,0.00025327769,0.00015254044,0.00007287605,0.000099377525],"category_scores_gemma":[0.000051098912,0.00005953888,0.000048892056,0.00088090583,0.0002044211,0.00023169514,0.000016466849,0.00059823965,0.0000046442096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047086553,0.00008762301,0.0001445794,0.00016956085,0.00011178053,0.000025320669,0.007457075,0.902292,0.0012735202,0.076364726,0.007726504,0.004300206],"study_design_scores_gemma":[0.0001243533,0.000113724614,0.0027016958,0.00009224732,0.000017042954,0.000030026273,0.008657526,0.98146224,0.0007749143,0.0006900028,0.0052467342,0.00008951571],"about_ca_topic_score_codex":0.0009474763,"about_ca_topic_score_gemma":0.0035887654,"teacher_disagreement_score":0.20086229,"about_ca_system_score_codex":0.00006530985,"about_ca_system_score_gemma":0.00009125746,"threshold_uncertainty_score":0.41024467},"labels":[],"label_agreement":null},{"id":"W4405673204","doi":"10.1007/s10479-024-06436-0","title":"Collaborative evolution of logistics platform governance: a three-party evolutionary game perspective","year":2024,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Theory of computation; Perspective (graphical); Corporate governance; Computer science; Game theory; Operations research; Mathematical economics; Economics; Management; Mathematics; Artificial intelligence","score_opus":0.12395492210019927,"score_gpt":0.37482797336484686,"score_spread":0.2508730512646476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405673204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8523309,0.0040559806,0.0024307542,0.0027841525,0.00032794528,0.00072054804,0.00028633702,0.00006567553,0.13699766],"genre_scores_gemma":[0.9986069,0.00016736322,0.00017245302,0.000047191057,0.0003252309,0.000030530136,0.000046994897,0.00001481707,0.0005884918],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877566,0.0000031184327,0.00033043066,0.00023672335,0.00038209843,0.00027197239],"domain_scores_gemma":[0.99744016,0.00009498726,0.00004848072,0.0001997925,0.0022000654,0.000016509704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065023795,0.00010417672,0.00018035443,0.0003319676,0.0001661398,0.00045298366,0.00020941756,0.000069226146,0.00022455066],"category_scores_gemma":[0.0005393394,0.0000920715,0.00007650551,0.0011966955,0.00030116166,0.004486031,0.00016750282,0.00019947272,0.00024144007],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005712452,0.000111159294,0.000296181,0.0001184927,0.000060837076,0.000003733197,0.00013625636,0.008462803,0.0001998879,0.97665495,0.013091709,0.0008068775],"study_design_scores_gemma":[0.0003564629,0.00018989452,0.013061616,0.00032374577,0.00002461496,0.0000032215326,0.0097928345,0.48960012,0.00047150307,0.46366158,0.022175618,0.00033879268],"about_ca_topic_score_codex":0.0021756957,"about_ca_topic_score_gemma":0.0015013429,"teacher_disagreement_score":0.51299334,"about_ca_system_score_codex":0.00014194993,"about_ca_system_score_gemma":0.00038043433,"threshold_uncertainty_score":0.4368132},"labels":[],"label_agreement":null},{"id":"W4406105499","doi":"10.1007/s10479-024-06418-2","title":"Evaluating economies of scope and potential merger: an alternative approach","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"Technologická Agentura České Republiky; European Commission","keywords":"Economies of scope; Scope (computer science); Frontier; Data envelopment analysis; Production (economics); Industrial organization; Production–possibility frontier; Economics; Economies of scale; Business; Microeconomics; Computer science; Mathematics","score_opus":0.5888806930953248,"score_gpt":0.6232797523450749,"score_spread":0.034399059249750175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406105499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9845981,0.0006381611,0.0061969925,0.0016183051,0.00004580075,0.00021542286,0.000017737682,0.000004546649,0.0066649253],"genre_scores_gemma":[0.99129283,0.00013791442,0.006725835,0.00004598864,0.000024774936,0.000015631744,0.000005707003,0.0000039444717,0.0017473554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99597406,0.0012531882,0.0007368759,0.0004469373,0.0013668837,0.00022204554],"domain_scores_gemma":[0.99497515,0.0007492685,0.000078324716,0.00060639594,0.0035282674,0.00006260005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01627177,0.00007694017,0.00029392765,0.0012604514,0.0004322759,0.0002871505,0.000718244,0.000047363905,0.00016257704],"category_scores_gemma":[0.006248607,0.000060096703,0.00007488376,0.0017036535,0.0006013207,0.0005455703,0.0002867761,0.00016448129,0.000013115368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010452639,0.0006762739,0.002449354,0.00003456645,0.00018669905,0.000001267256,0.0031547355,0.803489,0.05090835,0.06539221,0.002983669,0.07061932],"study_design_scores_gemma":[0.00019666315,0.00024998546,0.0048138513,0.000033179847,0.000011792055,8.536423e-7,0.0026244842,0.9473336,0.035840675,0.008667197,0.00014781053,0.00007990329],"about_ca_topic_score_codex":0.00059894985,"about_ca_topic_score_gemma":0.00012631327,"teacher_disagreement_score":0.14384457,"about_ca_system_score_codex":0.000010201913,"about_ca_system_score_gemma":0.00037032334,"threshold_uncertainty_score":0.7480617},"labels":[],"label_agreement":null},{"id":"W4406106880","doi":"10.1007/s10479-024-06442-2","title":"Sustainable vehicle route planning under uncertainty for modular integrated construction: multi-trip time-dependent VRP with time windows and data analytics","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Vehicle routing problem; Modular design; Truck; Computer science; Transport engineering; Integer programming; Operations research; Ant colony optimization algorithms; Routing (electronic design automation); Engineering; Computer network","score_opus":0.15333913247327524,"score_gpt":0.4288628080374323,"score_spread":0.2755236755641571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406106880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14162044,0.0005982265,0.8538199,0.001483243,0.00004057645,0.0012787661,0.00025923815,0.00016488049,0.0007347167],"genre_scores_gemma":[0.7574651,0.00015662,0.2248714,0.000102715545,0.000062789884,0.00012470625,0.0007214153,0.00007744476,0.016417764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839085,0.00022195943,0.0003364531,0.00034129753,0.00029333372,0.00041610503],"domain_scores_gemma":[0.9974361,0.00034418603,0.000022081602,0.0006033831,0.0015074494,0.0000867805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00215245,0.00014510458,0.00025461882,0.0004420421,0.00039926675,0.00022943964,0.00035450963,0.000108285814,0.00005053692],"category_scores_gemma":[0.00063892145,0.00013474586,0.000023826524,0.0009995429,0.0001937465,0.0004185296,0.0001919755,0.0003068233,0.000005078705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005196673,0.000036140194,0.00033829163,0.00009097184,0.00016944655,0.0000032695377,0.00013303338,0.993665,0.002400079,0.000897946,0.0011736542,0.0010402028],"study_design_scores_gemma":[0.00073027617,0.00007039622,0.00019399467,0.00008639813,0.000022695538,0.0000037526945,0.0012436883,0.99228024,0.004249885,0.00009384672,0.00089543225,0.00012939329],"about_ca_topic_score_codex":0.00020476159,"about_ca_topic_score_gemma":0.000032723787,"teacher_disagreement_score":0.6289485,"about_ca_system_score_codex":0.000077631936,"about_ca_system_score_gemma":0.0003361718,"threshold_uncertainty_score":0.5494777},"labels":[],"label_agreement":null},{"id":"W4406927510","doi":"10.1007/s10479-024-06327-4","title":"A generalized approach for multi-criteria decision aid methods","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Qatar National Library; Qatar University","keywords":"Theory of computation; Computer science; Mathematical optimization; Mathematics; Algorithm","score_opus":0.8288587454749092,"score_gpt":0.7196189920463937,"score_spread":0.10923975342851555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406927510","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05507359,0.00080097595,0.9379739,0.001933799,0.0003937347,0.0014504817,0.00010477043,0.000030879684,0.002237849],"genre_scores_gemma":[0.09701992,0.000089568784,0.89230025,0.00044663428,0.000084943094,0.00043839074,0.000028485116,0.00002372081,0.009568072],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9910232,0.0030215054,0.0017941785,0.0011114671,0.0023376995,0.00071196386],"domain_scores_gemma":[0.98225695,0.0077023534,0.000099043245,0.0018875094,0.007851563,0.0002025747],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.038934197,0.00022836469,0.00069434603,0.0027794642,0.0009509583,0.0012519516,0.0022575953,0.00021436646,0.0007481348],"category_scores_gemma":[0.05722931,0.00017319834,0.00035554793,0.0038802887,0.00034642278,0.00065159076,0.00085764367,0.00034452853,0.000073798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011114888,0.0011303404,0.0003539947,0.000056154702,0.00012047153,0.000003903117,0.0012350921,0.013406603,0.09763608,0.057491526,0.19137602,0.63607836],"study_design_scores_gemma":[0.0017932674,0.000116528405,0.0008736853,0.000063021114,0.0000070152573,0.000002626586,0.0007404105,0.85250413,0.031155653,0.017037634,0.09551468,0.00019133813],"about_ca_topic_score_codex":0.00013823215,"about_ca_topic_score_gemma":0.00006632732,"teacher_disagreement_score":0.83909756,"about_ca_system_score_codex":0.000038547645,"about_ca_system_score_gemma":0.00048265065,"threshold_uncertainty_score":0.9997848},"labels":[],"label_agreement":null},{"id":"W4407021778","doi":"10.1007/s10479-024-06390-x","title":"Value-at-risk constrained portfolios in incomplete markets: a dynamic programming approach to Heston’s model","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Technische Universität München","keywords":"Theory of computation; Dynamic programming; Heston model; Incomplete markets; Value (mathematics); Value at risk; Econometrics; Computer science; Mathematical optimization; Mathematics; Economics; Mathematical economics; Risk management; Stochastic volatility; Statistics; SABR volatility model; Microeconomics; Volatility (finance); Algorithm; Finance","score_opus":0.12461591006994675,"score_gpt":0.3808112805915064,"score_spread":0.2561953705215596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407021778","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11788613,0.0010896848,0.8385644,0.0043483307,0.00003201484,0.0015376849,0.00044548113,0.000026389229,0.03606986],"genre_scores_gemma":[0.964858,0.00018800971,0.03248896,0.00019084495,0.000012905724,0.0009795288,0.000046631358,0.000014457656,0.001220666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824744,0.000022829772,0.00071096414,0.0004770043,0.000100857855,0.00044089823],"domain_scores_gemma":[0.99901325,0.000091518355,0.000065062486,0.00042968878,0.00030651814,0.0000939816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018415833,0.00011893496,0.00032877704,0.0010533817,0.0003503694,0.00007997866,0.00040620775,0.000093198774,0.000019435165],"category_scores_gemma":[0.0008230197,0.00013883485,0.00007274407,0.0018597426,0.00015772221,0.0001329006,0.00022238896,0.00027115108,0.00006389666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039170365,0.00034717802,0.0010837326,0.000053963646,0.000025241108,5.595558e-7,0.00045012592,0.02689361,0.000056844932,0.9657559,0.00036452466,0.004929166],"study_design_scores_gemma":[0.00042843568,0.00007609989,0.014287194,0.00005591558,0.0000032095877,0.0000016517067,0.0002470139,0.8310893,0.00006754053,0.14946947,0.004060636,0.00021353658],"about_ca_topic_score_codex":0.001111993,"about_ca_topic_score_gemma":0.00032162026,"teacher_disagreement_score":0.84697187,"about_ca_system_score_codex":0.00011060048,"about_ca_system_score_gemma":0.00022685874,"threshold_uncertainty_score":0.56615204},"labels":[],"label_agreement":null},{"id":"W4407194486","doi":"10.1007/s10479-025-06477-z","title":"Sustainable ridesharing routing and scheduling problem: an efficient multi-objective adaptive large neighborhood search","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Hebei Province Outstanding Youth Fund; Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China","keywords":"Computer science; Theory of computation; Scheduling (production processes); Vehicle routing problem; Mathematical optimization; Job shop scheduling; Routing (electronic design automation); Distributed computing; Computer network; Mathematics; Algorithm","score_opus":0.10301871189886422,"score_gpt":0.40639415954148794,"score_spread":0.3033754476426237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407194486","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87345403,0.000281689,0.12095652,0.00044129184,0.000028515724,0.00092269643,0.00004737206,0.00011620444,0.0037516807],"genre_scores_gemma":[0.9924818,0.000050059487,0.006716351,0.000029594747,0.000014928761,0.000121888515,0.000037393995,0.000016313948,0.00053165806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851614,0.00010200033,0.00033706985,0.0002572779,0.00027734274,0.0005101681],"domain_scores_gemma":[0.9976856,0.00010872254,0.000009005101,0.00023704396,0.001875902,0.000083693056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017667415,0.00010841646,0.00015183544,0.00063223846,0.00061206985,0.00013622841,0.00014951656,0.000073675714,0.000027818378],"category_scores_gemma":[0.00018892688,0.00011589674,0.00003055837,0.0013970328,0.00010167602,0.00033666057,0.000064255786,0.0004377896,0.000004124637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016716634,0.00024963857,0.001811543,0.00014358213,0.000073417636,0.0000024235642,0.0048310873,0.7630304,0.0031316043,0.2256601,0.000037270107,0.0010121756],"study_design_scores_gemma":[0.0004776604,0.00008051184,0.01849386,0.00009832461,0.0000064532037,5.6412e-7,0.01981125,0.94872916,0.011907201,0.00017348614,0.00009609943,0.00012544381],"about_ca_topic_score_codex":0.0005299235,"about_ca_topic_score_gemma":0.0004915385,"teacher_disagreement_score":0.22548662,"about_ca_system_score_codex":0.00005351901,"about_ca_system_score_gemma":0.00024149999,"threshold_uncertainty_score":0.4726132},"labels":[],"label_agreement":null},{"id":"W4407664878","doi":"10.1007/s10479-025-06504-z","title":"Enhancing unmanned aerial vehicles logistics for dynamic delivery: a hybrid non-dominated sorting genetic algorithm II with Bayesian belief networks","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Sorting; Theory of computation; Computer science; Genetic algorithm; Bayesian probability; Algorithm; Artificial intelligence; Dynamic Bayesian network; Machine learning; Operations research; Mathematics","score_opus":0.024493277238973633,"score_gpt":0.33428920772002013,"score_spread":0.3097959304810465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407664878","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09271788,0.0002912494,0.9055934,0.0002773445,0.000049514558,0.0007857997,0.000044006658,0.000050731698,0.00019006894],"genre_scores_gemma":[0.90869933,0.00041439166,0.089976236,0.000027216927,0.000062601655,0.00035358424,0.00017109381,0.000030299556,0.00026523508],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877375,0.0000433623,0.00038390982,0.00022412717,0.0001871002,0.0003877203],"domain_scores_gemma":[0.99850345,0.00013793571,0.000023469403,0.0002804193,0.0009951493,0.000059559712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048299777,0.00012760024,0.00018967649,0.0003026394,0.0006195259,0.00010177212,0.00020175627,0.00007598371,0.000012622221],"category_scores_gemma":[0.00007808922,0.0001266847,0.00004122132,0.00070551876,0.000099232,0.00011384278,0.000067040375,0.00018741118,0.0000019360643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027428197,0.000057468573,0.00001309737,0.000052677253,0.00006412552,0.0000011573454,0.00009880441,0.97390324,0.0047593764,0.00037855175,0.00055583596,0.020088263],"study_design_scores_gemma":[0.0003893099,0.00015685886,0.00019856486,0.00008910988,0.000016103575,0.000001229695,0.00011565461,0.98133546,0.017245116,0.0001544402,0.00017821422,0.00011993788],"about_ca_topic_score_codex":0.0001189936,"about_ca_topic_score_gemma":0.0003548352,"teacher_disagreement_score":0.81598145,"about_ca_system_score_codex":0.000046187244,"about_ca_system_score_gemma":0.00014356246,"threshold_uncertainty_score":0.5166052},"labels":[],"label_agreement":null},{"id":"W4408348918","doi":"10.1007/s10479-025-06541-8","title":"Two-stage hybrid flow shop scheduling with sequence-dependent setup times in semiconductor manufacturing: A customized variable neighborhood search","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Theory of computation; Scheduling (production processes); Flow shop scheduling; Variable neighborhood search; Computer science; Stage (stratigraphy); Variable (mathematics); Job shop scheduling; Sequence (biology); Mathematical optimization; Industrial engineering; Mathematics; Algorithm; Engineering; Embedded system; Metaheuristic; Chemistry","score_opus":0.08975714486119546,"score_gpt":0.37725509621016456,"score_spread":0.2874979513489691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408348918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9109712,0.0007817498,0.06956337,0.0014160264,0.00020880857,0.0011996834,0.00017915129,0.00027819726,0.015401823],"genre_scores_gemma":[0.91801417,0.00023718967,0.07784234,0.00006116631,0.00005306832,0.00012222854,0.00009056197,0.000042567335,0.0035367352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977171,0.00023817027,0.00045201363,0.00037257915,0.0006075949,0.0006125469],"domain_scores_gemma":[0.9985151,0.00023930405,0.000014183784,0.0004782356,0.0006221339,0.00013102422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016407184,0.00020141297,0.00032872998,0.00095546426,0.0002787716,0.00031387853,0.00039415347,0.00009107106,0.00057992066],"category_scores_gemma":[0.00021445155,0.00018688412,0.00004749197,0.0010174557,0.00014059647,0.0004093646,0.00011003119,0.0007733537,0.000043158783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006404539,0.00008017332,0.00014929728,0.000098107026,0.00009114652,0.00001854796,0.00031240584,0.99134535,0.005171514,0.0016490136,0.00012876549,0.00089165807],"study_design_scores_gemma":[0.0011249962,0.000039429076,0.000020113479,0.00017272959,0.0000054065563,0.0000042930546,0.0007405897,0.8349131,0.1626317,0.000088157256,0.000099155826,0.0001603477],"about_ca_topic_score_codex":0.0003753284,"about_ca_topic_score_gemma":0.000101739315,"teacher_disagreement_score":0.15746018,"about_ca_system_score_codex":0.00010339426,"about_ca_system_score_gemma":0.00062683166,"threshold_uncertainty_score":0.76209134},"labels":[],"label_agreement":null},{"id":"W4408970799","doi":"10.1007/s10479-025-06552-5","title":"Adaptive optimization approach for production and distribution planning of perishable food products under demand uncertainty","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Theory of computation; Production (economics); Production planning; Food processing; Computer science; Distribution (mathematics); Mathematical optimization; Operations research; Mathematics; Economics; Microeconomics; Food science; Chemistry; Algorithm","score_opus":0.2041402963296177,"score_gpt":0.37813680160171736,"score_spread":0.17399650527209967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408970799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38836437,0.0013446779,0.58257276,0.012859006,0.00029878604,0.004824886,0.00006711381,0.000065031796,0.00960339],"genre_scores_gemma":[0.99608797,0.000036588273,0.0023737408,0.00010749852,0.00016055751,0.00019501986,0.00030630516,0.000007746943,0.0007245863],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902964,0.00003878961,0.00023808917,0.00026820914,0.00023547887,0.00018978487],"domain_scores_gemma":[0.99811035,0.000031664797,0.000058621863,0.00017544316,0.0016163172,0.000007598519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001324786,0.00008028107,0.00013746398,0.00033713796,0.00036002693,0.000113859904,0.000108149514,0.00004151509,0.000012527731],"category_scores_gemma":[0.0008077829,0.00007535888,0.000027780723,0.00081223564,0.00016278683,0.0006430745,0.00011064297,0.00007849786,4.1300981e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011756895,0.00018064927,0.00061366294,0.00055499177,0.00006758738,5.684066e-8,0.00010179933,0.91815484,0.00025944074,0.064812504,0.014757278,0.00037961788],"study_design_scores_gemma":[0.00035328115,0.0001119076,0.0015646237,0.00015726133,0.000028974775,1.7503699e-7,0.004836388,0.98568624,0.0030722786,0.0012526984,0.002817582,0.000118602096],"about_ca_topic_score_codex":0.00011646541,"about_ca_topic_score_gemma":0.000018301149,"teacher_disagreement_score":0.6077236,"about_ca_system_score_codex":0.000019547948,"about_ca_system_score_gemma":0.000050284845,"threshold_uncertainty_score":0.3073046},"labels":[],"label_agreement":null},{"id":"W4409284532","doi":"10.1007/s10479-025-06561-4","title":"Two simplex-based approximate stochastic dynamic programming schemes for a real hydropower management problem","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Rio Tinto (Canada); Université Laval; Laurentian University","funders":"","keywords":"Theory of computation; Mathematical optimization; Stochastic programming; Dynamic programming; Simplex; Computer science; Simplex algorithm; Hydropower; Mathematics; Linear programming; Algorithm; Combinatorics","score_opus":0.06274712068409638,"score_gpt":0.4042494648851683,"score_spread":0.3415023442010719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409284532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03415056,0.00020285048,0.94785064,0.001262642,0.000057903424,0.00371207,0.000019033736,0.000244513,0.012499797],"genre_scores_gemma":[0.9456456,0.00006705684,0.04960741,0.00002981867,0.000015957146,0.0010954363,0.00019515738,0.00003260729,0.0033109754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988516,0.000042355292,0.00024449552,0.00020347655,0.0002673594,0.00039069046],"domain_scores_gemma":[0.999341,0.000047065318,0.000011332298,0.00025524598,0.00030533387,0.00004003296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006487656,0.00011416036,0.00013497588,0.000584844,0.00021746554,0.00016990537,0.00022715515,0.0000358652,0.000026851452],"category_scores_gemma":[0.000024349985,0.00011190084,0.000056709094,0.00065521477,0.00006879181,0.00014251098,0.00007797425,0.00010662644,0.0000052697196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029200117,0.000081005164,0.000015015371,0.0006290859,0.00010913545,9.4400224e-7,0.0001011188,0.9645213,0.00019988873,0.01672368,0.0009866958,0.016602969],"study_design_scores_gemma":[0.0005012787,0.000059973136,0.000024621824,0.000111608475,0.000014231062,6.1016856e-8,0.00013856073,0.9874785,0.0011228829,0.00046641167,0.009979172,0.00010270486],"about_ca_topic_score_codex":0.000023687893,"about_ca_topic_score_gemma":0.00007466975,"teacher_disagreement_score":0.91149503,"about_ca_system_score_codex":0.000036334768,"about_ca_system_score_gemma":0.000024299317,"threshold_uncertainty_score":0.45631838},"labels":[],"label_agreement":null},{"id":"W4409542906","doi":"10.1007/s10479-025-06608-6","title":"Management science in the age of the internet and digital revolution","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Theory of computation; The Internet; Digital Revolution; Computer science; World Wide Web; Telecommunications; Algorithm","score_opus":0.22820790542207878,"score_gpt":0.43675045399961243,"score_spread":0.20854254857753365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409542906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91552925,0.00023640587,0.0005651963,0.0111931795,0.00010276673,0.00047115592,0.000005715963,0.0000047618596,0.07189159],"genre_scores_gemma":[0.99839264,0.00008741138,0.000020995043,0.00026389514,0.000022159444,0.000015045946,0.0000062133736,0.000001503085,0.0011901131],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99918175,0.000017338194,0.0001609809,0.00013016314,0.0003729211,0.0001368262],"domain_scores_gemma":[0.9992976,0.00003706938,0.00001662186,0.00028184996,0.0003646108,0.000002212727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014949355,0.000039296676,0.0000555951,0.000388879,0.00018084169,0.0003599705,0.00068020605,0.000014797123,0.000020171396],"category_scores_gemma":[0.00037468827,0.000022572118,0.000016098313,0.0021721302,0.0006167463,0.00090083265,0.0005867175,0.00010038537,0.0000072379326],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029122151,0.00025371846,0.03657081,0.0003578479,0.0000138822315,0.000003932529,0.00028862926,0.00027539348,0.0011629286,0.8983662,0.0208891,0.041788403],"study_design_scores_gemma":[0.00022093982,0.00002036668,0.83546907,0.00070769177,0.000011152266,0.0000012682742,0.0024311915,0.014430404,0.0028570106,0.014150779,0.12956794,0.00013220061],"about_ca_topic_score_codex":0.0005961899,"about_ca_topic_score_gemma":0.00024576587,"teacher_disagreement_score":0.8842155,"about_ca_system_score_codex":0.000005922686,"about_ca_system_score_gemma":0.00002841246,"threshold_uncertainty_score":0.34712037},"labels":[],"label_agreement":null},{"id":"W4410636405","doi":"10.1007/s10479-025-06663-z","title":"On random weighted coherent systems based on a new structure-based performance measure","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Measure (data warehouse); Theory of computation; Computer science; Mathematics; Algorithm; Data mining","score_opus":0.25078242180109456,"score_gpt":0.4881953319757417,"score_spread":0.23741291017464716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410636405","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.074984975,0.00006370646,0.89468503,0.012999185,0.00011431806,0.002387821,0.0008292762,0.00009891305,0.013836779],"genre_scores_gemma":[0.9955317,0.000004997779,0.002229839,0.00032635374,0.000024573568,0.00020712268,0.00018820414,0.000010610285,0.0014766491],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979876,0.00032166464,0.00041146317,0.0002393567,0.00079167244,0.0002481969],"domain_scores_gemma":[0.99643785,0.0016393665,0.00003689177,0.00050045724,0.0012608065,0.00012461482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007761411,0.00012587411,0.00022896897,0.0003455906,0.00040410305,0.000113147435,0.00023646916,0.00008609317,0.0006047305],"category_scores_gemma":[0.0022444034,0.00010216918,0.00006034524,0.0008658678,0.00011598698,0.000050576687,0.000016874204,0.0002930346,0.00006566267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002573424,0.0003694479,0.000020619034,0.00014164057,0.000025962949,4.3946255e-7,0.000022068007,0.034124006,0.00045731146,0.8907266,0.072282076,0.0015724562],"study_design_scores_gemma":[0.0019406381,0.00023226645,0.0008365344,0.00044433412,0.000013579501,2.1397032e-7,0.000029833207,0.96863014,0.012137358,0.013754743,0.0018595215,0.00012083159],"about_ca_topic_score_codex":0.00006233434,"about_ca_topic_score_gemma":0.000023201996,"teacher_disagreement_score":0.9345061,"about_ca_system_score_codex":0.00005552481,"about_ca_system_score_gemma":0.0006539857,"threshold_uncertainty_score":0.6621375},"labels":[],"label_agreement":null},{"id":"W4410637431","doi":"10.1007/s10479-025-06616-6","title":"Selecting a sustainable hydrogen production method using a novel dual evaluation EDAS approach","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Khalifa University of Science, Technology and Research","keywords":"EDAS; Theory of computation; Dual (grammatical number); Computer science; Production (economics); Mathematical optimization; Mathematics; Artificial intelligence; Algorithm; Estimation of distribution algorithm; Microeconomics; Economics","score_opus":0.3230636913130012,"score_gpt":0.512624896531063,"score_spread":0.1895612052180618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410637431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8521919,0.00096925726,0.07616765,0.0018473301,0.00024136378,0.0021757518,0.0000062049485,0.00010390244,0.06629662],"genre_scores_gemma":[0.9560572,0.000017856559,0.02307635,0.000029627734,0.0002890909,0.0004057644,0.000057483914,0.000032080618,0.020034527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99544287,0.0016092143,0.00056137325,0.00055921986,0.0011562555,0.0006710572],"domain_scores_gemma":[0.9938779,0.00016565349,0.000056151355,0.0005764345,0.0052465424,0.00007730749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012858423,0.00015524784,0.00028116992,0.0011309569,0.0009268441,0.00016119404,0.00024384227,0.00012646758,0.00006517787],"category_scores_gemma":[0.004058093,0.00015421517,0.00008456293,0.003289986,0.000095112155,0.00051579677,0.00017387122,0.0003159515,0.000006639351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023305662,0.00020715513,0.000029503703,0.00010398609,0.00012379234,9.467695e-7,0.0004777045,0.7816331,0.16222529,0.05290119,0.00046588777,0.00180818],"study_design_scores_gemma":[0.00027468923,0.00004593584,0.000019723486,0.00006463382,0.000023804396,0.000020724592,0.0026547567,0.67950416,0.31141245,0.00077430916,0.0050815856,0.0001232388],"about_ca_topic_score_codex":0.030956823,"about_ca_topic_score_gemma":0.0009503516,"teacher_disagreement_score":0.14918716,"about_ca_system_score_codex":0.00027282076,"about_ca_system_score_gemma":0.0017410036,"threshold_uncertainty_score":0.9754961},"labels":[],"label_agreement":null},{"id":"W4411625814","doi":"10.1007/s10479-025-06699-1","title":"Optimal smoothing mechanism for actuarial discount rate in pension liability valuation in North America","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Key Technologies Research and Development Program; Fundamental Research Funds for the Central Universities; Shanghai Office of Philosophy and Social Science; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Valuation (finance); Actuarial science; Liability; Pension; Economics; Mechanism (biology); Econometrics; Finance","score_opus":0.19287666443157714,"score_gpt":0.49615709386717866,"score_spread":0.3032804294356015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411625814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9817895,0.00003296367,0.0039558294,0.009575504,0.0001736357,0.0019387754,0.000023879527,0.000012939515,0.002496957],"genre_scores_gemma":[0.9973717,0.00038296156,0.0012739449,0.00016667026,0.000055654724,0.00037126755,0.000035679506,0.000005981382,0.000336143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9968192,0.0012761903,0.00044395923,0.00033709305,0.00068611593,0.00043744565],"domain_scores_gemma":[0.998081,0.00042756216,0.00003595216,0.00028146178,0.001129754,0.000044238448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008757534,0.00008495986,0.00019761671,0.0007111515,0.0006168999,0.00016888841,0.00032229637,0.00007257823,0.00003793983],"category_scores_gemma":[0.002627144,0.00008585164,0.000073817384,0.0018711705,0.0003093944,0.00046737478,0.00010927115,0.00024381392,0.0000056395766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046634936,0.0015248839,0.06302502,0.00019849447,0.00008166354,0.000006520963,0.041039072,0.1351556,0.001490039,0.7348953,0.0018066202,0.020310476],"study_design_scores_gemma":[0.002215868,0.000518264,0.7068747,0.00025247067,0.000025308958,4.9078835e-8,0.029134337,0.18445112,0.0026670876,0.06339279,0.009940549,0.0005274168],"about_ca_topic_score_codex":0.02185105,"about_ca_topic_score_gemma":0.13337953,"teacher_disagreement_score":0.6715025,"about_ca_system_score_codex":0.00011529614,"about_ca_system_score_gemma":0.0005289306,"threshold_uncertainty_score":0.98466253},"labels":[],"label_agreement":null},{"id":"W4411870151","doi":"10.1007/s10479-025-06704-7","title":"Emerging trends in the interplay between analytics and operations in MSMEs","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Theory of computation; Analytics; Computer science; Data science; Algorithm","score_opus":0.2964710677610711,"score_gpt":0.5148256317080159,"score_spread":0.21835456394694475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411870151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9352459,0.0003771591,0.0008372836,0.045960847,0.00005571583,0.00024009806,0.000015760768,0.000010104211,0.017257174],"genre_scores_gemma":[0.9983212,0.00014588775,0.000064412685,0.0005088332,0.000100164194,0.00003094253,0.000075067,0.0000043922273,0.0007491171],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99895936,0.000058199326,0.00031547513,0.00018761914,0.00025324852,0.0002260768],"domain_scores_gemma":[0.999224,0.00012354991,0.000012136199,0.00025769338,0.00037698832,0.0000056400168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017447765,0.00007677915,0.00013722834,0.0017129192,0.00023576358,0.0004354989,0.00040598222,0.000046077093,0.00014216862],"category_scores_gemma":[0.00042395346,0.00005701409,0.000023524282,0.0033868912,0.00014214912,0.00090591074,0.0002280203,0.00026540653,0.000013377373],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046108467,0.00052265736,0.3678111,0.00026329546,0.000073454925,0.000015004075,0.001779225,0.01613021,0.00065895193,0.36380753,0.037009515,0.21188295],"study_design_scores_gemma":[0.00049651536,0.000035673416,0.7232468,0.00050657376,0.000026353788,0.000001111285,0.0058027795,0.18578054,0.0008965125,0.0041935965,0.07868996,0.0003235602],"about_ca_topic_score_codex":0.0040682587,"about_ca_topic_score_gemma":0.012861334,"teacher_disagreement_score":0.35961393,"about_ca_system_score_codex":0.000007816173,"about_ca_system_score_gemma":0.000041372256,"threshold_uncertainty_score":0.7176926},"labels":[],"label_agreement":null},{"id":"W4412552465","doi":"10.1007/s10479-025-06638-0","title":"A hybrid approach for resilient sourcing and supply chain network design","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Theory of computation; Supply chain; Computer science; Supply chain network; Supply chain management; Chain (unit); Business; Algorithm; Marketing","score_opus":0.12748517526952988,"score_gpt":0.37801052959982556,"score_spread":0.25052535433029566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412552465","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18214153,0.0034696371,0.7571767,0.025565002,0.00027458373,0.0067106658,0.00001611555,0.00012155816,0.024524225],"genre_scores_gemma":[0.9829825,0.00033121274,0.010401085,0.0013346561,0.00045289352,0.0005541992,0.000051276704,0.000018230145,0.003873914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842024,0.0000678398,0.00029836534,0.00035734347,0.00035308828,0.0005031259],"domain_scores_gemma":[0.9987667,0.00022351752,0.00003139525,0.00030513885,0.00065543276,0.000017787734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033618093,0.00012017562,0.00019354849,0.000633536,0.00082038966,0.00040655988,0.00031426738,0.000041157742,0.000033650056],"category_scores_gemma":[0.00043558326,0.00010370191,0.000060394705,0.0008209762,0.00016955455,0.00042861386,0.0003071599,0.0001459656,0.000009212678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022867323,0.0003124317,0.0031163457,0.0006055662,0.00010608868,0.0000037978527,0.00015648156,0.45794278,0.0003806072,0.20355742,0.3151318,0.018457996],"study_design_scores_gemma":[0.000702934,0.00008075146,0.002639243,0.0001718546,0.000029117924,6.8795447e-7,0.001763149,0.9248483,0.0014879919,0.011066928,0.056969605,0.00023942889],"about_ca_topic_score_codex":0.0005182429,"about_ca_topic_score_gemma":0.00004365255,"teacher_disagreement_score":0.80084103,"about_ca_system_score_codex":0.000011591339,"about_ca_system_score_gemma":0.000070017864,"threshold_uncertainty_score":0.6309857},"labels":[],"label_agreement":null},{"id":"W4412639113","doi":"10.1007/s10479-025-06685-7","title":"A closed loop supply chain with environmental, manufacturing and recycling decisions","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Supply chain; Theory of computation; Closed loop; Loop (graph theory); Computer science; Operations research; Business; Mathematics; Engineering; Control engineering; Algorithm","score_opus":0.07999693406996555,"score_gpt":0.3551215444414657,"score_spread":0.27512461037150016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412639113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9768207,0.00030976004,0.0008897738,0.012069187,0.000036868125,0.00083528704,0.0000049102982,0.000032680033,0.009000827],"genre_scores_gemma":[0.99203813,0.0003372545,0.0006071624,0.00088330073,0.00009376621,0.0001142843,0.00003683201,0.000019568975,0.005869716],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99835443,0.000050499086,0.0002853211,0.00035997844,0.0005119012,0.0004378564],"domain_scores_gemma":[0.99910283,0.00022863214,0.00003139047,0.00040755843,0.00020827602,0.000021323252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014802587,0.00013910979,0.00017933369,0.0012004547,0.0006793867,0.00045357968,0.00030073457,0.000050538958,0.00026692942],"category_scores_gemma":[0.00034284228,0.00012090228,0.000036693742,0.000680524,0.00021565796,0.0007196508,0.0005439227,0.00023454074,0.00004264595],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014018902,0.0025006677,0.09166905,0.0020717864,0.0011722388,0.00038307146,0.0016205776,0.06814343,0.011582322,0.2733356,0.098352484,0.44776687],"study_design_scores_gemma":[0.006351361,0.0004048485,0.29163462,0.002040605,0.00019125357,0.000006576388,0.055380315,0.1348948,0.047184523,0.028212376,0.43192822,0.0017705127],"about_ca_topic_score_codex":0.00083320984,"about_ca_topic_score_gemma":0.0002990627,"teacher_disagreement_score":0.44599637,"about_ca_system_score_codex":0.00003223364,"about_ca_system_score_gemma":0.000051504685,"threshold_uncertainty_score":0.52253616},"labels":[],"label_agreement":null},{"id":"W4412917335","doi":"10.1007/s10479-025-06682-w","title":"Improved block rearrangement algorithm","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Fonds Wetenschappelijk Onderzoek","keywords":"Theory of computation; Computer science; Block (permutation group theory); Algorithm; Mathematics; Combinatorics","score_opus":0.12811141626620398,"score_gpt":0.4464913557260017,"score_spread":0.3183799394597977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412917335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026600242,0.0015525549,0.9241495,0.029384378,0.00028665338,0.0008631555,0.00009751804,0.000105182415,0.016960777],"genre_scores_gemma":[0.78385186,0.00120983,0.2122376,0.0010054266,0.000097599586,0.00019264218,0.00004581036,0.000008636245,0.0013505894],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987642,0.00016054566,0.00020175714,0.00026173188,0.00034264734,0.00026908622],"domain_scores_gemma":[0.99822843,0.0000941763,0.00000923886,0.0007392627,0.0008682905,0.000060617942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013629886,0.00005962657,0.00009723587,0.00045166415,0.00031622712,0.00020938311,0.0008429678,0.00004097431,0.000029573563],"category_scores_gemma":[0.00014281503,0.000054715198,0.000056563145,0.0015381948,0.000108923836,0.00038004084,0.00045113475,0.00018946333,0.000015984582],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009915502,0.00046526303,0.00006403897,0.000034871086,0.00007540837,0.0000043749883,0.0006696849,0.000120534554,0.011699181,0.75708044,0.05560674,0.17416953],"study_design_scores_gemma":[0.0009156731,0.00063571025,0.004078365,0.00013235594,0.0000071424124,0.0000039185525,0.00045938598,0.60082644,0.17381568,0.03213925,0.18661226,0.00037378774],"about_ca_topic_score_codex":0.00042455056,"about_ca_topic_score_gemma":0.00012531776,"teacher_disagreement_score":0.7572516,"about_ca_system_score_codex":0.0000068755016,"about_ca_system_score_gemma":0.00018994046,"threshold_uncertainty_score":0.24321954},"labels":[],"label_agreement":null},{"id":"W4413215598","doi":"10.1007/s10479-025-06765-8","title":"A simple derivation of the waiting-time distribution (in the queue) for the bulk-service $$M/G^{(a,b)}/1$$ queueing system","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Simple (philosophy); Theory of computation; Queueing theory; Queueing system; Queue; Computer science; Service (business); Bulk queue; Distribution (mathematics); Mathematical optimization; Mathematics; Discrete mathematics; Applied mathematics; Computer network; Algorithm; Mathematical analysis; Business","score_opus":0.09808665355295156,"score_gpt":0.3930079840448452,"score_spread":0.2949213304918937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413215598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.926663,0.00024240604,0.014224377,0.05448891,0.00007574547,0.0019984897,0.000042337222,0.000035306777,0.0022294712],"genre_scores_gemma":[0.9986864,0.000009086888,0.000022914277,0.0006444259,0.00012404953,0.00021611576,0.0000715385,0.000008280819,0.00021723458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985855,0.00020120278,0.00040486472,0.0001725392,0.00039228456,0.0002435702],"domain_scores_gemma":[0.99671113,0.001076289,0.00010027401,0.0005247617,0.0015835162,0.000004004338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004691442,0.00008712805,0.00015392624,0.00018915893,0.00094085914,0.00019561914,0.0007455701,0.000044771707,0.000019415324],"category_scores_gemma":[0.0021579918,0.000048665275,0.00010362504,0.002622853,0.0001215136,0.0004341027,0.00020173809,0.00018442463,0.000010670517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000828427,0.0001079387,0.00067227025,0.000516721,0.00008629849,3.6461054e-7,0.00033336875,0.15413633,0.005540307,0.8329669,0.0038110414,0.0017455952],"study_design_scores_gemma":[0.0002637016,0.0000114141485,0.0039757434,0.00032287062,0.00005576534,3.3938818e-7,0.004653301,0.96646285,0.0044896286,0.0099763945,0.009696759,0.00009123968],"about_ca_topic_score_codex":0.002740461,"about_ca_topic_score_gemma":0.001320097,"teacher_disagreement_score":0.82299054,"about_ca_system_score_codex":0.00003227543,"about_ca_system_score_gemma":0.00007612196,"threshold_uncertainty_score":0.7236423},"labels":[],"label_agreement":null},{"id":"W4413411476","doi":"10.1007/s10479-025-06781-8","title":"Set-valued $$\\Phi $$-coherent risk measures for sustainable decision-making","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Set (abstract data type); Computer science; Algorithm","score_opus":0.326874455026115,"score_gpt":0.5719149145548164,"score_spread":0.24504045952870135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413411476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3696378,0.0022930414,0.5981827,0.0042282944,0.0002842316,0.0026331504,0.00010980682,0.000045992412,0.022585046],"genre_scores_gemma":[0.97451526,0.0015372717,0.0079914825,0.00011567474,0.000065007946,0.00020490099,0.000012776878,0.00001244972,0.015545188],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952696,0.0007603043,0.00089836784,0.000508594,0.002004939,0.00055818865],"domain_scores_gemma":[0.98411405,0.0037730888,0.00009263507,0.00087453926,0.011047866,0.00009780009],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.016654314,0.00012623165,0.00030557756,0.0016142145,0.0013899269,0.0008210254,0.0009379373,0.00011908801,0.00024094763],"category_scores_gemma":[0.042509545,0.00009626637,0.00017281604,0.0032154312,0.00018940115,0.000654903,0.0002545195,0.0002509082,0.000056919755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056401594,0.0001989426,0.0043513607,0.000017125249,0.000088328066,0.000005564099,0.0014011662,0.29104745,0.00012116865,0.12145935,0.30397797,0.27676755],"study_design_scores_gemma":[0.0009286546,0.0004427379,0.009235831,0.00016889404,0.000026842932,0.0000017201157,0.012661727,0.33887446,0.005730911,0.34434354,0.28726703,0.00031762916],"about_ca_topic_score_codex":0.00033861952,"about_ca_topic_score_gemma":0.00034121957,"teacher_disagreement_score":0.6048775,"about_ca_system_score_codex":0.00003866194,"about_ca_system_score_gemma":0.0008144921,"threshold_uncertainty_score":0.9999101},"labels":[],"label_agreement":null},{"id":"W4413940000","doi":"10.1007/s10479-025-06804-4","title":"Randomized algorithms for fully online multiprocessor scheduling with testing","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Theory of computation; Multiprocessing; Parallel computing; Multiprocessor scheduling; Randomized algorithm; Scheduling (production processes); Algorithm; Fair-share scheduling; Rate-monotonic scheduling; Mathematical optimization; Mathematics; Operating system; Schedule","score_opus":0.20645734329322205,"score_gpt":0.4393213788118706,"score_spread":0.23286403551864857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413940000","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11435734,0.0013552092,0.8782099,0.0021913971,0.00013058697,0.0014716254,0.000072307965,0.00023635036,0.0019753126],"genre_scores_gemma":[0.28405216,0.0001570973,0.71438634,0.000076532095,0.000091956084,0.0003542235,0.000073633455,0.000029860887,0.0007781807],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871075,0.000090513146,0.0003864219,0.00020020756,0.00028529658,0.00032682568],"domain_scores_gemma":[0.99610597,0.001035129,0.000016040098,0.0002142417,0.0025628991,0.00006571213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016294967,0.00012193939,0.00032190094,0.00045689684,0.0002854395,0.000112175556,0.00020496325,0.00007558438,0.000018074012],"category_scores_gemma":[0.002943673,0.00010083848,0.000062113766,0.001184045,0.00015177066,0.00016311373,0.00003000311,0.00024904025,0.000003730257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088756555,0.000074242496,0.000019448742,0.00013402749,0.00010779547,6.6317233e-7,0.00016177872,0.98661804,0.00049325736,0.0009408902,0.00009852636,0.010463743],"study_design_scores_gemma":[0.016190907,0.000054408934,0.00001889716,0.00018111132,0.000012102397,9.697978e-7,0.00034120513,0.97260827,0.010275047,0.00011848954,0.000095334566,0.00010323701],"about_ca_topic_score_codex":0.000057202436,"about_ca_topic_score_gemma":0.000040419385,"teacher_disagreement_score":0.16969483,"about_ca_system_score_codex":0.000015186476,"about_ca_system_score_gemma":0.00020635176,"threshold_uncertainty_score":0.41120738},"labels":[],"label_agreement":null},{"id":"W4414171846","doi":"10.1007/s10479-025-06746-x","title":"Comparisons of mean-variance analysis and entropy-based approaches to portfolio selection under asymmetric returns in bear and bull markets","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Portfolio; Portfolio optimization; Post-modern portfolio theory; Sharpe ratio; Autoregressive model; Capital asset pricing model; Rate of return on a portfolio; Replicating portfolio; Financial market","score_opus":0.24148770661282243,"score_gpt":0.3554903035305996,"score_spread":0.1140025969177772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414171846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96541995,0.0024610455,0.0077995975,0.005996749,0.000028383032,0.00046991452,0.0000994028,0.0000063732296,0.017718585],"genre_scores_gemma":[0.99635565,0.00065402425,0.0021201372,0.00012329899,0.000008494123,0.0000395923,0.000015782041,0.0000051873362,0.0006778339],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988063,0.000089314504,0.00049454876,0.0003094948,0.00007823848,0.00022210964],"domain_scores_gemma":[0.999407,0.00013783015,0.00005874435,0.00018779185,0.00015294927,0.000055717966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016098045,0.00008555969,0.00037081158,0.0026292945,0.00012358896,0.00009015389,0.00011190389,0.00007254334,0.00005654013],"category_scores_gemma":[0.00031829064,0.00009366266,0.000050431507,0.0039557396,0.00013485207,0.00016220748,0.000056915032,0.00015039492,0.0000024150859],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000914957,0.0002611348,0.19724126,0.000086132924,0.0001912008,5.326557e-7,0.00018423462,0.009273726,0.0001153192,0.7901207,0.0019758246,0.00045842328],"study_design_scores_gemma":[0.0003054221,0.00016844965,0.93047225,0.00003459565,0.000014698586,1.7083778e-7,0.00025967948,0.059282687,0.0013367427,0.0066497424,0.0013646213,0.00011096593],"about_ca_topic_score_codex":0.002223748,"about_ca_topic_score_gemma":0.0013374455,"teacher_disagreement_score":0.783471,"about_ca_system_score_codex":0.000027100812,"about_ca_system_score_gemma":0.00009691109,"threshold_uncertainty_score":0.38194525},"labels":[],"label_agreement":null},{"id":"W4414213966","doi":"10.1007/s10479-025-06821-3","title":"On the sensitivity of restless bandits solutions to uncertainty in the models of the arms","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Markov decision process; Heuristic; Theory of computation; Equivalence (formal languages); Sensitivity (control systems); Scheduling (production processes); Markov process; Job shop scheduling; Dynamic programming","score_opus":0.601241179788179,"score_gpt":0.5791320940734874,"score_spread":0.022109085714691612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414213966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82773393,0.0001519997,0.025414199,0.13951433,0.00009955824,0.0018760273,0.00024229004,0.000004755155,0.0049628885],"genre_scores_gemma":[0.9981487,0.00005504646,0.00009746288,0.00030793724,0.000017464248,0.00009240259,0.0000017478425,0.000004621874,0.0012746473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99115825,0.00423601,0.00065271533,0.0003289193,0.0031960164,0.00042808361],"domain_scores_gemma":[0.98023325,0.014501608,0.000059672988,0.0016280139,0.003528174,0.00004925059],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.027204912,0.000092411625,0.00024846054,0.0007105215,0.0006245401,0.00010831387,0.0017382979,0.00006203326,0.00006483022],"category_scores_gemma":[0.024211496,0.000040451992,0.00012295194,0.005498659,0.000907054,0.00021078721,0.0006061152,0.00058464304,0.000018059549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074758645,0.00023885854,0.000111022666,0.000006270561,0.000015129156,0.0000014466505,0.0021288502,0.87488437,0.0022592414,0.102458596,0.014331733,0.0034897327],"study_design_scores_gemma":[0.0003950965,0.00030984572,0.030660754,0.00028356048,0.000004646257,0.0000022217932,0.012402679,0.64804924,0.036224164,0.27017707,0.0013535823,0.00013713016],"about_ca_topic_score_codex":0.0014380221,"about_ca_topic_score_gemma":0.0052122017,"teacher_disagreement_score":0.22683509,"about_ca_system_score_codex":0.00003528325,"about_ca_system_score_gemma":0.0006501639,"threshold_uncertainty_score":0.984008},"labels":[],"label_agreement":null},{"id":"W4414358657","doi":"10.1007/s10479-025-06845-9","title":"Bayesian network modeling for ROI simulation and scenario analysis: a case study on commercial aquaponics","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Innovations in Aquaponics and Hydroponics Systems","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge; Lethbridge College","funders":"","keywords":"Flexibility (engineering); Variety (cybernetics); Bayesian network; Resource (disambiguation); Sustainability; Aquaponics; Bayesian probability; Range (aeronautics); Profitability index","score_opus":0.34461525568467055,"score_gpt":0.5005654714985831,"score_spread":0.15595021581391255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414358657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9908091,0.00013981377,0.0054812618,0.0021472948,0.000047127887,0.00096414366,0.000034301393,0.000011594575,0.00036538547],"genre_scores_gemma":[0.9992757,0.000017784521,0.00014159938,0.00011902216,0.000105860745,0.000094688716,0.000053503307,0.0000011018375,0.00019075253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985061,0.00027331506,0.0004075617,0.00027405727,0.00026731082,0.0002716149],"domain_scores_gemma":[0.9982486,0.00055302103,0.00002909971,0.00013047605,0.0009978536,0.000040988485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002570129,0.00008982373,0.00021804642,0.00017072678,0.0012613003,0.00020075183,0.00015500098,0.00007916565,0.000014530543],"category_scores_gemma":[0.00020702844,0.000044876702,0.000078802725,0.00222252,0.000045098386,0.000092816124,0.000074815136,0.00018002436,0.0000011508783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005207979,0.00031216943,0.0017168254,0.000007488022,0.00018986627,0.000005728491,0.0004336497,0.9750105,0.00016556578,0.015453105,0.00021250479,0.006440514],"study_design_scores_gemma":[0.00014241255,0.0004597755,0.00071103557,0.000021678363,0.00003547739,0.0000014727567,0.0024722796,0.99489033,0.000023686374,0.0006764959,0.0004896294,0.000075725286],"about_ca_topic_score_codex":0.0022971877,"about_ca_topic_score_gemma":0.017273443,"teacher_disagreement_score":0.019879827,"about_ca_system_score_codex":0.00001814256,"about_ca_system_score_gemma":0.000047978658,"threshold_uncertainty_score":0.97010297},"labels":[],"label_agreement":null},{"id":"W4416075108","doi":"10.1007/s10479-025-06926-9","title":"Strategic pricing and investment in environmental quality by an incumbent facing a greenwasher entrant","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; HEC Montréal","funders":"","keywords":"Greenwashing; Quality (philosophy); Investment (military); Environmental quality; Theory of computation; Competitive advantage; Market size","score_opus":0.1298599074727212,"score_gpt":0.40073058767788733,"score_spread":0.27087068020516614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416075108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99412495,0.00028233865,0.000058066114,0.0026927723,0.00001983939,0.0006322615,0.000010255061,0.000012207214,0.0021672847],"genre_scores_gemma":[0.9985741,0.00008843633,0.0000690471,0.0008318759,0.000029662642,0.00007531744,0.00006830649,0.00001017202,0.0002531294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982756,0.0001316046,0.00042362636,0.00035602957,0.00044723842,0.0003659009],"domain_scores_gemma":[0.9995126,0.000060093942,0.000033842945,0.00029615822,0.00007408916,0.000023192388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018551016,0.00013118285,0.0001881944,0.00039779104,0.00027064577,0.00024276772,0.00020892889,0.000065179185,0.0001447667],"category_scores_gemma":[0.00009990237,0.00012869082,0.000027126516,0.00053731113,0.0003023545,0.0010875013,0.00032273371,0.00022743938,0.000011461907],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016889272,0.0033743668,0.73154867,0.0011234961,0.00007855426,0.000017827708,0.0012036834,0.011369044,0.11472459,0.12662181,0.0008206854,0.008948358],"study_design_scores_gemma":[0.0015442303,0.00010448766,0.92325306,0.00021572872,0.000017365604,9.325111e-7,0.016143246,0.032097396,0.007935282,0.0134904515,0.0046665613,0.0005312584],"about_ca_topic_score_codex":0.008053848,"about_ca_topic_score_gemma":0.0011961057,"teacher_disagreement_score":0.19170438,"about_ca_system_score_codex":0.000105842235,"about_ca_system_score_gemma":0.00004293512,"threshold_uncertainty_score":0.9985516},"labels":[],"label_agreement":null},{"id":"W4416211947","doi":"10.1007/s10479-025-06884-2","title":"Computer-Aided process planning group technology and delayed product differentiation for hybrid manufacturing using a hybridized machine learning and optimization approach","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Regional Municipality of Niagara","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cellular manufacturing; Group technology; Theory of computation; Process (computing); Product (mathematics); Production planning; New product development; Production (economics)","score_opus":0.07092728411741997,"score_gpt":0.356019356740556,"score_spread":0.2850920726231361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416211947","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68047106,0.00040508236,0.31709835,0.0009960305,0.00004235031,0.00081382965,0.0000023842274,0.00005802991,0.0001129093],"genre_scores_gemma":[0.97469276,0.00006866096,0.02454384,0.000054019554,0.0001274323,0.000102923026,0.00030539557,0.00001751398,0.00008745064],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880517,0.000038386104,0.0003054959,0.00039195202,0.00020209093,0.00025689663],"domain_scores_gemma":[0.9990596,0.00004623443,0.000077846205,0.00011192857,0.0006936006,0.0000107675005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093585876,0.00013129732,0.0002032373,0.0014297963,0.0008060506,0.00035001358,0.000119696175,0.00004598802,0.000005084601],"category_scores_gemma":[0.00036305332,0.00012747549,0.000019616746,0.0007731061,0.00008810707,0.0008373073,0.00018029315,0.0001808679,2.938098e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052619894,0.0003435172,0.01658683,0.0021282572,0.00025593585,0.0000021588162,0.00038776745,0.9246676,0.009165435,0.0124580655,0.0002790088,0.03319923],"study_design_scores_gemma":[0.0006314938,0.000022439543,0.00061054865,0.000100758574,0.000022403377,0.0000024832857,0.00017071316,0.9878121,0.009505175,0.0008054446,0.00018777548,0.00012864677],"about_ca_topic_score_codex":0.000051010717,"about_ca_topic_score_gemma":0.000005369394,"teacher_disagreement_score":0.29422173,"about_ca_system_score_codex":0.000014020969,"about_ca_system_score_gemma":0.000042720196,"threshold_uncertainty_score":0.6199571},"labels":[],"label_agreement":null},{"id":"W70512572","doi":"10.1023/a:1014903232563","title":"Operational Decisions in AGV-Served Flowshop Loops: Scheduling","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Texas at Dallas","keywords":"Computer science; Theory of computation; Maximization; Sizing; Scheduling (production processes); Mathematical optimization; Decomposition; Job shop scheduling; Minification; Set (abstract data type); Genetic algorithm; Material flow; Schedule; Operations research; Industrial engineering; Algorithm; Mathematics; Engineering","score_opus":0.24446898892206767,"score_gpt":0.43355618102556936,"score_spread":0.1890871921035017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W70512572","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71369684,0.0006381678,0.2783387,0.0010991957,0.00011814721,0.00034700212,0.00002282089,0.00009418524,0.005644916],"genre_scores_gemma":[0.96927685,0.0024960914,0.027590876,0.000037327205,0.0000670318,0.000051499865,0.00007452969,0.00002056671,0.00038521268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987727,0.0000700671,0.00032746102,0.00017581883,0.00034579352,0.00030816343],"domain_scores_gemma":[0.9989183,0.00022636248,0.000006611308,0.0002659702,0.0005062197,0.00007654909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006864191,0.00009269518,0.00013308291,0.00044205683,0.00018403683,0.00007481888,0.00018945274,0.00007637006,0.00016117294],"category_scores_gemma":[0.0009442876,0.00009423243,0.000032207416,0.0006464953,0.00006652638,0.0003195084,0.000047515736,0.00030571248,0.00004870402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009580133,0.00005505707,0.00017579406,0.000005994155,0.00000875899,0.000006177736,0.00015526079,0.9920306,0.0013078211,0.0033686275,0.0003108466,0.0025654836],"study_design_scores_gemma":[0.00024448134,0.000040269602,0.002490655,0.000060405397,0.0000012560566,0.0000036863205,0.00014296992,0.98446053,0.009407641,0.0011212936,0.0018982122,0.0001286232],"about_ca_topic_score_codex":0.000106794556,"about_ca_topic_score_gemma":0.00046972762,"teacher_disagreement_score":0.25558,"about_ca_system_score_codex":0.000031738997,"about_ca_system_score_gemma":0.000069132766,"threshold_uncertainty_score":0.3842687},"labels":[],"label_agreement":null},{"id":"W75241701","doi":"10.1023/a:1013138919445","title":"A Comprehensive Input Format for Stochastic Linear Programs","year":2001,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Theory of computation; Range (aeronautics); Computer science; Mathematical economics; Mathematical optimization; Mathematics; Applied mathematics; Algorithm; Engineering","score_opus":0.32938202019815765,"score_gpt":0.45775449056652306,"score_spread":0.1283724703683654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W75241701","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061664037,0.0004497245,0.93158203,0.0014962781,0.00007392945,0.0018815316,0.00001526528,0.00021114346,0.0026260652],"genre_scores_gemma":[0.9616896,0.00023079575,0.03684344,0.000054812663,0.00007259574,0.0004085113,0.000065455235,0.000032249434,0.00060256745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991354,0.00002529488,0.00022979334,0.00008820749,0.00022222017,0.00029909017],"domain_scores_gemma":[0.9987675,0.00012269041,0.000006206401,0.00016011487,0.00085672026,0.00008677667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029343818,0.00007159,0.00012746129,0.0001583515,0.0001437937,0.00006491515,0.00012172388,0.000048239337,0.000044383658],"category_scores_gemma":[0.00016957526,0.000065328284,0.000050451294,0.0003857484,0.000063828746,0.00017188147,0.000030374706,0.00012565934,0.000035697238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028842227,0.00023880872,0.0000073452725,0.00036556585,0.00006796491,0.0000015233745,0.0010606304,0.93314976,0.00094238395,0.0119846305,0.0038371508,0.048315376],"study_design_scores_gemma":[0.00020637107,0.00015150655,0.00000442306,0.000041888154,0.000002567206,0.0000035823566,0.000282074,0.9796157,0.0009521035,0.00048507674,0.018176757,0.00007795243],"about_ca_topic_score_codex":0.00001085486,"about_ca_topic_score_gemma":0.000018316237,"teacher_disagreement_score":0.90002555,"about_ca_system_score_codex":0.000011193888,"about_ca_system_score_gemma":0.000027228734,"threshold_uncertainty_score":0.26640102},"labels":[],"label_agreement":null}]}