{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":83,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":83,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"88f1e3330a18","filters":{"venue":"INFORMS Journal on Applied Analytics"}},"results":[{"id":"W1990846384","doi":"10.1287/inte.32.2.63.57","title":"Mount Sinai Hospital Uses Integer Programming to Allocate Operating Room Time","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":212,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Dalhousie University","funders":"","keywords":"Mount; Integer programming; Schedule; Operations research; Heuristic; Integer (computer science); Operations management; Branch and price; Computer science; Linear programming; Mathematical optimization; Engineering; Operating system; Mathematics; Artificial intelligence; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.05208496301005444,"gpt":0.3588725518668935,"spread":0.306787588856839,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009760381,0.000257179,0.0003600014,0.0003096057,0.00167815,0.0002694674,0.0002472629,0.0002300527,0.0008861634],"category_scores_gemma":[0.0003634504,0.0001917273,0.00008834409,0.0005412363,0.00002527249,0.000319587,0.00007617589,0.001325908,0.00267468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006304644,"about_ca_system_score_gemma":0.0002321629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002603851,"about_ca_topic_score_gemma":0.00001527866,"domain_scores_codex":[0.9973534,0.00006315891,0.001173643,0.0002246444,0.0004825841,0.0007025813],"domain_scores_gemma":[0.9981737,0.0001464483,0.0003505247,0.0002809137,0.0005524593,0.0004959651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001680515,0.00112791,0.006793742,0.0003232321,0.0004354238,0.0001124595,0.0471391,0.6481419,0.0007324077,0.04573414,0.04454454,0.2047471],"study_design_scores_gemma":[0.002765977,0.001745471,0.001089985,0.001196846,0.0001144487,0.00004861708,0.01131935,0.669185,0.0001505593,0.0003044739,0.3105904,0.001488865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7672148,0.000119149,0.1321133,0.0298349,0.002118891,0.004474495,0.00003649296,0.0005443545,0.06354354],"genre_scores_gemma":[0.9551549,0.00009127403,0.03309945,0.006915591,0.0007994898,0.00007759222,0.00002603559,0.00005906631,0.003776585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2660459,"threshold_uncertainty_score":0.9996215,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056364446","doi":"10.1287/inte.30.3.95.11655","title":"Just-in-Time Manufacturing and Pollution Prevention Generate Mutual Benefits in the Furniture Industry","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":97,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Business; Control (management); Pollution prevention; Pollution; Production (economics); Investment (military); Work (physics); Environmental pollution; Manufacturing; Environmental economics; Industrial organization; Operations management; Marketing; Engineering; Environmental protection; Environmental science; Waste management; Economics; Management","retraction":null,"screen_n_in":null,"score":{"opus":0.01373921316750517,"gpt":0.2203255836066333,"spread":0.2065863704391281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007485077,0.0002011268,0.0001853397,0.0003237773,0.0001890138,0.0004822645,0.0002642771,0.0002113623,0.0003709983],"category_scores_gemma":[0.00001713135,0.0001417671,0.00004960877,0.0003679439,0.00006159659,0.0008367724,0.00006378858,0.0008930221,0.0001296472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871045,"about_ca_system_score_gemma":0.00001621822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002202324,"about_ca_topic_score_gemma":0.0000293183,"domain_scores_codex":[0.99863,0.000009213669,0.00045227,0.0001606913,0.00042231,0.0003255549],"domain_scores_gemma":[0.9995819,0.00001684802,0.0002001768,0.0001637595,0.00001709366,0.00002020755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007593971,0.0009155124,0.06676435,0.0002998691,0.00008572984,0.0001906894,0.0009197897,0.4579331,0.0001926185,0.009269807,0.001184357,0.4614848],"study_design_scores_gemma":[0.003245266,0.00005429349,0.9449134,0.0002253299,0.0001133641,0.0001092761,0.002139891,0.008423072,0.0002507413,0.009363357,0.03043498,0.0007270246],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926836,0.00002344839,0.000009703076,0.00108216,0.00004172625,0.0002487183,0.000001219039,0.00001527403,0.005894076],"genre_scores_gemma":[0.9962941,0.00006463724,0.00003285334,0.002728414,0.000502056,0.000007174143,0.00001317296,0.00001500563,0.0003425716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.878149,"threshold_uncertainty_score":0.5781094,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2019742604","doi":"10.1287/inte.30.1.96.11617","title":"An Asset and Liability Management System for Towers Perrin-Tillinghast","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian General-Tower (Canada)","funders":"","keywords":"Liability; Asset (computer security); Pension; Actuarial science; Business; Plan (archaeology); Investment (military); Asset management; Generator (circuit theory); Finance; Risk management; Risk analysis (engineering); Computer science; Power (physics); Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.01581097410358162,"gpt":0.296733585176161,"spread":0.2809226110725794,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002566688,0.0002417356,0.0003326304,0.0002623751,0.00106486,0.0006084251,0.0004705531,0.000122937,0.0001401752],"category_scores_gemma":[0.00001415564,0.0002037792,0.0001817208,0.0003785656,0.0002604961,0.0003555793,0.00002749211,0.00029073,0.00003729282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003194528,"about_ca_system_score_gemma":0.00005683739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005875955,"about_ca_topic_score_gemma":0.00009603624,"domain_scores_codex":[0.9975752,0.00004290921,0.0006432223,0.0003045156,0.0008428292,0.0005913662],"domain_scores_gemma":[0.9987972,0.00006234474,0.000263537,0.0003673635,0.0001305629,0.0003790382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005100308,0.0004704096,0.0100681,0.0004001278,0.0006367349,0.00005009267,0.005579174,0.01170311,0.000006010929,0.4416456,0.002259713,0.5266709],"study_design_scores_gemma":[0.002504043,0.0004616198,0.0189028,0.0001450913,0.0003993948,0.0000136808,0.02967959,0.005810885,0.00002631951,0.009184344,0.9319349,0.0009373584],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.510847,0.00005732666,0.005554805,0.0004945513,0.0006679647,0.001829934,0.00005234233,0.0002323052,0.4802638],"genre_scores_gemma":[0.9952229,0.000645284,0.0023509,0.0004487112,0.0003668426,0.00003409944,0.000009370209,0.00002120986,0.0009006547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9296752,"threshold_uncertainty_score":0.8309873,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2100639794","doi":"10.1287/inte.1050.0127","title":"A Florida County Locates Disaster Recovery Centers","year":2005,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Residence; Agency (philosophy); Emergency management; Mile; Transport engineering; Operations management; Engineering; Geography; Operations research; Business; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.01880897272590336,"gpt":0.2209670978383494,"spread":0.2021581251124461,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004792366,0.0002542374,0.0002315891,0.0004239595,0.000260753,0.0006207518,0.0003558032,0.00006627032,0.0009216066],"category_scores_gemma":[0.00004061572,0.0001991886,0.0001623862,0.0004406874,0.00005030989,0.001232549,0.0001037214,0.000317949,0.003291773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000176399,"about_ca_system_score_gemma":0.00002669442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003532246,"about_ca_topic_score_gemma":0.0001037573,"domain_scores_codex":[0.9981791,0.000002340317,0.0006541819,0.0001932008,0.0005639952,0.0004071976],"domain_scores_gemma":[0.9992836,0.00001359149,0.0002145834,0.0002826947,0.0001572145,0.00004830147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008164356,0.0005950151,0.004166976,0.0003681664,0.000587785,0.0000227533,0.0003193378,0.3799435,0.0000996236,0.1354802,0.2447146,0.2328856],"study_design_scores_gemma":[0.0009822448,0.00002363588,0.001572996,0.00004698109,0.00008777929,0.00000468123,0.0007335852,0.04251326,0.00003402764,0.001920145,0.9516521,0.0004285786],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3663842,0.00007582851,0.01690787,0.0119008,0.003398245,0.0007442852,0.0000168918,0.0003628819,0.600209],"genre_scores_gemma":[0.978202,0.000113269,0.000211177,0.01739234,0.002079235,0.000008364821,0.0000372161,0.00002569823,0.001930712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7069375,"threshold_uncertainty_score":0.9999917,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2002507421","doi":"10.1287/inte.1110.0611","title":"A Strategic Empty Container Logistics Optimization in a Major Shipping Company","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Booth University College","funders":"","keywords":"Operations research; Container (type theory); Stock (firearms); Safety stock; Business; Profit (economics); Service (business); Computer science; Operations management; Transport engineering; Marketing; Supply chain; Engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.04407673720646854,"gpt":0.2834755213931192,"spread":0.2393987841866506,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009814635,0.000241462,0.0003294938,0.0004047298,0.00009578598,0.0001674773,0.0001885807,0.0001625506,0.00009989936],"category_scores_gemma":[0.00006568317,0.0002126351,0.00007041595,0.0005576549,0.00003655319,0.0002676164,0.00002504667,0.0007210419,0.00003919832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003456066,"about_ca_system_score_gemma":0.00004745967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001364221,"about_ca_topic_score_gemma":0.00000247944,"domain_scores_codex":[0.9982901,0.00002536196,0.0007353569,0.00009262938,0.0003179696,0.0005385445],"domain_scores_gemma":[0.9991875,0.000119151,0.0001853475,0.0001842986,0.00008169624,0.0002419566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002189281,0.00003797157,0.002029617,0.00002605202,0.00004266113,0.000005489,0.0002619836,0.986726,0.00005303101,0.009557522,0.00005741397,0.001180319],"study_design_scores_gemma":[0.0009624278,0.0000277072,0.000665657,0.00005076745,0.00003376671,0.00004558559,0.0005013538,0.9964582,0.0001008938,0.000543193,0.0003148601,0.0002956363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02738197,0.00009523916,0.941379,0.00004482422,0.0003615016,0.0001861962,0.000005028254,0.0001774625,0.03036885],"genre_scores_gemma":[0.9233328,0.00009894792,0.07598775,0.0002255535,0.0002548699,0.000004802322,0.00001323161,0.00004413172,0.00003795616],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8959508,"threshold_uncertainty_score":0.8671007,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2151059370","doi":"10.1287/inte.30.6.17.11631","title":"A Decision Support System for Planning Remanufacturing at Nortel Networks","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Government of Ontario","keywords":"Remanufacturing; Plan (archaeology); Decision support system; Product (mathematics); Reverse logistics; Process (computing); Process management; Operations research; Computer science; Engineering; Business; Manufacturing engineering; Supply chain; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.0134665566187081,"gpt":0.2301464132882598,"spread":0.2166798566695517,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00108014,0.0003766154,0.0004333413,0.0006545974,0.0008090435,0.0009203339,0.0005138694,0.0001442766,0.0006110145],"category_scores_gemma":[0.00004121512,0.0003032998,0.0002496094,0.0004562032,0.00003491808,0.0007341731,0.0001719228,0.0003918529,0.0004642807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006254622,"about_ca_system_score_gemma":0.00003233476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008348939,"about_ca_topic_score_gemma":0.000006203951,"domain_scores_codex":[0.9972956,0.000002760943,0.0009008801,0.0003084236,0.0006832292,0.0008091272],"domain_scores_gemma":[0.9986921,0.0001303591,0.0005593629,0.0003825049,0.0001646435,0.00007105164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001076798,0.00005193509,0.0008637179,0.0003400433,0.0001748002,0.000216531,0.00007624563,0.8494655,0.000003124691,0.008774397,0.02761211,0.1113448],"study_design_scores_gemma":[0.003121305,0.0000697001,0.001138136,0.0003008901,0.0002542069,0.00007505964,0.001857788,0.2601076,0.00004089206,0.002462822,0.7298362,0.0007353935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.38209,0.00008277844,0.1853519,0.0006531764,0.002212166,0.00266345,0.000008032229,0.0007436361,0.4261949],"genre_scores_gemma":[0.9902909,0.00002092954,0.001072013,0.002870113,0.002566322,0.00003664645,0.0000512517,0.00007688221,0.003014956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7022241,"threshold_uncertainty_score":0.9999419,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2150863986","doi":"10.1287/inte.31.3.3.9636","title":"Value Analysis and Optimization of Reusable Containers at Canada Post","year":2001,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":55,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Supply chain; Container (type theory); Stock (firearms); Business; Operations research; Productivity; Stock control; Operations management; Inventory control; Control (management); Environmental economics; Computer science; Industrial organization; Marketing; Economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.00953963887279685,"gpt":0.1971473545844692,"spread":0.1876077157116723,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003535186,0.0001708,0.0003103308,0.0006425011,0.0001998903,0.0001709918,0.0001896551,0.00004698516,0.0005069376],"category_scores_gemma":[0.00004834016,0.000137384,0.00009919526,0.001000974,0.00004371131,0.0003573093,0.0001109214,0.0001361719,0.00001096514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002221343,"about_ca_system_score_gemma":0.00006070563,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02099507,"about_ca_topic_score_gemma":0.02938344,"domain_scores_codex":[0.9986241,0.000003089711,0.0005042201,0.0001374703,0.0004794558,0.0002516214],"domain_scores_gemma":[0.9990251,0.00002852858,0.0005133346,0.0001920978,0.000197905,0.0000430498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002103078,0.00005218139,0.02717509,0.00006373326,0.0008106033,0.0000364785,0.00003437926,0.9297916,0.00005059253,0.03275399,0.007250215,0.001770865],"study_design_scores_gemma":[0.002705558,0.00007847954,0.01203607,0.00006147839,0.001996197,0.00002159236,0.002270512,0.6932557,0.0001332015,0.001006812,0.285669,0.0007653859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6100489,0.00008096137,0.02415849,0.003485283,0.0006140327,0.0005682659,0.00001411691,0.00007702823,0.3609529],"genre_scores_gemma":[0.9921032,0.0001092239,0.0003980854,0.006059784,0.0002441218,0.000002301628,0.00005638203,0.00001601138,0.00101095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3820542,"threshold_uncertainty_score":0.9883278,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2124194632","doi":"10.1287/inte.1100.0550","title":"A Nonhomogeneous Agent-Based Simulation Approach to Modeling the Spread of Disease in a Pandemic Outbreak","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":55,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Outbreak; Pandemic; Disease; Transmission (telecommunications); Promotion (chess); Population; Agency (philosophy); Operations research; Computer science; Geography; Environmental health; Risk analysis (engineering); Business; Coronavirus disease 2019 (COVID-19); Medicine; Infectious disease (medical specialty); Virology; Engineering; Telecommunications; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.2822713010076148,"gpt":0.3823590692111269,"spread":0.1000877682035121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001411818,0.0002354214,0.0004889134,0.0002285097,0.0001249152,0.00002505287,0.0003807053,0.00009328753,0.00001628252],"category_scores_gemma":[0.001543995,0.000131952,0.000204003,0.0003778541,0.00006131797,0.00005041029,0.0001036392,0.0004144328,0.00001445239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002150527,"about_ca_system_score_gemma":0.00009735503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003514251,"about_ca_topic_score_gemma":0.00001912715,"domain_scores_codex":[0.9979507,0.00004263686,0.00102758,0.0001895366,0.0004411489,0.0003484097],"domain_scores_gemma":[0.997905,0.0009644838,0.000430241,0.0003636887,0.0001199883,0.0002166583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005394289,0.000275642,0.00604509,0.00006245065,0.00006395637,0.000005367079,0.001011884,0.9826738,0.00001024861,0.00715715,0.00003286024,0.002122177],"study_design_scores_gemma":[0.0006545106,0.0001017172,0.001717804,0.00007423638,0.0001065819,0.000001800359,0.000284808,0.9361162,0.0000196569,0.06059343,0.0001252244,0.0002040715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4657432,0.00003037945,0.5286559,0.0001483094,0.00004519545,0.0006352198,0.00001160935,0.00004683835,0.004683319],"genre_scores_gemma":[0.991683,0.00002065034,0.006912667,0.001261103,0.00005784016,0.00002441086,0.000002066742,0.00001875467,0.00001950038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5259398,"threshold_uncertainty_score":0.5380847,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2139457845","doi":"10.1287/inte.1040.0097","title":"Improving Volunteer Scheduling for the Edmonton Folk Festival","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"","keywords":"Crew; Entertainment; Advertising; Scheduling (production processes); Operations management; Business; Operations research; Marketing; Psychology; Engineering; Aeronautics; Art; Visual arts","retraction":null,"screen_n_in":null,"score":{"opus":0.08812373420240385,"gpt":0.358632925710732,"spread":0.2705091915083281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005136106,0.0002446452,0.0003529986,0.0004313235,0.001377017,0.001261087,0.001079975,0.0001385413,0.00004736632],"category_scores_gemma":[0.004260197,0.0001298207,0.0004170998,0.0009087439,0.000138092,0.0003511576,0.00009073596,0.0007903745,0.0002929746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002104471,"about_ca_system_score_gemma":0.0004741394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001852247,"about_ca_topic_score_gemma":0.00001777831,"domain_scores_codex":[0.9964178,0.00001408708,0.001084372,0.0002957917,0.001575407,0.0006125742],"domain_scores_gemma":[0.996137,0.001665691,0.000714791,0.0005881665,0.0006200866,0.0002742236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002075369,0.000110645,0.0002109901,0.000005342536,0.0001848269,0.000007651002,0.0005999362,0.7974021,0.0004741848,0.09525928,0.001428901,0.1041086],"study_design_scores_gemma":[0.007405717,0.0006713706,0.00192504,0.0001544973,0.0005653602,0.0003520056,0.007642194,0.4341283,0.003492266,0.3984869,0.1439756,0.001200804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04916585,0.0001770912,0.9389207,0.004243594,0.001233285,0.0003655334,0.00001305606,0.00007516156,0.005805676],"genre_scores_gemma":[0.9632921,0.00002719454,0.03317938,0.001101406,0.0009831865,0.00001537637,0.000002256611,0.00002627199,0.001372884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9141262,"threshold_uncertainty_score":0.9999231,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113108023","doi":"10.1287/inte.32.4.28.54","title":"Implementing a Distribution-Network Decision-Support System at Pfizer/Warner-Lambert","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":48,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Decision support system; Plan (archaeology); Operations research; Supply chain; Computer science; Operations management; Distribution (mathematics); Process management; Business; Engineering; Marketing; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.04395180645594679,"gpt":0.2669750386432939,"spread":0.2230232321873471,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001105953,0.0003968153,0.0004601511,0.0002573237,0.001183338,0.00107987,0.0006792088,0.0001571313,0.002749304],"category_scores_gemma":[0.0001105609,0.000297728,0.0002354499,0.001116236,0.00007325602,0.001057124,0.0005315406,0.0005061656,0.004875455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003188269,"about_ca_system_score_gemma":0.00002563321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001555711,"about_ca_topic_score_gemma":0.00003009121,"domain_scores_codex":[0.996466,0.000003858052,0.001189967,0.0003209187,0.000983618,0.001035668],"domain_scores_gemma":[0.998029,0.0001072954,0.0009671338,0.0004842669,0.0003296866,0.00008265002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002462719,0.0001847368,0.008533401,0.0002776369,0.0002755963,0.0001845729,0.00005327495,0.007515769,0.00002168091,0.1906618,0.6298851,0.1621601],"study_design_scores_gemma":[0.0006724865,0.00001897718,0.0007005359,0.0001960634,0.0001391763,0.0001566739,0.0001916616,0.03497892,0.00002697485,0.001392671,0.9610475,0.0004784065],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08287508,0.0003168141,0.1725996,0.001728867,0.0050926,0.001230488,0.0001692644,0.0008502029,0.735137],"genre_scores_gemma":[0.9914237,0.0001234208,0.0005563095,0.001977783,0.003891205,0.00001322494,0.000241369,0.00004830972,0.001724654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9085487,"threshold_uncertainty_score":0.9999571,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2162564886","doi":"10.1287/inte.1030.0055","title":"The Canadian Pacific Railway Transforms Operations by Using Models to Develop Its Operating Plans","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Canadian Pacific Railway (Canada)","funders":"","keywords":"Tonnage; Train; Productivity; Service (business); Operations research; Block (permutation group theory); Engineering; Suite; Fuel efficiency; Transport engineering; Rail freight transport; Heuristic; Operations management; Computer science; Business; Economics; Automotive engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.03949468063436216,"gpt":0.2849870721228541,"spread":0.2454923914884919,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007609387,0.0001361181,0.0001259471,0.000176181,0.004639842,0.0008220084,0.0002390711,0.00009772984,0.00001870016],"category_scores_gemma":[0.00005578512,0.00009536989,0.00003954537,0.0007576379,0.00006226078,0.0004367334,0.000002965063,0.0003384126,0.00003006743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005928781,"about_ca_system_score_gemma":0.002256753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.008159806,"about_ca_topic_score_gemma":0.2929249,"domain_scores_codex":[0.9984711,0.00001358067,0.000451498,0.0001132841,0.0005061768,0.0004442976],"domain_scores_gemma":[0.9989647,0.00003240634,0.00007489842,0.00008491649,0.0003522904,0.0004907965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006948948,0.00000729201,0.00002084681,0.000001025093,0.00001844537,0.000002625397,0.01421918,0.8832648,0.00006897207,0.1012121,0.0001819419,0.0009957864],"study_design_scores_gemma":[0.006247318,0.0004049877,0.0004544067,0.000668607,0.000284705,0.00007002702,0.1840966,0.3554506,0.004035921,0.01226638,0.4324133,0.003607151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.264248,0.00007318699,0.5283243,0.01705134,0.0007569519,0.001428364,0.0002691317,0.0001781494,0.1876705],"genre_scores_gemma":[0.9938487,0.00007641411,0.004550332,0.000706947,0.0001141025,0.00000654646,0.00003726588,0.00001463003,0.0006450164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7296007,"threshold_uncertainty_score":0.9984449,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2098734012","doi":"10.1287/inte.32.2.42.66","title":"Student Consulting Projects Benefit Faculty and Industry","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Engineering management; Engineering; Business; Knowledge management; Process management; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.0551187533400317,"gpt":0.2858808689916905,"spread":0.2307621156516588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003496954,0.0002124481,0.0002400763,0.0002093838,0.0003589652,0.0008441476,0.0006095466,0.0001563994,0.00002452373],"category_scores_gemma":[0.00003284614,0.0001556781,0.00006025614,0.0003868536,0.00004042401,0.0003508026,0.0002900755,0.0009729506,0.0000492926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008504472,"about_ca_system_score_gemma":0.00002926869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003172617,"about_ca_topic_score_gemma":0.000001190795,"domain_scores_codex":[0.998329,0.000005666116,0.0004785321,0.0002331188,0.000531989,0.0004216546],"domain_scores_gemma":[0.9989858,0.000071114,0.0003031524,0.0002778665,0.0001000935,0.0002619663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002341727,0.0004250135,0.03025203,0.00005319673,0.0004010026,0.0002715146,0.01380883,0.02710091,0.0001536606,0.2077441,0.005283999,0.7144823],"study_design_scores_gemma":[0.006151457,0.0007696077,0.05261527,0.0004379399,0.0001093998,0.001810796,0.00386522,0.8803703,0.00125402,0.005885925,0.04473201,0.001998059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235855,0.00009147463,0.01629348,0.0008362917,0.000401695,0.0002287382,0.000003111832,0.0001811378,0.05837855],"genre_scores_gemma":[0.9906501,0.00004136128,0.007756447,0.001053502,0.000198924,0.000002146372,8.063077e-7,0.00001095748,0.0002857475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8532694,"threshold_uncertainty_score":0.8140135,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2120218454","doi":"10.1287/inte.1100.0510","title":"Approximate Dynamic Programming Captures Fleet Operations for Schneider National","year":2010,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Work (physics); Operations research; Fleet management; Quality (philosophy); Service (business); Dynamic programming; Computer science; Operations management; Engineering; Transport engineering; Business; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01265744713664329,"gpt":0.2662540256432108,"spread":0.2535965785065675,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002771299,0.0001513687,0.0001370258,0.0002610215,0.0002397835,0.00020537,0.000140162,0.0001104675,0.00005769124],"category_scores_gemma":[0.00004438723,0.0001288388,0.00008823234,0.0002689294,0.0000352814,0.000202084,0.000004005203,0.0005455552,0.00002015576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006909333,"about_ca_system_score_gemma":0.00009574339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.783114e-7,"about_ca_topic_score_gemma":0.0001305587,"domain_scores_codex":[0.9989094,0.000001155901,0.0004763982,0.00009031346,0.0002936922,0.0002290809],"domain_scores_gemma":[0.9993832,0.00003114096,0.00005509566,0.0001193225,0.000307842,0.0001033968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002206578,0.0000930465,0.00008107168,0.00005846906,0.0001828654,0.000001386403,0.0004825782,0.6132335,0.008774255,0.359936,0.001427501,0.01570724],"study_design_scores_gemma":[0.002579418,0.0001016644,0.002783397,0.00003783468,0.0001250403,0.00008650754,0.00100563,0.7236596,0.003444638,0.01273421,0.2525558,0.0008863615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2710924,0.00002463301,0.6926418,0.00188935,0.001927291,0.001744135,0.0002686483,0.0008981974,0.02951358],"genre_scores_gemma":[0.9697264,0.000008442828,0.02937782,0.0003725668,0.0001420106,0.00008143579,0.0001381376,0.00002761146,0.0001255152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6986341,"threshold_uncertainty_score":0.5253893,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2094427046","doi":"10.1287/inte.1070.0337","title":"Spreadsheet Model Helps to Assign Medical Residents at the University of Vermont's College of Medicine","year":2008,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Rotman School of Management, University of Toronto","keywords":"Scope (computer science); Scheduling (production processes); Computer science; Operations research; Software; Engineering management; Software engineering; Operations management; Engineering; Programming language","retraction":null,"screen_n_in":null,"score":{"opus":0.1120006925111145,"gpt":0.3425552182805954,"spread":0.2305545257694809,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003647815,0.0001298857,0.0004497849,0.0004374246,0.0005067704,0.00001114225,0.001108331,0.0001205502,0.0005751451],"category_scores_gemma":[0.002286503,0.00007238093,0.0001590661,0.001146516,0.0005839115,0.000103297,0.0001816414,0.0003733127,0.0001561896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001125964,"about_ca_system_score_gemma":0.0004781523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003664857,"about_ca_topic_score_gemma":0.0000625197,"domain_scores_codex":[0.9954439,0.00004372915,0.0008596446,0.0001677513,0.003236693,0.0002482579],"domain_scores_gemma":[0.9971145,0.0009128871,0.0005803638,0.0004992961,0.0005019848,0.0003910135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00138349,0.0002695439,0.004755844,0.00001075637,0.0003230172,0.00017842,0.003944604,0.477903,0.0006398059,0.03037985,0.4753323,0.004879427],"study_design_scores_gemma":[0.01681441,0.002201421,0.06826694,0.000908191,0.0006888191,0.001530118,0.01661109,0.6851491,0.00529411,0.1156047,0.0855213,0.001409752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7997708,0.0001417437,0.1126154,0.01405232,0.0005043216,0.0003673914,0.0001721097,0.00003653323,0.07233939],"genre_scores_gemma":[0.9925839,0.0001464878,0.001346375,0.0005656031,0.00007938199,2.144789e-7,0.000001655637,0.000006562183,0.005269776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3898109,"threshold_uncertainty_score":0.6297435,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1991773164","doi":"10.1287/inte.1110.0612","title":"Quantifying the Contribution of NHL Player Types to Team Performance","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Salary; League; Cluster analysis; Value (mathematics); Computer science; Artificial intelligence; Machine learning; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.04719951990944064,"gpt":0.2540716229958695,"spread":0.2068721030864288,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001387319,0.0001618793,0.0003664054,0.0002849734,0.0002379912,0.00009128054,0.000289573,0.0000845841,0.000231827],"category_scores_gemma":[0.00009195422,0.0001118488,0.0001303044,0.0003891821,0.00004655518,0.0002772817,0.00004516194,0.0003592793,0.0006164851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057697,"about_ca_system_score_gemma":0.00002827829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007721765,"about_ca_topic_score_gemma":0.000003899263,"domain_scores_codex":[0.9984522,0.000001939929,0.0008837451,0.0001104044,0.0001296788,0.0004219661],"domain_scores_gemma":[0.9987002,0.00006817619,0.000689552,0.0002771972,0.00009023465,0.0001746241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001181699,0.0001875779,0.5001909,0.00002935203,0.000181212,7.783127e-7,0.001000308,0.02399131,0.00006107754,0.4665974,0.003423728,0.004218216],"study_design_scores_gemma":[0.001422772,0.0005120753,0.2541327,0.0001180685,0.00007882997,0.0000623416,0.0004698309,0.05776618,0.002966546,0.002429926,0.6792177,0.0008230855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9441438,0.0004045662,0.003928822,0.0004304937,0.0006459628,0.0002182551,0.00003171743,0.00001616364,0.05018024],"genre_scores_gemma":[0.9977813,0.0004842655,0.0001415233,0.0008634761,0.0003718143,0.000004230346,0.000005577882,0.0000156334,0.0003321445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6757939,"threshold_uncertainty_score":0.7923875,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163689154","doi":"10.1287/inte.33.2.12.14465","title":"Applying Operations Research Techniques to Financial Markets","year":2003,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"University of Nottingham; London School of Economics and Political Science","keywords":"Financial market; Equity (law); Debt; Finance; Business; Financial modeling; Market data; Financial engineering; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.1305274223136478,"gpt":0.4299620589831789,"spread":0.299434636669531,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009318704,0.0001612194,0.0002688928,0.001457889,0.0008836121,0.001159137,0.000633738,0.0001412809,0.0003439166],"category_scores_gemma":[0.003956414,0.0001093902,0.000108305,0.002477222,0.00006715057,0.0003638247,0.00006833256,0.0007320645,0.0007321542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001404545,"about_ca_system_score_gemma":0.0004415373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003172009,"about_ca_topic_score_gemma":0.00001542121,"domain_scores_codex":[0.9958791,0.00009863872,0.0009934658,0.0002580825,0.002311195,0.0004594863],"domain_scores_gemma":[0.9976558,0.0003782084,0.0001397652,0.0004687441,0.00098588,0.0003715961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001774601,0.0001430628,0.0007985223,0.000002168019,0.00002471684,0.00003603579,0.0006829465,0.1259019,0.0003008352,0.2865517,0.1232812,0.4620994],"study_design_scores_gemma":[0.0002431715,0.0001412187,0.0004853263,0.00001859263,0.00000725559,0.00005342051,0.0005367234,0.003449237,0.002556542,0.03221884,0.960068,0.0002216926],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03974999,0.00003124759,0.3739708,0.001352487,0.0007705894,0.00154866,0.00001378828,0.00009578395,0.5824667],"genre_scores_gemma":[0.9406807,0.0005100705,0.04887227,0.0032294,0.0005661817,0.0001367835,0.000004762635,0.00003004401,0.005969809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9009307,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2101273286","doi":"10.1287/inte.1080.0405","title":"Fraser Health Uses Mathematical Programming to Plan Its Inpatient Hospital Network","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Fraser Health; BC Cancer Agency","funders":"Fraser Health Authority","keywords":"Plan (archaeology); Process (computing); Population; Health care; Acute care; Operations management; Operations research; Capacity planning; Business; Computer science; Medicine; Engineering; Geography; Environmental health; Economics; Economic growth","retraction":null,"screen_n_in":null,"score":{"opus":0.06127268751091639,"gpt":0.3935687067256145,"spread":0.3322960192146981,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001309796,0.000227722,0.0004271078,0.000212462,0.001536525,0.0001219184,0.0001986104,0.0001981511,0.0001777609],"category_scores_gemma":[0.000221208,0.0001668235,0.0000792311,0.000544411,0.00001497639,0.0001673482,0.00003631082,0.001180362,0.0005260801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000417077,"about_ca_system_score_gemma":0.0007199388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003185701,"about_ca_topic_score_gemma":0.00001190172,"domain_scores_codex":[0.9969595,0.0000718704,0.00136035,0.0001894733,0.0005538082,0.0008649869],"domain_scores_gemma":[0.9980027,0.0001484894,0.0005012366,0.0002470371,0.0003229945,0.0007775562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004455799,0.001173752,0.00578546,0.0003699374,0.0001640114,0.00003626682,0.02166299,0.3665978,0.000006127827,0.3001064,0.05754852,0.2461031],"study_design_scores_gemma":[0.01060625,0.0190361,0.02544073,0.007243426,0.0002094291,0.00006209251,0.0294734,0.1560543,0.00006520715,0.02799297,0.7199036,0.003912526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4474707,0.0001821061,0.4183191,0.08038981,0.00282785,0.00872334,0.00005824721,0.0006154309,0.04141343],"genre_scores_gemma":[0.9112453,0.0001342658,0.05846583,0.02836779,0.00126484,0.00005194217,0.00004956064,0.00003559225,0.0003849046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6623551,"threshold_uncertainty_score":0.9997633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979906780","doi":"10.1287/inte.1110.0544","title":"Designing New Electoral Districts for the City of Edmonton","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"HEC Montréal; University of Alberta","funders":"","keywords":"Redistricting; Contiguity; Plan (archaeology); Heuristic; Operations research; Population; Computer science; Process (computing); Transport engineering; Tabu search; Engineering; Geography; Legislature; Sociology; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.06246574811638864,"gpt":0.2709474706006554,"spread":0.2084817224842668,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005405441,0.0001349722,0.0001931655,0.0001095035,0.000104657,0.00004689943,0.0002483232,0.00007471463,0.00004315876],"category_scores_gemma":[0.0001027474,0.0000903037,0.0001051334,0.0002818463,0.00002490979,0.00009343131,0.00001468646,0.0002944356,0.000003658475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007827838,"about_ca_system_score_gemma":0.00006107858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005527853,"about_ca_topic_score_gemma":0.000002365022,"domain_scores_codex":[0.9990544,0.000005983178,0.0004374271,0.00005984816,0.000204997,0.0002372897],"domain_scores_gemma":[0.9992539,0.0001942705,0.000187662,0.0001642211,0.00008262802,0.0001173439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000195597,0.00004582891,0.002442139,0.00005979873,0.0004003192,0.000002589375,0.001347785,0.8861067,0.00238175,0.009102204,0.002493222,0.09542202],"study_design_scores_gemma":[0.002830347,0.0004235537,0.01045896,0.0001058201,0.0003905511,0.00005021232,0.0004498523,0.8451977,0.1239171,0.007537431,0.00786624,0.0007723038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007467648,0.00004200394,0.9855805,0.00001738999,0.0001507992,0.0001517102,0.000002670184,0.00005851332,0.006528786],"genre_scores_gemma":[0.8298822,0.00005180974,0.1696971,0.00006837113,0.0001728224,0.00000331109,0.000001745236,0.00002716788,0.00009547767],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8224146,"threshold_uncertainty_score":0.3682478,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2143105265","doi":"10.1287/inte.2013.0683","title":"Mathematical Programming Guides Air-Ambulance Routing at Ornge","year":2013,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Operations research; Work (physics); Computer science; Fixed wing; Routing (electronic design automation); Route planning; Air traffic control; Range (aeronautics); Vehicle routing problem; Operations management; Aeronautics; Transport engineering; Engineering; Computer network; Wing","retraction":null,"screen_n_in":null,"score":{"opus":0.01871677831065077,"gpt":0.2584463641114855,"spread":0.2397295858008348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006881303,0.0002706747,0.0003479317,0.0001802217,0.0002260059,0.0002601323,0.0002852761,0.0001434677,0.0003376147],"category_scores_gemma":[0.000141907,0.0002159046,0.0001182382,0.0003499867,0.0000491503,0.0002533512,0.00006981069,0.0005638633,0.0008009752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003236551,"about_ca_system_score_gemma":0.00002506508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.326854e-7,"about_ca_topic_score_gemma":4.788494e-7,"domain_scores_codex":[0.998017,0.00001261575,0.0008278668,0.0001357646,0.0004589437,0.0005478344],"domain_scores_gemma":[0.9989616,0.0001513435,0.0002130922,0.000279391,0.0001268467,0.0002677187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001153737,0.00004344305,0.0006149996,0.0001098623,0.000159428,0.00001752494,0.0005007044,0.8765327,0.0006182332,0.008805739,0.002521469,0.1100643],"study_design_scores_gemma":[0.0005990777,0.00004829286,0.0004649364,0.0001274814,0.0000429115,0.0002270229,0.0002541114,0.9857957,0.001759695,0.002176473,0.00802651,0.0004778169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1403675,0.00004992605,0.7765049,0.0002687064,0.0003132513,0.0005589809,0.000002866513,0.0008092486,0.08112467],"genre_scores_gemma":[0.7071429,0.00003609341,0.2917576,0.0003240136,0.0002478731,0.00001867343,0.000004348065,0.00007081184,0.0003976887],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5667754,"threshold_uncertainty_score":0.999977,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4256526873","doi":"10.1287/inte.31.3s.108.9685","title":"Implementing and Evaluating SilverScreener: A Marketing Management Support System for Movie Exhibitors","year":2001,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Movie theater; Attendance; Revenue; Path (computing); Path analysis (statistics); Computer science; Marketing; Advertising; Operations research; Business; Multimedia; Engineering; Economics; Art; Visual arts","retraction":null,"screen_n_in":null,"score":{"opus":0.09065147209015902,"gpt":0.3933037154119106,"spread":0.3026522433217516,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01960734,0.0002042245,0.0003925647,0.000472722,0.001132741,0.0007575897,0.0004313727,0.00006595641,0.0001997105],"category_scores_gemma":[0.0004857708,0.000142723,0.0002142573,0.0006154975,0.00009889214,0.0002753528,0.000169121,0.0002279287,0.00008225985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001206822,"about_ca_system_score_gemma":0.00004492893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.860848e-7,"about_ca_topic_score_gemma":0.000001136035,"domain_scores_codex":[0.996454,0.00006984645,0.001458629,0.0003227765,0.001194689,0.0005000489],"domain_scores_gemma":[0.9967521,0.001280317,0.001108584,0.0003491984,0.0002854785,0.0002242883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00145199,0.00003986671,0.0007542646,0.00004763413,0.0001907592,0.00001239358,0.0002899461,0.005507017,0.00007832469,0.4980932,0.002392228,0.4911423],"study_design_scores_gemma":[0.02122956,0.0004522409,0.001369433,0.0002989858,0.0007146494,0.0008674806,0.08792594,0.1811713,0.0006130536,0.1572655,0.5467725,0.001319377],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1890001,0.00004248667,0.4935339,0.001043488,0.0005513352,0.00183412,0.00003177525,0.0001562728,0.3138065],"genre_scores_gemma":[0.9869096,0.00004843987,0.009479712,0.0003906277,0.0003784137,0.00006316372,0.000006479502,0.00001919236,0.002704381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7979095,"threshold_uncertainty_score":0.871224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3158898498","doi":"10.1287/inte.2020.1055","title":"A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Supply chain; Computer science; Service level; Service management; Service (business); Stock (firearms); Risk analysis (engineering); Supply chain management; Operations management; Operations research; Reliability engineering; Business; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.02284518305943014,"gpt":0.2354543909942878,"spread":0.2126092079348577,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000864087,0.0003046077,0.0004054702,0.000732048,0.0004217451,0.0007242992,0.0003800332,0.0001187244,0.00008591849],"category_scores_gemma":[0.0001397518,0.0002402637,0.0001832052,0.0010848,0.00002680667,0.0004476022,0.0001276464,0.0005726153,0.00009295291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001916696,"about_ca_system_score_gemma":0.0001236299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001301186,"about_ca_topic_score_gemma":0.0006895226,"domain_scores_codex":[0.997783,0.00000803717,0.0007533388,0.000287439,0.0005952354,0.0005729265],"domain_scores_gemma":[0.9987187,0.0001200889,0.0005404651,0.0002450515,0.0003271949,0.00004849383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005328731,0.0003594681,0.07355437,0.002019064,0.000241457,0.0003368803,0.0003321165,0.8247986,0.0001521969,0.07954544,0.001859939,0.01626757],"study_design_scores_gemma":[0.004050217,0.00005105173,0.003753979,0.0004809718,0.0001394582,0.00002054262,0.007054566,0.8652311,0.0002566947,0.000684772,0.1177571,0.0005195228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6480567,0.0007603163,0.1655191,0.03497986,0.004445208,0.005779279,0.0001731561,0.001546802,0.1387395],"genre_scores_gemma":[0.9932551,0.00002868705,0.0006287399,0.004503605,0.0009247832,0.00004408385,0.0001165073,0.00004374223,0.0004547719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3451983,"threshold_uncertainty_score":0.9797668,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2762403164","doi":"10.1287/inte.2017.0906","title":"Calibrated Route Finder: Improving the Safety, Environmental Consciousness, and Cost Effectiveness of Truck Routing in Sweden","year":2017,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Truck; Standardization; Fuel efficiency; Process (computing); Operations research; Routing (electronic design automation); Transport engineering; Analytics; Externality; Key (lock); Environmental economics; Telematics; Computer science; Business; Engineering; Computer security; Economics; Automotive engineering; Telecommunications; Microeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.01253939128950415,"gpt":0.2298546110265086,"spread":0.2173152197370045,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005152446,0.0001403315,0.0002032374,0.0001038827,0.0002329735,0.0001899592,0.0002340333,0.00006402702,0.00001367195],"category_scores_gemma":[0.00002445558,0.00009721937,0.00003960193,0.00006296128,0.0001193804,0.0001763545,0.00009531469,0.0002279151,0.000004533064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001328896,"about_ca_system_score_gemma":0.00001706928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001404483,"about_ca_topic_score_gemma":0.00004874375,"domain_scores_codex":[0.9991689,0.00001216774,0.0003604002,0.00008303759,0.0001864947,0.0001889774],"domain_scores_gemma":[0.9994423,0.00006786746,0.0002018061,0.0002170219,0.000009098111,0.00006191115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007961652,0.0001857349,0.3438426,0.0007948126,0.0007820853,0.0001022036,0.001453341,0.3575969,0.01169594,0.09632095,0.0002220832,0.1862072],"study_design_scores_gemma":[0.005028949,0.00009485606,0.614849,0.0002849085,0.00009424156,0.00004283728,0.001105668,0.3666562,0.007489331,0.001138623,0.002700974,0.0005143592],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691645,0.00005030249,0.01109977,0.00008375324,0.0002738384,0.0006433685,0.00002382101,0.00004745448,0.01861322],"genre_scores_gemma":[0.9996688,0.0001612712,0.00004583468,0.00004037528,0.00002245196,0.000004453078,0.000006881266,0.00001593856,0.00003395584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2710064,"threshold_uncertainty_score":0.3964491,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004985180","doi":"10.1287/inte.30.2.41.11673","title":"Air Transat Uses ALTITUDE to Manage Its Aircraft Routing, Crew Pairing, and Work Assignment","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Charter; Scheduling (production processes); Operations research; Crew scheduling; Crew; Flexibility (engineering); Navy; Work (physics); Computer science; Operations management; Engineering; Aeronautics","retraction":null,"screen_n_in":null,"score":{"opus":0.01623516938582708,"gpt":0.2473318439163179,"spread":0.2310966745304908,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006720956,0.0003208272,0.0003524103,0.0002635155,0.0001974121,0.0002143537,0.0002563098,0.0001342467,0.0003835702],"category_scores_gemma":[0.00002938356,0.0002833977,0.00009911081,0.0004912704,0.0000270237,0.0001883717,0.00002582426,0.0005617657,0.0001907632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001936594,"about_ca_system_score_gemma":0.00001907077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.370821e-7,"about_ca_topic_score_gemma":0.000001929581,"domain_scores_codex":[0.9981722,0.00001960329,0.0006512547,0.0001921659,0.000461879,0.0005028818],"domain_scores_gemma":[0.9991293,0.0000843212,0.00009052912,0.0002395276,0.00004235363,0.0004139808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003441086,0.00002247277,0.0004333207,0.00003009675,0.0001071292,0.00001736928,0.0006073304,0.9254327,0.00006077011,0.0004144449,0.0005471307,0.07229279],"study_design_scores_gemma":[0.005748414,0.0006291596,0.02804371,0.00123989,0.0005403809,0.0002966562,0.0006823823,0.6375169,0.008345867,0.0007937312,0.312602,0.003560985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3454668,0.0002047692,0.5856624,0.000805962,0.0003794413,0.0006921501,0.00001173276,0.000814939,0.06596182],"genre_scores_gemma":[0.9571364,0.000430669,0.0397948,0.001260019,0.0001987937,0.000009022171,0.000002737803,0.00007478044,0.001092767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6116696,"threshold_uncertainty_score":0.9999618,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2109092812","doi":"10.1287/inte.1050.0194","title":"The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups","year":2006,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Management and Marketing Education","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Work (physics); Group (periodic table); Working group; Process (computing); Mathematics education; Engineering management; Computer science; Management; Engineering; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.008498257883819513,"gpt":0.2199077129801811,"spread":0.2114094550963616,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001845282,0.0001837697,0.0002136378,0.0004084442,0.0006385702,0.0003657496,0.0008950637,0.00002418554,0.0001900324],"category_scores_gemma":[0.00002560614,0.000137706,0.00008787666,0.0007527009,0.0001268929,0.0006747899,0.0004210228,0.0001179053,0.00009626538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002781596,"about_ca_system_score_gemma":0.0000285059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005069101,"about_ca_topic_score_gemma":0.0004714767,"domain_scores_codex":[0.9980519,0.000006613614,0.0005120002,0.0002132142,0.0008750855,0.0003411875],"domain_scores_gemma":[0.9986534,0.00003113251,0.0006215415,0.0004294456,0.0002239985,0.00004050777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001164134,0.001510614,0.05157425,0.0006616278,0.0007353166,0.00004407206,0.0004256593,0.01208682,0.000117497,0.802222,0.06790654,0.06155154],"study_design_scores_gemma":[0.002661352,0.0001730311,0.6695876,0.000230167,0.0007796951,0.000001583193,0.03072644,0.001507587,0.00005810687,0.006866731,0.2867989,0.0006088936],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3787701,0.0000190484,0.0009405448,0.0002270421,0.0003339986,0.0009607036,8.122094e-7,0.00003978876,0.618708],"genre_scores_gemma":[0.9954879,0.0001014368,0.000502016,0.0002128861,0.0002216175,0.000003734044,0.000002810707,0.00001295059,0.00345464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7953552,"threshold_uncertainty_score":0.5615488,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1982221171","doi":"10.1287/inte.1110.0561","title":"A Decision Support System for Scheduling the Canadian Football League","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan; Federated Co-operatives (Canada)","funders":"","keywords":"League; Football; Schedule; Operations research; Scheduling (production processes); Computer science; Decision support system; Business; Engineering; Operations management; Advertising; Political science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1160641987402657,"gpt":0.3654990332152486,"spread":0.2494348344749829,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01152876,0.0002400986,0.0003982387,0.0008415975,0.00202481,0.00126754,0.001144488,0.0001988593,0.00009427508],"category_scores_gemma":[0.0026675,0.0001286351,0.0003799441,0.001045026,0.0001028836,0.0003879727,0.00006071559,0.0006980872,0.001131988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005438072,"about_ca_system_score_gemma":0.0009213132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004036835,"about_ca_topic_score_gemma":0.003741525,"domain_scores_codex":[0.995787,0.00003123491,0.001238113,0.000224532,0.001708841,0.001010303],"domain_scores_gemma":[0.9952375,0.001843957,0.00060977,0.0006679184,0.0006514975,0.0009893356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000409093,0.0001870747,0.007360991,0.00002368416,0.0004788453,0.00001922627,0.002361416,0.1627582,0.00006943187,0.6131912,0.04426106,0.1688798],"study_design_scores_gemma":[0.002613117,0.0002983762,0.003523532,0.0001472575,0.0003528213,0.0007640495,0.008663065,0.09188632,0.000501206,0.0335631,0.8567866,0.0009005606],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1471354,0.0004396824,0.6596447,0.006172607,0.01074809,0.001654493,0.0001460136,0.0002380523,0.173821],"genre_scores_gemma":[0.9817746,0.000008369359,0.01512445,0.001132454,0.001013082,0.00001553292,0.000005399279,0.00002334958,0.0009027949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8346392,"threshold_uncertainty_score":0.9997692,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2131427758","doi":"10.1287/inte.1090.0435","title":"A Simulation Model to Compare Strategies for the Reduction of Health-Care–Associated Infections","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Isolation (microbiology); Hygiene; Infection control; Health care; Discrete event simulation; Medicine; Operations management; Medical emergency; Business; Operations research; Computer science; Intensive care medicine; Economics; Engineering; Simulation; Economic growth","retraction":null,"screen_n_in":null,"score":{"opus":0.12066629367792,"gpt":0.4551952630040059,"spread":0.3345289693260859,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001108865,0.0001312052,0.0002883987,0.0002412783,0.002010768,0.00006180516,0.0001155466,0.00009859519,0.00001452386],"category_scores_gemma":[0.0002480258,0.00008953694,0.00008983925,0.0004734774,0.00001967394,0.0001860223,0.00001025349,0.0005317412,0.000009329862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004693251,"about_ca_system_score_gemma":0.001322276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002598232,"about_ca_topic_score_gemma":0.00007411385,"domain_scores_codex":[0.9981269,0.0000626398,0.001099576,0.0001097898,0.0002811922,0.0003199247],"domain_scores_gemma":[0.9976659,0.0003371439,0.0006717051,0.0001888479,0.001003273,0.0001330589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006758179,0.00005486204,0.00004561814,0.00002617292,0.0000244892,2.850348e-8,0.006403893,0.9604303,0.00001599373,0.0246401,0.0007471113,0.007543867],"study_design_scores_gemma":[0.0007364584,0.0004045874,0.0007945145,0.0001303515,0.00003190507,6.847853e-7,0.0154847,0.9772773,0.000005233661,0.003327398,0.001690481,0.0001163516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03685017,0.00004048179,0.9522729,0.00659107,0.0003132798,0.001581303,0.00003603784,0.00005570006,0.002259036],"genre_scores_gemma":[0.9915964,0.00004880254,0.005511472,0.002465252,0.0001751184,0.00004033849,0.00005478759,0.00001265103,0.00009516003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9547462,"threshold_uncertainty_score":0.9992885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2014291971","doi":"10.1287/inte.1090.0448","title":"Optimization Helps Shermag Gain Competitive Edge","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Supply chain optimization; Procurement; Competitive advantage; Supply chain network; Software; Component (thermodynamics); Computer science; Market share; Total cost; Operations research; Supply chain management; Engineering; Business; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01019653572668703,"gpt":0.2230742850534684,"spread":0.2128777493267814,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001923471,0.0001972035,0.0002101566,0.0002503829,0.0001296275,0.0001949932,0.0001676203,0.0001104672,0.0001649701],"category_scores_gemma":[0.00002319749,0.0001703009,0.00008290696,0.0003577324,0.00002304429,0.0001765583,0.000007851688,0.0004598385,0.0001216332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000135854,"about_ca_system_score_gemma":0.0000303176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.200942e-7,"about_ca_topic_score_gemma":1.935727e-7,"domain_scores_codex":[0.9989089,0.000005316783,0.0004197361,0.00009295045,0.0003004916,0.0002725744],"domain_scores_gemma":[0.999423,0.00003131975,0.0001002049,0.0001453408,0.0001091292,0.0001910316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001419009,0.0000239138,0.000005483867,0.000003657951,0.00003306729,0.000007771684,0.000143478,0.9814441,0.00002238961,0.005742795,0.0005208128,0.01203832],"study_design_scores_gemma":[0.0006584092,0.00007233719,0.00006394774,0.00003346763,0.0000186624,0.00003755229,0.000238461,0.995086,0.0006588679,0.000408061,0.002470839,0.0002534016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001326656,0.00005582746,0.8379253,0.0002586433,0.0004032675,0.0001188091,0.000005675091,0.0003086486,0.1595972],"genre_scores_gemma":[0.8159776,0.0008622718,0.1787536,0.003033661,0.0008484042,0.000003955516,0.00006737091,0.00006297381,0.0003900921],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.814651,"threshold_uncertainty_score":0.6944669,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2083945967","doi":"10.1287/inte.1090.0444","title":"Rebuttal of “Polar Bear Population Forecasts: A Public-Policy Forecasting Audit”","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"Office of Science; U.S. Forest Service; U.S. Geological Survey; Woods Hole Oceanographic Institution; Arctic Institute of North America; U.S. Department of Energy; National Science Foundation","keywords":"Population; Listing (finance); Audit; Rebuttal; Endangered species; Government (linguistics); Threatened species; Geography; Operations research; Political science; Business; Accounting; Ecology; Engineering; Habitat; Sociology; Finance; Law; Biology; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.02203923232944397,"gpt":0.2334201035736783,"spread":0.2113808712442343,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005322955,0.0001983819,0.0003013581,0.0004127389,0.0003185396,0.0001369443,0.0002753624,0.00009918021,0.0002456229],"category_scores_gemma":[0.0001850753,0.0001467421,0.0001525955,0.0005471887,0.00006751362,0.0004548031,0.00001100287,0.0004723649,0.00004502861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004649541,"about_ca_system_score_gemma":0.0001876325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001499276,"about_ca_topic_score_gemma":0.00007474282,"domain_scores_codex":[0.998126,0.00001272321,0.0006806881,0.0001397018,0.0005726565,0.0004681952],"domain_scores_gemma":[0.9987726,0.0000921345,0.0005823093,0.0001767804,0.0001097562,0.0002663799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000265357,0.00009631077,0.1016934,0.00004075573,0.0001318792,0.00005041986,0.000598238,0.03760353,0.00002055643,0.03577277,0.0004447692,0.8232819],"study_design_scores_gemma":[0.002548346,0.002248142,0.3703949,0.0002193778,0.0001432298,0.001370719,0.002321406,0.5039005,0.00008331145,0.1055874,0.01004845,0.001134168],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271935,0.00002828635,0.006302109,0.001641874,0.0002465933,0.0002151999,0.00007984752,0.00004976486,0.06424286],"genre_scores_gemma":[0.9950178,0.00007125036,0.003251931,0.0009640594,0.0004745269,1.444085e-7,0.0001122131,0.000005443851,0.0001026267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8221478,"threshold_uncertainty_score":0.5983971,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2149852331","doi":"10.1287/inte.1040.0113","title":"Bombardier Flexjet Significantly Improves Its Fractional Aircraft Ownership Operations","year":2005,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Crew; Charter; Engineering; Aeronautics; Operations research; Service (business); Operations management; Business; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.02273125815674075,"gpt":0.2711719378261229,"spread":0.2484406796693822,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006220404,0.0002625968,0.0002681041,0.0003218505,0.0002829266,0.000304576,0.0002464512,0.0001697135,0.0003599542],"category_scores_gemma":[0.0001004225,0.0002183177,0.0001224603,0.0003647909,0.00003389715,0.0004873533,0.00002306616,0.0008679708,0.0004901469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002866741,"about_ca_system_score_gemma":0.0001057093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.140467e-7,"about_ca_topic_score_gemma":0.000003312026,"domain_scores_codex":[0.9982617,0.00001720958,0.0006814363,0.00014684,0.0004886859,0.000404063],"domain_scores_gemma":[0.9991062,0.0001055699,0.0001050716,0.0002185503,0.0001872597,0.0002773107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001549354,0.00002890915,0.00001845404,0.00001039217,0.0001112308,0.000002968156,0.000149255,0.9742764,0.002869989,0.004408533,0.002130888,0.01597755],"study_design_scores_gemma":[0.0006931632,0.00004937277,0.0002959599,0.00001963783,0.00005796083,0.00006238957,0.0001915579,0.9295841,0.00629431,0.0002055264,0.06213868,0.0004073475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04079449,0.0001459253,0.8618012,0.001696582,0.001037199,0.0004961716,0.00005122941,0.0008273707,0.09314983],"genre_scores_gemma":[0.918729,0.0001547726,0.07739569,0.001120501,0.001134878,0.00001270764,0.00002593259,0.00006991825,0.001356576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8779345,"threshold_uncertainty_score":0.8902739,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2146336822","doi":"10.1287/inte.1110.0583","title":"Universal Tool for Vaccine Scheduling: Applications for Children and Adults","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Oak Ridge Institute for Science and Education; Centers for Disease Control and Prevention; Georgia Institute of Technology; U.S. Department of Energy","keywords":"Schedule; Vaccination; Immunization; Scheduling (production processes); Computer science; Disease control; Medicine; Disease; Health care; Operations research; Environmental health; Operations management; Engineering; Immunology; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02108206902359892,"gpt":0.2738359357310502,"spread":0.2527538667074513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003950216,0.0001205404,0.0001814143,0.0001384202,0.0006854302,0.0001011463,0.0002214117,0.0001023191,0.00004832932],"category_scores_gemma":[0.00006388978,0.000101299,0.0001050835,0.0001645589,0.00001637009,0.0002264645,0.00001983142,0.0001583126,0.00001131734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007137381,"about_ca_system_score_gemma":0.0001488796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001538173,"about_ca_topic_score_gemma":0.00005350905,"domain_scores_codex":[0.9990919,0.000004454994,0.0003037381,0.0001378669,0.0001674801,0.0002946232],"domain_scores_gemma":[0.9992001,0.00009563932,0.0002180986,0.000120911,0.0001955249,0.0001697129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001077567,0.0002019064,0.01115979,0.0000410513,0.0002555256,0.000001732334,0.006559324,0.0001213219,0.00002066268,0.8693875,0.00407965,0.107094],"study_design_scores_gemma":[0.03318625,0.003014466,0.1508963,0.0002819996,0.0013959,0.00008235914,0.02125395,0.003153054,0.001209335,0.3065434,0.4758865,0.003096509],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5821581,0.000234221,0.3702699,0.002148636,0.0003232404,0.005282921,0.0001441225,0.0001908975,0.03924797],"genre_scores_gemma":[0.985859,0.0003779256,0.01189942,0.0005497473,0.0007643523,0.00004951997,0.00001801724,0.00001820273,0.0004638563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.562844,"threshold_uncertainty_score":0.5271844,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2106360850","doi":"10.1287/inte.1120.0650","title":"Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Automotive industry; Scheduling (production processes); Stamping; Manufacturing engineering; Production planning; Supply chain; Engineering; Overtime; Industrial engineering; Operations research; Operations management; Business; Production (economics); Marketing; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.02761085595828231,"gpt":0.2549771217926849,"spread":0.2273662658344026,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003379,0.0002319264,0.0002663757,0.0003458646,0.0001176052,0.0001169891,0.0001164106,0.00008434563,0.00008997476],"category_scores_gemma":[0.00001268536,0.0001974492,0.00004631879,0.0001133706,0.00002839481,0.0002214085,0.00003808687,0.0005691204,0.000028111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002650213,"about_ca_system_score_gemma":0.00001217929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001773048,"about_ca_topic_score_gemma":4.96695e-7,"domain_scores_codex":[0.9986708,0.00000756525,0.0005073972,0.00009764588,0.0002525464,0.0004640469],"domain_scores_gemma":[0.999469,0.00004732161,0.000116745,0.0001047233,0.00001728828,0.0002448699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002792573,0.00003533755,0.00361379,0.00001900868,0.00009095076,0.000006031373,0.0009268455,0.9862174,0.0001265436,0.0001801368,0.00003189201,0.00872416],"study_design_scores_gemma":[0.001501238,0.00005305283,0.01954297,0.00008473595,0.00003108421,0.00004764469,0.002393276,0.971754,0.001874268,0.0001241061,0.002216808,0.0003768604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8591964,0.0001255532,0.1378717,0.00003421175,0.0001858808,0.0002074086,0.00001383438,0.0001238661,0.002241087],"genre_scores_gemma":[0.9467006,0.00007662042,0.05287499,0.0001547647,0.0001172347,0.000005722079,0.00002475676,0.00002997755,0.00001535468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08750416,"threshold_uncertainty_score":0.8051744,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4367676883","doi":"10.1287/inte.2023.1164","title":"Bombardier Aftermarket Demand Forecast with Machine Learning","year":2023,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"McGill University; Group for Research in Decision Analysis; HEC Montréal; Mila - Quebec Artificial Intelligence Institute; Bombardier (Canada)","funders":"","keywords":"Spare part; Demand forecasting; Computer science; Analytics; On demand; Process (computing); Economic shortage; Operations research; Data mining; Engineering; Operations management","retraction":null,"screen_n_in":null,"score":{"opus":0.07595793931106345,"gpt":0.3423356359571896,"spread":0.2663776966461261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002959779,0.0002219705,0.0003397197,0.0006731346,0.0005615178,0.000646637,0.0006785368,0.00009281396,0.0002525481],"category_scores_gemma":[0.0003184628,0.0001265537,0.0001526201,0.001709962,0.0001122665,0.000218444,0.0001447228,0.0007327832,0.0007838725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006108126,"about_ca_system_score_gemma":0.00007209552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002336211,"about_ca_topic_score_gemma":0.000008895786,"domain_scores_codex":[0.9970991,0.00002381639,0.0007744792,0.0002683148,0.001397193,0.0004370853],"domain_scores_gemma":[0.9980662,0.0004542444,0.0005376745,0.000439095,0.0002377327,0.0002650821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001121887,0.0001788333,0.04083661,0.00002998946,0.0003848406,0.0003263778,0.001284046,0.1370855,0.0003162569,0.05942119,0.1879048,0.5711097],"study_design_scores_gemma":[0.001213261,0.0005818519,0.008751144,0.00008777774,0.00006685783,0.0004313312,0.0006374107,0.1987083,0.0004986823,0.07195029,0.716444,0.0006291862],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4824075,0.00005169157,0.1573427,0.003963057,0.0003207618,0.000909635,0.00007966144,0.001061148,0.3538639],"genre_scores_gemma":[0.990665,0.0000835316,0.003610732,0.00046256,0.0001601943,0.00002005469,0.00001334255,0.00003010798,0.004954461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5704805,"threshold_uncertainty_score":0.9999942,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2119849184","doi":"10.1287/inte.30.2.54.11677","title":"TransAlta Redesigns Its Service-Delivery Network","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"TransAlta (Canada); University of Alberta","funders":"","keywords":"Staffing; Service (business); Heuristics; Service delivery framework; Operations management; Operations research; Business; Engineering; Transport engineering; Computer science; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.02214844934402232,"gpt":0.2406537194303505,"spread":0.2185052700863282,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006004925,0.0002568846,0.0003006789,0.0001435012,0.0001940126,0.0001765479,0.0003164244,0.0001705606,0.001181602],"category_scores_gemma":[0.000009306093,0.0002287727,0.0001111077,0.0007327409,0.00001559747,0.0002095132,0.000009100146,0.0007032373,0.0005058047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001224927,"about_ca_system_score_gemma":0.00004942031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.810564e-7,"about_ca_topic_score_gemma":0.000001682328,"domain_scores_codex":[0.9983399,0.00001809412,0.0006378893,0.000122939,0.0003854844,0.0004956871],"domain_scores_gemma":[0.9992336,0.00008864212,0.00009077146,0.000236925,0.0000943484,0.0002556833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003974351,0.00001234388,0.00001501221,0.00002205936,0.00008398601,0.000009969509,0.000155242,0.9525094,0.0001248903,0.0005766593,0.002016653,0.04443406],"study_design_scores_gemma":[0.000847198,0.00005547588,0.0001113352,0.00007637664,0.00006832759,0.00007323908,0.00005796552,0.9488401,0.0007041418,0.0005814772,0.04815658,0.0004277849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1450331,0.0004234153,0.390794,0.0009649975,0.001219194,0.0007482379,0.00002823216,0.001819085,0.4589697],"genre_scores_gemma":[0.9204599,0.002082974,0.07073981,0.003463429,0.001526862,0.000009991961,0.00001964065,0.0001889704,0.00150845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7754268,"threshold_uncertainty_score":0.9997315,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2167612934","doi":"10.1287/inte.1030.0049","title":"Preferred Scenarios in the Sport of Curling","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Federated Co-operatives (Canada)","funders":"","keywords":"Championship; Curling; Shot (pellet); World championship; Point (geometry); Class (philosophy); Advertising; Team sport; Tipping point (physics); Marketing; Psychology; Computer science; Engineering; Mathematics; Artificial intelligence; Athletes; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.03536256942786613,"gpt":0.2321553533887104,"spread":0.1967927839608442,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001064079,0.0001485148,0.0003873164,0.0004096328,0.00009334414,0.00009385837,0.0003962066,0.00008482678,0.00009748928],"category_scores_gemma":[0.00003242596,0.0001070385,0.000146748,0.0004616317,0.00005290048,0.000160004,0.0000224445,0.0004879062,0.0001100676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001154852,"about_ca_system_score_gemma":0.00006074741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004155717,"about_ca_topic_score_gemma":0.00002239747,"domain_scores_codex":[0.9983366,7.460605e-7,0.001119112,0.0001351238,0.0001308651,0.000277628],"domain_scores_gemma":[0.9988306,0.0000258166,0.0007472804,0.0002902909,0.00003678888,0.00006928897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005750593,0.0003136977,0.09370504,0.00002821105,0.00006518141,0.00003103744,0.001909885,0.2351353,0.000005894773,0.6674648,0.0001785254,0.001104939],"study_design_scores_gemma":[0.01141427,0.00129241,0.3251521,0.0005310463,0.0001069477,0.00034709,0.004826606,0.05939305,0.0006952439,0.3628641,0.2312899,0.002087145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9162068,0.0001826253,0.001701265,0.0005747013,0.0002128633,0.0001966926,0.00001424775,0.00000974518,0.08090107],"genre_scores_gemma":[0.9982798,0.0004993149,0.0002117241,0.0007464471,0.0001294081,0.000002800164,0.000005381162,0.00001264493,0.0001125142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3046006,"threshold_uncertainty_score":0.4364904,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2155355405","doi":"10.1287/inte.1050.0175","title":"Developing the Reflective Practitioner—Designing an Undergraduate Class","year":2006,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Reflective Practices in Education","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"McGill University; University of Strathclyde","keywords":"Reflection (computer programming); Class (philosophy); Reflective practice; Process (computing); Action (physics); Action research; Statement (logic); Mathematics education; Psychology; Medical education; Engineering ethics; Engineering; Computer science; Pedagogy; Medicine; Political science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.0507119137437996,"gpt":0.3914413770110575,"spread":0.3407294632672579,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002538379,0.0001662329,0.0001590101,0.0002221329,0.002355418,0.0008733353,0.0004127452,0.0001212318,0.00003374844],"category_scores_gemma":[0.0004557445,0.0001153971,0.00007300358,0.0008115346,0.0002399204,0.001322568,0.00002624042,0.0008471803,0.00010068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378746,"about_ca_system_score_gemma":0.001070728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001965539,"about_ca_topic_score_gemma":0.0006377578,"domain_scores_codex":[0.9978954,0.00019646,0.0004579439,0.000176758,0.0008482872,0.0004251596],"domain_scores_gemma":[0.9978673,0.0005803267,0.0008145845,0.000207822,0.0004051115,0.0001248961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005886886,0.00008553119,0.0003534719,0.000002682626,0.00006238599,0.000004410028,0.003843002,0.006461948,0.0002194824,0.9739867,0.001647432,0.01327411],"study_design_scores_gemma":[0.0003873975,0.0001134018,0.002206357,0.00003331457,0.00008186811,0.00003876582,0.02079576,0.0005786257,0.00102697,0.5832815,0.3910841,0.0003719371],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01437085,0.00002169639,0.07383211,0.01792111,0.000720831,0.000330845,0.000001097206,0.00008548184,0.892716],"genre_scores_gemma":[0.9831021,0.0001815091,0.01218731,0.001853016,0.001470272,0.00001561739,0.000006299059,0.00002071871,0.00116318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9687312,"threshold_uncertainty_score":0.9989434,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2074009058","doi":"10.1287/inte.32.2.28.59","title":"In Search of Strategic Operations Research/Management Science","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Competitive advantage; Strategic planning; Work (physics); Strategic management; Key (lock); Inclusion (mineral); Profit impact of marketing strategy; Business; Strategic information system; Strategic thinking; Strategic financial management; Knowledge management; Process management; Information system; Computer science; Engineering; Marketing; Management information systems; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.2551161738251385,"gpt":0.3761353162200654,"spread":0.1210191423949269,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001977991,0.000128523,0.0001762798,0.002008506,0.0003843259,0.0007523641,0.0008395919,0.00004911186,0.000713605],"category_scores_gemma":[0.00005085809,0.00009725641,0.00004218453,0.003579543,0.0004131616,0.001628388,0.0002460551,0.0005684511,0.0007005179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001052066,"about_ca_system_score_gemma":0.00004509882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006161637,"about_ca_topic_score_gemma":0.00003857259,"domain_scores_codex":[0.9975491,0.0000039607,0.0005255761,0.0001921299,0.001246896,0.0004822956],"domain_scores_gemma":[0.9990682,0.00002630182,0.00008989808,0.0003164034,0.0004655632,0.00003362075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003058546,0.0002821795,0.000305234,0.0001046199,0.00001830757,0.00003661319,0.00009575113,0.0242259,0.0005382042,0.9622625,0.001454468,0.01064569],"study_design_scores_gemma":[0.003315119,0.0002019649,0.008241659,0.0008357682,0.0001050384,0.00007298276,0.01165646,0.7841619,0.003632319,0.09372948,0.09257594,0.001471369],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4269432,0.00004052534,0.0007779034,0.001210087,0.0003117485,0.0003591853,0.000003379047,0.00002488475,0.5703291],"genre_scores_gemma":[0.9981743,0.0001864986,0.000292538,0.0005354256,0.0002981794,0.000004486029,0.000002847978,0.00000986057,0.000495937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.868533,"threshold_uncertainty_score":0.9003974,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3000986316","doi":"10.1287/inte.2019.1022","title":"Analytics and Optimization Reduce Sewage Overflows to Protect Community Waterways in Kentucky","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Tetra Tech (Canada)","funders":"","keywords":"Combined sewer; Analytics; Metropolitan area; Sanitary sewer; Routing (electronic design automation); Maximization; Environmental science; General partnership; Computer science; Environmental engineering; Computer network; Stormwater; Business; Data science; Finance; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.03268766417471507,"gpt":0.2363283965739841,"spread":0.2036407323992691,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005805476,0.0002123281,0.0002417835,0.0001734725,0.0003227086,0.0001800374,0.0003836079,0.00007672749,0.0002766169],"category_scores_gemma":[0.0000713023,0.000177347,0.00005234127,0.0007360173,0.00008790106,0.0003277961,0.0004039942,0.0007731846,0.0001992323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004007084,"about_ca_system_score_gemma":0.00001487331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000568671,"about_ca_topic_score_gemma":0.00004940659,"domain_scores_codex":[0.9984384,0.00004033219,0.0005187412,0.0001881168,0.0004496333,0.0003647616],"domain_scores_gemma":[0.9991415,0.0000312918,0.0001788628,0.0002717603,0.000014151,0.0003624253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009598075,0.0000814778,0.002980979,0.00001527132,0.0000288704,0.00001312366,0.002000222,0.9895476,0.0005254576,0.0002559546,0.002758347,0.001696755],"study_design_scores_gemma":[0.004216141,0.001554155,0.02841586,0.0001461328,0.0002201164,0.00005993027,0.003272253,0.8912203,0.002477427,0.002084918,0.06467601,0.001656782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7638318,0.000008326492,0.1676632,0.005146515,0.0001310885,0.001527665,0.00002139055,0.0001354973,0.0615345],"genre_scores_gemma":[0.9888344,0.00003577481,0.008074791,0.00272424,0.00005530566,0.00001146392,0.000009704446,0.00002168374,0.0002325972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2250027,"threshold_uncertainty_score":0.7232002,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2162064622","doi":"10.1287/inte.2013.0702","title":"Editorial: The 10th Rothkopf Rankings of Universities’ Contributions to the INFORMS Practice Literature","year":2013,"lang":"en","type":"editorial","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Visibility; Ranking (information retrieval); Yield (engineering); Norwegian; Library science; Sociology; Management; Geography; Computer science; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01221001072816613,"gpt":0.2812236583623554,"spread":0.2690136476341892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002051763,0.000542492,0.0006308435,0.0006273211,0.0007471798,0.002493799,0.00231075,0.0008442904,0.0001464422],"category_scores_gemma":[0.002333372,0.0002771046,0.0003019029,0.001801784,0.0002158107,0.002720617,0.000556972,0.003306681,0.000734023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003134394,"about_ca_system_score_gemma":0.0006953407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002218395,"about_ca_topic_score_gemma":0.00002959433,"domain_scores_codex":[0.9956005,0.00001311276,0.001071002,0.0002699391,0.002461168,0.0005843307],"domain_scores_gemma":[0.9903653,0.001056662,0.002297667,0.0008445098,0.00537418,0.00006170224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003134542,0.00004779858,8.310172e-7,0.0001112967,0.0002428482,0.000004851926,0.0002474466,0.0009335809,0.000002279037,0.0223698,0.973334,0.002391884],"study_design_scores_gemma":[0.0005219821,0.00003728946,0.000003214274,0.0004921193,0.0004386319,0.000007440136,0.001843407,0.000208672,0.000006515356,0.001380687,0.9946714,0.000388666],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002893863,0.0001167715,0.002252415,0.004773851,0.969516,0.0007373659,0.0005716833,0.00005443693,0.0219485],"genre_scores_gemma":[0.0009917802,0.0005731689,0.00006182955,0.003216704,0.9929006,0.00001995164,0.0005363718,0.00004688644,0.001652735],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02338453,"threshold_uncertainty_score":0.9999681,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3174371370","doi":"10.1287/inte.2021.1073","title":"Seasonal Inventory Management Model for Raw Materials in Steel Industry","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Raw material; Yard; Economic shortage; Business; Operations management; Environmental science; Supply chain; Operations research; Port (circuit theory); Inventory theory; Inventory control; Waste management; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02789558829875992,"gpt":0.2582201354321988,"spread":0.2303245471334389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007679278,0.0002833986,0.0003558985,0.0005949012,0.0002198841,0.0007099793,0.0003996872,0.0001949953,0.0002891344],"category_scores_gemma":[0.00003255563,0.0002350653,0.0001451207,0.0005839175,0.00004735879,0.000625528,0.0002421612,0.0004762814,0.0001300531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705361,"about_ca_system_score_gemma":0.00008043477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004517893,"about_ca_topic_score_gemma":0.00002371226,"domain_scores_codex":[0.9978262,0.00000466239,0.0007136782,0.0002895563,0.0006115122,0.0005543802],"domain_scores_gemma":[0.9991004,0.00002566877,0.0003844587,0.000291997,0.0001477626,0.00004972231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005161514,0.0006169772,0.003734795,0.0007560034,0.0003764657,0.0003957668,0.0001640886,0.3722683,0.0004458597,0.5334334,0.05588432,0.03140782],"study_design_scores_gemma":[0.01004439,0.00005777032,0.009719956,0.0006514383,0.000550508,0.00003492373,0.006764917,0.6716641,0.001500639,0.09731847,0.199869,0.001823925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8408613,0.00009058309,0.01670411,0.003145371,0.001573806,0.001539773,0.00002507617,0.0001534855,0.1359065],"genre_scores_gemma":[0.9818395,0.0001447964,0.0008715288,0.01143079,0.001033077,0.00005956205,0.00007578393,0.00004419098,0.004500779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4361149,"threshold_uncertainty_score":0.9585686,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015655819","doi":"10.1287/inte.1120.0632","title":"Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"League; Football; Scheduling (production processes); Analytics; Sport management; Recreation; Operations research; Computer science; Engineering; Advertising; Data science; Business; Political science; Public relations; Operations management","retraction":null,"screen_n_in":null,"score":{"opus":0.05280231666078187,"gpt":0.3403268695709684,"spread":0.2875245529101865,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007576582,0.000308009,0.0004734959,0.001281532,0.0009947052,0.0004622507,0.0008479907,0.0001662841,0.001090768],"category_scores_gemma":[0.001212732,0.0001921808,0.0002320766,0.00325733,0.00009940255,0.0003915353,0.0001266984,0.001152402,0.001623827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002620844,"about_ca_system_score_gemma":0.000187669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002771889,"about_ca_topic_score_gemma":0.00001285297,"domain_scores_codex":[0.994532,0.00003824823,0.001597488,0.0004021412,0.002629297,0.0008008169],"domain_scores_gemma":[0.9969658,0.0003655962,0.0007294117,0.001035557,0.000362824,0.0005407571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002125347,0.0006846769,0.008204288,0.000004027089,0.00007203338,0.000008660581,0.001493867,0.6303902,0.00001402704,0.07056223,0.1204401,0.1679135],"study_design_scores_gemma":[0.0003120078,0.00007418229,0.005534096,0.00002545822,0.0000612679,0.00004839129,0.001498559,0.003072192,0.000112164,0.005778708,0.9832009,0.000282085],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5482351,0.0003098643,0.09144304,0.09449985,0.01831025,0.003379385,0.00008745565,0.0003594564,0.2433756],"genre_scores_gemma":[0.9326882,0.0001090599,0.004485185,0.002208115,0.0558393,0.00003326179,0.00001360826,0.00003246367,0.004590755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8627608,"threshold_uncertainty_score":0.9998224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3129384632","doi":"10.1287/inte.2022.1132","title":"Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto","year":2022,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"","keywords":"Scheduling (production processes); Status quo; Computer science; Absenteeism; Schedule; Long-term care; Operations management; Operations research; Nursing; Nurse scheduling problem; Business; Job shop scheduling; Medicine; Flow shop scheduling; Economics; Engineering; Management","retraction":null,"screen_n_in":null,"score":{"opus":0.05387119972986606,"gpt":0.3475262837933807,"spread":0.2936550840635146,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002132987,0.0001413182,0.0003075658,0.0001394823,0.001301382,0.0001550595,0.00106184,0.00005364784,0.0007062604],"category_scores_gemma":[0.0004984774,0.00007335527,0.0003012721,0.0007533355,0.0002173615,0.0001783408,0.0002551492,0.0004469143,0.000004946422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005341136,"about_ca_system_score_gemma":0.0002852524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002305054,"about_ca_topic_score_gemma":0.00005802002,"domain_scores_codex":[0.9964797,0.00007697431,0.0009572504,0.0001664532,0.002064841,0.0002547239],"domain_scores_gemma":[0.9971849,0.0004409617,0.001193092,0.0006219572,0.0004700366,0.00008909954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007923619,0.00007853279,0.005080554,0.000005278152,0.00005626728,7.097838e-7,0.002323807,0.9785236,0.00007993067,0.002196155,0.000152562,0.01142337],"study_design_scores_gemma":[0.008824462,0.002029847,0.1174676,0.001080068,0.001792828,0.0006340637,0.254793,0.5548309,0.02375463,0.02422759,0.008287432,0.002277572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9432424,0.00146451,0.03907478,0.0007212524,0.001049297,0.0003036526,0.00006329131,0.00002169731,0.01405912],"genre_scores_gemma":[0.9974898,0.00007967621,0.001753086,0.00009520938,0.00008377417,0.000003300844,0.00000599095,0.00001056298,0.0004785766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4236927,"threshold_uncertainty_score":0.9999988,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2916399584","doi":"10.1287/inte.2018.0969","title":"Automated Pathologist Scheduling at The Ottawa Hospital","year":2019,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Canadian Electricity Association; Ottawa Hospital; University of Ottawa","funders":"Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine","keywords":"Scheduling (production processes); Medical laboratory; Medicine; Computer science; Medical physics; Medical emergency; Pathology; Operations management; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03070036650754712,"gpt":0.3653847770548557,"spread":0.3346844105473086,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001734269,0.000194694,0.0002812206,0.0001456024,0.001899247,0.00009601401,0.0002674884,0.0002734688,0.0009945962],"category_scores_gemma":[0.0002330853,0.0001112467,0.00009927493,0.0003699386,0.0000613678,0.0001562961,0.00009077637,0.001457673,0.003894534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004669285,"about_ca_system_score_gemma":0.0004711468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001285749,"about_ca_topic_score_gemma":0.00002422051,"domain_scores_codex":[0.9977727,0.00009568747,0.0009749896,0.0001784006,0.0004434074,0.0005348275],"domain_scores_gemma":[0.9981619,0.000309283,0.0005778904,0.0004012098,0.0003477402,0.0002019815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002315881,0.0002300555,0.0708376,0.0002006615,0.0002120431,0.00004162882,0.006968087,0.8116127,0.0004493077,0.06878421,0.03255429,0.007877777],"study_design_scores_gemma":[0.004978097,0.0009493107,0.02703365,0.0005427837,0.0001140056,0.00008046586,0.01471907,0.7851032,0.0001407905,0.001163238,0.1640499,0.001125463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9270388,0.00004493748,0.004263137,0.006991794,0.001584596,0.001038345,0.00001794055,0.0002904541,0.05873],"genre_scores_gemma":[0.9866652,0.0001277276,0.004029028,0.004824002,0.0003654858,0.00002470289,0.00004735793,0.00003201915,0.003884459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1314956,"threshold_uncertainty_score":0.9999186,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2594829375","doi":"10.1287/inte.2016.0864","title":"A Review of Scheduling Problems and Research Opportunities in Motion Picture Exhibition","year":2017,"lang":"en","type":"review","venue":"INFORMS Journal on Applied Analytics","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Exhibition; Movie theater; Film industry; Scheduling (production processes); Computer science; Context (archaeology); Scale (ratio); Engineering; Data science; Multimedia; Visual arts; Art; Operations management; History; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.4224786817422227,"gpt":0.3940462467131995,"spread":0.02843243502902321,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003406087,0.0002621827,0.002040637,0.001239946,0.0001826389,0.0001177509,0.0002644998,0.0002372167,0.00003895184],"category_scores_gemma":[0.0004818196,0.0002068309,0.0002585278,0.0002731366,0.00014491,0.0001615646,0.0001046989,0.001214415,0.00003317766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001915947,"about_ca_system_score_gemma":0.0001259912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006042012,"about_ca_topic_score_gemma":0.000006165733,"domain_scores_codex":[0.9975369,0.00001775265,0.00177438,0.0002212493,0.000141936,0.0003077618],"domain_scores_gemma":[0.9973281,0.0001223912,0.001973159,0.0003254975,0.0001343732,0.0001164838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005398605,0.00005200037,0.00002402758,0.1077636,0.0001516826,0.00001286495,0.0002558985,0.00001272544,2.461863e-8,0.03922742,0.0007583823,0.851736],"study_design_scores_gemma":[0.0002275074,0.00006030586,0.000008309611,0.09452972,0.00006121066,0.00003659656,0.0001132951,0.00002487852,1.108538e-7,0.006402101,0.8983465,0.0001894802],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001146744,0.9772106,0.00007005729,0.0001813384,0.0001340995,0.000543346,0.00004708439,0.000004688241,0.02179729],"genre_scores_gemma":[0.0001406875,0.9990396,0.0001130063,0.0001185161,0.0001989466,0.00003994904,0.00003640317,0.00002388609,0.0002889295],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8975881,"threshold_uncertainty_score":0.8434319,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2147714773","doi":"10.1287/inte.1100.0520","title":"Taking the Politics Out of Paving: Achieving Transportation Asset Management Excellence Through OR","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Government of New Brunswick; Transport Canada","funders":"U.S. Department of Transportation","keywords":"Asset management; Asset (computer security); Business; Heuristic; Operations research; Transport engineering; Finance; Computer science; Engineering; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.2077104877777052,"gpt":0.372130339538934,"spread":0.1644198517612288,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00180096,0.0001838216,0.0002700837,0.0003546277,0.0003952899,0.0002295917,0.0009188883,0.00005904915,0.001146986],"category_scores_gemma":[0.0001021438,0.0000954091,0.0001583506,0.0007502135,0.0001543455,0.0005428228,0.00005690691,0.000354668,0.00009255611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004721709,"about_ca_system_score_gemma":0.00005952543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000920148,"about_ca_topic_score_gemma":0.00002545326,"domain_scores_codex":[0.9968451,0.00002296343,0.001243621,0.0001912883,0.001391068,0.000305914],"domain_scores_gemma":[0.9976721,0.0002332993,0.001354168,0.0004607033,0.0002063536,0.0000734193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005321888,0.0001806089,0.02687626,0.0001018873,0.000407451,0.0000560407,0.0184333,0.003040665,0.00005481338,0.5484824,0.003502664,0.3983317],"study_design_scores_gemma":[0.004766453,0.001090282,0.260568,0.0006600733,0.0009112039,0.0001125161,0.0926161,0.01102329,0.003906209,0.2108441,0.4116539,0.001847877],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.281716,0.00003389991,0.1115822,0.0005283564,0.001613001,0.000634666,0.00001938128,0.00005983989,0.6038127],"genre_scores_gemma":[0.9928634,0.0002601577,0.004089451,0.0004731682,0.0001105154,0.000004619837,0.000002097398,0.00001013376,0.002186456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7111474,"threshold_uncertainty_score":0.9997661,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3044751814","doi":"10.1287/inte.2020.1027","title":"Barrick’s Turquoise Ridge Gold Mine Optimizes Underground Production Scheduling Operations","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Barrick Gold (Canada)","funders":"","keywords":"Production (economics); Time horizon; Schedule; Resource (disambiguation); Horizon; Computer science; Operations research; Mining engineering; Engineering; Business; Mathematics; Finance; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.02620593714103942,"gpt":0.2249408667407473,"spread":0.1987349295997079,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001749768,0.0002019844,0.0002427869,0.000134951,0.0001229497,0.0002590695,0.0001990348,0.0000847843,0.0000698907],"category_scores_gemma":[0.00005545881,0.0001797706,0.00009154246,0.000214247,0.00002415224,0.0002956751,0.00003133551,0.0005295156,0.000104014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001614504,"about_ca_system_score_gemma":0.00004180491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001475596,"about_ca_topic_score_gemma":0.000004071495,"domain_scores_codex":[0.9989586,0.000002816119,0.0005066523,0.0001368256,0.0001443994,0.0002507203],"domain_scores_gemma":[0.9994472,0.00001885936,0.00007533645,0.0001719686,0.00004951997,0.0002371064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002066965,0.00001160356,0.00001859449,0.00002310008,0.00007287059,0.000004047683,0.0002269503,0.9895909,0.001017511,0.003669816,0.003657738,0.001686229],"study_design_scores_gemma":[0.000506514,0.0001321252,0.00003555487,0.00004470014,0.00006357499,0.00006484437,0.0004510096,0.9788206,0.005094517,0.0005012915,0.01385135,0.0004339826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.774781,0.0001220753,0.1900462,0.002484706,0.0008935412,0.0004314967,0.00002364639,0.0008755989,0.0303417],"genre_scores_gemma":[0.9558015,0.0004718903,0.04207496,0.0006219344,0.000833637,0.000008241221,0.00001903142,0.00004482143,0.0001239578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1810205,"threshold_uncertainty_score":0.7330833,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046076181","doi":"10.1287/inte.1070.0322","title":"Optimizing Highway Transportation at the United States Postal Service","year":2007,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Postal service; Service (business); Transport engineering; Business; Finance; Engineering; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01934596091721497,"gpt":0.2791708987249374,"spread":0.2598249378077224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00122441,0.0001285124,0.0001210473,0.0002370612,0.00116649,0.0001703283,0.0002000266,0.0001064202,0.0001293864],"category_scores_gemma":[0.00002011073,0.0000888892,0.00006675732,0.0009191602,0.00009247116,0.000206915,0.000002977166,0.0003284313,0.00004966971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001751329,"about_ca_system_score_gemma":0.0001200069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002691842,"about_ca_topic_score_gemma":0.00268101,"domain_scores_codex":[0.9984357,0.00001594195,0.0004760401,0.0001019233,0.0006303304,0.0003400182],"domain_scores_gemma":[0.9989095,0.0001997369,0.0003237801,0.0001017886,0.0002785342,0.0001867075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002890014,0.00004080137,0.001318157,0.000009521165,0.00006834588,0.00002227223,0.05017513,0.9192377,0.00004993695,0.02526229,0.001278609,0.002248261],"study_design_scores_gemma":[0.003496293,0.0002453502,0.0389866,0.0001644869,0.0003611101,0.00002124237,0.1210678,0.01889903,0.001638426,0.002856244,0.8110922,0.001171206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9046055,0.00003046594,0.0575869,0.004723721,0.0004392151,0.0003077913,0.00004503326,0.0001857135,0.03207566],"genre_scores_gemma":[0.9930326,0.0002468489,0.001517475,0.003631391,0.0001901244,0.000001607445,0.0004803634,0.00001684162,0.0008827007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9003386,"threshold_uncertainty_score":0.8971816,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2917137472","doi":"10.1287/inte.2018.0972","title":"Operations Research Enables Auction to Repurpose Television Spectrum for Next-Generation Wireless Technologies","year":2019,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Spectrum auction; Wireless; Telecommunications; Business; Computer science; Advertising; Marketing; Auction theory","retraction":null,"screen_n_in":null,"score":{"opus":0.2383467181516775,"gpt":0.4288633834914778,"spread":0.1905166653398002,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004965511,0.0001934816,0.000319403,0.001358487,0.001281889,0.001455751,0.0008751329,0.0001972086,0.000238224],"category_scores_gemma":[0.001142053,0.0001333658,0.0001537037,0.002101996,0.0001199362,0.0007606042,0.0001397091,0.000635697,0.001685872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002660622,"about_ca_system_score_gemma":0.0002004802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003128666,"about_ca_topic_score_gemma":0.00001896813,"domain_scores_codex":[0.9964938,0.00005548444,0.001055349,0.0004592806,0.001488487,0.0004475578],"domain_scores_gemma":[0.9972711,0.0005862907,0.000245156,0.000834231,0.000890479,0.0001727892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002095189,0.0001409849,0.000055035,0.000006775559,0.0000373818,0.000001204461,0.0003945531,0.238825,0.03194248,0.5399103,0.01523129,0.1732455],"study_design_scores_gemma":[0.001128057,0.001073818,0.0001165166,0.00006137216,0.00003125664,0.00008639105,0.01533727,0.1983129,0.1017879,0.2984568,0.3830052,0.0006025428],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5429646,0.00002740241,0.433759,0.01483809,0.0007803874,0.002114953,0.0000307933,0.000202378,0.005282377],"genre_scores_gemma":[0.9903235,0.00008486582,0.002552437,0.0003531749,0.000422256,0.0001074165,0.00001623917,0.00002052859,0.006119516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4473589,"threshold_uncertainty_score":0.9995809,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015973458","doi":"10.1287/inte.32.2.74.64","title":"How Should Team Captains Order Golfers on the Final Day of the Ryder Cup Matches?","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada; Royal Ottawa Mental Health Centre","funders":"","keywords":"Order (exchange); SLATES; Advertising; Momentum (technical analysis); Engineering; Management; Operations research; Operations management; Marketing; Business; Computer science; Economics; World Wide Web; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.08696453909582184,"gpt":0.2210731652860867,"spread":0.1341086261902649,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008495424,0.0002724425,0.0004347643,0.0002490795,0.0003570471,0.0003117353,0.0006971046,0.0001453936,0.001097852],"category_scores_gemma":[0.0001595205,0.000152318,0.0003062966,0.0005806223,0.0001755314,0.00017164,0.00006660222,0.0008813984,0.0002488137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001451865,"about_ca_system_score_gemma":0.00003498693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001066076,"about_ca_topic_score_gemma":0.000009188402,"domain_scores_codex":[0.9982917,0.000005010997,0.0008370791,0.0002068984,0.000245645,0.0004136815],"domain_scores_gemma":[0.9979969,0.0001326266,0.001032826,0.0006237703,0.00009175477,0.0001220702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006375345,0.0005413746,0.05400978,0.00007301252,0.000511819,0.00001129139,0.00224425,0.03929606,0.00001738928,0.8153696,0.08280925,0.005052379],"study_design_scores_gemma":[0.001678148,0.0003903102,0.02511133,0.0001254702,0.00009969623,0.00005104054,0.00151086,0.1530815,0.0003739438,0.01663828,0.800036,0.0009033631],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4313044,0.0005263934,0.003361287,0.03207587,0.001592361,0.0008315617,0.0002922448,0.00005049815,0.5299654],"genre_scores_gemma":[0.9829155,0.0007043933,0.00005262762,0.003454773,0.0002546413,0.000005490461,0.000002105739,0.00002917016,0.01258135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7987313,"threshold_uncertainty_score":0.9998153,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012135359","doi":"10.1287/inte.2020.1031","title":"A Decision Support System for Attended Home Services","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Decision support system; Business; Electricity; Distribution (mathematics); Operations research; Operations management; Marketing; Computer science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01422764611899736,"gpt":0.2260256437190176,"spread":0.2117979976000203,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001049658,0.0001722468,0.0002354087,0.0001020616,0.0001075465,0.0001191654,0.0001847133,0.00008680562,0.00001447293],"category_scores_gemma":[0.00001303462,0.0001373383,0.00008473987,0.0001274496,0.00001122667,0.0001250173,0.00001843685,0.0002419322,0.00006557174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001084508,"about_ca_system_score_gemma":0.00001728921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.375675e-7,"about_ca_topic_score_gemma":4.257448e-7,"domain_scores_codex":[0.9990177,0.00000130937,0.0004127722,0.0001025756,0.000228019,0.0002376087],"domain_scores_gemma":[0.9994279,0.00006171518,0.0001181815,0.0001167186,0.00006573441,0.0002098099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009186598,0.0000052907,0.000005750207,0.0002094924,0.00004675782,0.00000725942,0.0001359159,0.9870995,0.00004674379,0.003932954,0.000439594,0.007978847],"study_design_scores_gemma":[0.00173149,0.0002252586,0.00004912267,0.00008531308,0.00008168177,0.00004304521,0.0006285854,0.9673878,0.002551994,0.003220652,0.02358329,0.0004118003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00340229,0.00001288698,0.9902187,0.00006205821,0.0003195353,0.0001589387,0.00002245972,0.0002686169,0.005534525],"genre_scores_gemma":[0.971018,0.00006144369,0.02813219,0.0003868135,0.0003062098,0.000006858889,0.00002827489,0.00003685251,0.00002333859],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9676157,"threshold_uncertainty_score":0.5600493,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2785506546","doi":"10.1287/inte.2017.0930","title":"Discrete-Event Simulation Modeling Unlocks Value for the Jansen Potash Project","year":2018,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Amec Foster Wheeler (Canada); BHP (Canada)","funders":"","keywords":"Net present value; Discrete event simulation; Production (economics); Engineering; Operations research; Dice; Potash; Operations management; Event (particle physics); Economics; Simulation; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03419948282742167,"gpt":0.2935306931228241,"spread":0.2593312102954024,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004754478,0.0001598435,0.0001666813,0.000119097,0.000231308,0.0001550889,0.0002249447,0.00009242412,0.00001242625],"category_scores_gemma":[0.00002206152,0.0001053522,0.0001204563,0.0001017657,0.00002633418,0.0001068499,0.00002604638,0.000273231,0.0000176652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001467252,"about_ca_system_score_gemma":0.00003560743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002866078,"about_ca_topic_score_gemma":0.000003702207,"domain_scores_codex":[0.9990667,0.000002384411,0.0004405411,0.00008694132,0.0001337725,0.0002697381],"domain_scores_gemma":[0.9994688,0.00009058737,0.0001041365,0.0002132918,0.00006211772,0.0000610713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003657991,0.000004949718,0.000006139758,0.00001053785,0.00006932959,3.031428e-7,0.0002736835,0.9860422,0.00001648797,0.00510992,0.0008779169,0.007551923],"study_design_scores_gemma":[0.0002566078,0.00009695966,0.000004036519,0.00002463639,0.00004196984,0.000007415276,0.0001559346,0.9758798,0.0002449932,0.003321602,0.01980795,0.0001580635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02764749,0.00001538328,0.9634551,0.00007658676,0.0002425399,0.0003511218,0.00001121771,0.0001287142,0.008071831],"genre_scores_gemma":[0.9927703,0.00008764045,0.006193978,0.0001997081,0.0006309299,0.00001475953,0.000006365044,0.00003573184,0.00006065477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9651228,"threshold_uncertainty_score":0.4296136,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}