{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":60,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":60,"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":"828120d46610","filters":{"venue":"Decision Support Systems"}},"results":[{"id":"W2091139645","doi":"10.1016/j.dss.2009.02.014","title":"Virtual worlds — past, present, and future: New directions in social computing","year":2009,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Games and Media","field":"Social Sciences","cited_by":435,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"IBM (Canada); University of Toronto; University of Alberta","funders":"","keywords":"Metaverse; Extant taxon; Frontier; Theme (computing); TRACE (psycholinguistics); Social worlds; Focus (optics); Sociology; Data science; Virtual machine; Virtual world; Computer science; Virtual reality; World Wide Web; Social science; Human–computer interaction; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02592232241745073,"gpt":0.3256713621303726,"spread":0.2997490397129219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007018535,0.0001017235,0.0002307405,0.0001419881,0.0001985318,0.0002936237,0.000156995,0.0001091549,0.00006154964],"category_scores_gemma":[0.00004028195,0.00009320133,0.00005742631,0.000479381,0.00005772008,0.0002463234,0.00003796628,0.0001084578,0.00004162479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005768704,"about_ca_system_score_gemma":0.0001336267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002684185,"about_ca_topic_score_gemma":0.0002310125,"domain_scores_codex":[0.9984869,0.00008160013,0.0003388125,0.0002428054,0.0005344214,0.0003155029],"domain_scores_gemma":[0.9993717,0.000160293,0.00008916535,0.000097222,0.0000477467,0.0002338602],"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":[0.00001122878,0.00003434088,0.001729817,0.00000128205,0.000003359532,0.00001474792,0.007678899,0.000003800493,0.000002847715,0.006198419,0.1113483,0.872973],"study_design_scores_gemma":[0.0002924163,0.0000459793,0.02049189,0.00002501859,0.000003538244,0.000005170027,0.007104052,0.00004394814,6.273721e-7,0.0002770988,0.971605,0.0001052512],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1799375,0.001475569,0.003103897,0.01297131,0.009153203,0.001154983,0.00002051106,0.0003296998,0.7918533],"genre_scores_gemma":[0.9487783,0.00009489033,0.0001274674,0.0001718107,0.01159019,0.000003204344,0.000007305317,0.000009585598,0.03921722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8728677,"threshold_uncertainty_score":0.380064,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2117204836","doi":"10.1016/s0167-9236(00)00065-8","title":"Project portfolio selection through decision support","year":2000,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":379,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Portfolio; Selection (genetic algorithm); Decision support system; Project portfolio management; Resource (disambiguation); Usability; Application portfolio management; Quality (philosophy); Computer science; Risk analysis (engineering); Investment (military); Business; Operations research; Process management; Project management; Systems engineering; Engineering; Finance; Data mining; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.07175070099255448,"gpt":0.3266277910032583,"spread":0.2548770900107038,"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":[0.001126125,0.0004881667,0.0006197264,0.0005592815,0.000443374,0.001079432,0.0008044413,0.000310841,0.02793285],"category_scores_gemma":[0.0001989273,0.000400784,0.0002177682,0.002087875,0.00007591266,0.003926781,0.0001987029,0.0002746716,0.01795211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008210241,"about_ca_system_score_gemma":0.0001445408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001649284,"about_ca_topic_score_gemma":0.00009016807,"domain_scores_codex":[0.9955932,0.00002163331,0.001297055,0.0009851839,0.001379755,0.0007231023],"domain_scores_gemma":[0.9980047,0.0001380241,0.0004281603,0.0008555214,0.0005350981,0.00003843513],"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":[0.0003560634,0.0002050279,0.00848183,0.0001191423,0.0000331173,0.000115111,0.0000525185,0.0001884548,0.00009249291,0.002084638,0.70222,0.2860517],"study_design_scores_gemma":[0.0005247953,0.000045523,0.002572144,0.0001902204,0.00005797604,0.0002341075,0.0001459853,0.003248745,0.00006682405,0.001342694,0.9910401,0.000530947],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3855232,0.0004899825,0.132,0.0003006792,0.01197685,0.003541789,0.0001229958,0.001732149,0.4643123],"genre_scores_gemma":[0.9691835,0.0002760489,0.002227487,0.001597065,0.003972617,0.0001662689,0.000682775,0.0001486023,0.02174562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5836603,"threshold_uncertainty_score":0.9999576,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2727729132","doi":"10.1016/j.dss.2017.06.004","title":"Increasing firm agility through the use of data analytics: The role of fit","year":2017,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":239,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Leverage (statistics); Agile software development; Analytics; Dynamic capabilities; Data analysis; Business analytics; Data science; Computer science; Knowledge management; Perspective (graphical); Order (exchange); Business; Process management; Business model; Marketing; Data mining; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.3523520200785031,"gpt":0.374713631088695,"spread":0.02236161101019191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002038368,0.0001657799,0.000365434,0.00006490985,0.0005363945,0.0008548871,0.003200656,0.00008133393,0.0002640213],"category_scores_gemma":[0.002206389,0.00008626669,0.00008650427,0.0002373494,0.0003169692,0.003746397,0.001947368,0.0001281474,0.0001229334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009301923,"about_ca_system_score_gemma":0.00003973829,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01664166,"about_ca_topic_score_gemma":0.0003182635,"domain_scores_codex":[0.9979434,0.00003426753,0.0007671776,0.0003652167,0.00068089,0.000209043],"domain_scores_gemma":[0.9932677,0.0006082004,0.001206438,0.004426081,0.000482001,0.000009589238],"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":[0.0004998024,0.0003601187,0.6305175,0.0006353864,0.0002770274,0.00002405601,0.0003218164,0.0005858361,0.0005481403,0.01652366,0.142985,0.2067216],"study_design_scores_gemma":[0.0001258141,0.000004883225,0.04064107,0.0002314064,0.0001047195,0.00001223082,0.0005158939,0.03005868,0.00006079581,0.001342266,0.9267679,0.0001343134],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9424102,0.001600589,0.0287916,0.001511924,0.003747987,0.001764893,0.0009453708,0.00009627581,0.01913121],"genre_scores_gemma":[0.9988023,0.00004439251,0.0002868966,0.0001316039,0.0004328022,0.000004990557,0.0001080482,0.00001504209,0.0001739338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.783783,"threshold_uncertainty_score":0.9899066,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2586885238","doi":"10.1016/j.dss.2017.02.001","title":"Online review helpfulness: Impact of reviewer profile image","year":2017,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":225,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Helpfulness; Perception; Psychology; Valence (chemistry); Emotional valence; Differential effects; Computer science; Social psychology; Medicine; Cognition; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.05327603447169874,"gpt":0.422788200665073,"spread":0.3695121661933742,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004850734,0.0001619605,0.0007453991,0.00005879451,0.0005670633,0.0002728455,0.0008348888,0.0001187887,0.001108474],"category_scores_gemma":[0.02155028,0.0001205581,0.0003876112,0.0001700665,0.0003192958,0.0005322369,0.0001204074,0.0001197025,0.0003843902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000965681,"about_ca_system_score_gemma":0.0004726732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001781435,"about_ca_topic_score_gemma":0.0001103184,"domain_scores_codex":[0.9972878,0.0003257061,0.0007713978,0.0002816705,0.0009828008,0.0003506727],"domain_scores_gemma":[0.996604,0.0004299852,0.0008557878,0.0008718441,0.0009798963,0.0002585146],"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":[0.0000434217,0.0003141412,0.01202853,0.001636884,0.00006912284,0.00005494825,0.001335617,1.913025e-7,0.00002928247,0.0008899917,0.6822169,0.301381],"study_design_scores_gemma":[0.0004815308,0.0001982765,0.02535497,0.01607154,0.00008229455,0.000007767532,0.001574141,0.00001236681,0.000009890972,0.0005470701,0.9551889,0.0004712362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1751207,0.03424419,0.0003363136,0.001501931,0.01090672,0.004297133,0.000853257,0.0002553431,0.7724844],"genre_scores_gemma":[0.964647,0.01694511,0.0004642603,0.0001243944,0.001258302,0.00008940288,0.00007063143,0.00004033516,0.01636054],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7895263,"threshold_uncertainty_score":0.9998047,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2014179994","doi":"10.1016/j.dss.2008.11.003","title":"Examining the success factors for mobile work in healthcare: A deductive study","year":2008,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":217,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Health care; Context (archaeology); Work (physics); Proposition; Computer science; Process (computing); Knowledge management; Process management; Business; Political science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.2567293354449826,"gpt":0.4267060105893846,"spread":0.169976675144402,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004929531,0.000274142,0.0006894897,0.0007516743,0.0005962123,0.0001861324,0.001527106,0.0002478333,0.0004037987],"category_scores_gemma":[0.002626305,0.0001595358,0.000145573,0.002243322,0.0001727465,0.000339985,0.0002314309,0.0003802318,0.0002672418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001195707,"about_ca_system_score_gemma":0.0001914499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003058089,"about_ca_topic_score_gemma":0.0001888925,"domain_scores_codex":[0.9947743,0.0004742557,0.001598759,0.0009391855,0.001708544,0.0005049095],"domain_scores_gemma":[0.9917701,0.005661624,0.0005179302,0.001373244,0.0005169591,0.0001600948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001038606,0.0002334331,0.959623,0.000001388183,0.000009197855,0.00005560132,0.004703615,0.00007779725,0.000002735665,0.00006246188,0.02968669,0.005440256],"study_design_scores_gemma":[0.0008476052,0.0004823412,0.930666,0.00002587021,0.000007537553,0.00007123077,0.04832049,0.00005558525,0.000009650385,0.00033013,0.01897463,0.0002089171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916387,0.0001602226,0.003072925,0.0002017897,0.00194369,0.002699487,0.0001059133,0.0001199258,0.00005731562],"genre_scores_gemma":[0.9965708,0.000006736234,0.0002468208,0.00007637813,0.0000682559,0.001120828,0.0000161102,0.00002720513,0.00186684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04361688,"threshold_uncertainty_score":0.6505681,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059263796","doi":"10.1016/j.dss.2007.02.004","title":"Weblogging: A study of social computing and its impact on organizations","year":2007,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":206,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Technische Universität Berlin; University of British Columbia; University of Hong Kong","keywords":"Computer science; Social impact; Business; Sociology; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.0383330722093607,"gpt":0.3953286684967534,"spread":0.3569955962873926,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00241816,0.00008834768,0.000218553,0.0002286924,0.000585657,0.0000954537,0.0001672356,0.00005815697,0.0001332137],"category_scores_gemma":[0.0002709492,0.0000747415,0.00003182238,0.0006626006,0.00002542307,0.00009328565,0.00009124527,0.00006539938,0.00005514072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006126646,"about_ca_system_score_gemma":0.00004485756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002096616,"about_ca_topic_score_gemma":0.0002611525,"domain_scores_codex":[0.9986141,0.00008976433,0.000380573,0.0001891225,0.0004980345,0.0002283915],"domain_scores_gemma":[0.9991279,0.000308171,0.0001581499,0.00009409284,0.0002277818,0.00008385659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001194718,0.001167856,0.5924713,0.00006507348,0.0001909831,0.00008660388,0.3348547,0.0002053515,0.0001701336,0.0325464,0.01356062,0.02456154],"study_design_scores_gemma":[0.00296376,0.0009840284,0.599924,0.0001669325,0.0001139184,0.000005848327,0.3541679,0.003798619,0.00004803947,0.0001954171,0.03697646,0.0006550899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9632162,0.00002565986,0.001427046,0.00001708195,0.0004545864,0.0004691168,0.000001897057,0.00005115707,0.03433723],"genre_scores_gemma":[0.9985395,0.000001678479,0.00001374155,0.000007864716,0.0002401894,0.000001188664,0.000002425343,0.00001030752,0.001183099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03532328,"threshold_uncertainty_score":0.450446,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2810318119","doi":"10.1016/j.dss.2018.06.012","title":"Which online reviews do consumers find most helpful? A multi-method investigation","year":2018,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":185,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Helpfulness; Argument (complex analysis); Computer science; Frame (networking); Perception; Psychology; Variance (accounting); Marketing; Social psychology; Medicine; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.08523670504956499,"gpt":0.4028864784627982,"spread":0.3176497734132332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007920405,0.0002046251,0.0005221107,0.000155078,0.0006239132,0.0003812026,0.0004075176,0.0002735998,0.0003746463],"category_scores_gemma":[0.01553246,0.0001785189,0.0001055971,0.001125992,0.0003630238,0.000335739,0.00007342666,0.0001827806,0.001230599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001295343,"about_ca_system_score_gemma":0.000503722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740704,"about_ca_topic_score_gemma":0.003844945,"domain_scores_codex":[0.9960698,0.001170237,0.0008942985,0.0004909995,0.0009065485,0.0004680917],"domain_scores_gemma":[0.9965756,0.001288549,0.0004271268,0.0004005202,0.0008482601,0.0004599338],"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":[0.000110969,0.0002877915,0.05580607,0.0001362925,0.0000652936,0.00002279837,0.05036815,0.000002964981,0.0003728131,0.003646394,0.2496493,0.6395312],"study_design_scores_gemma":[0.0004888106,0.00009656027,0.005278911,0.0005040721,0.00002425253,0.00000579579,0.009198023,0.0002772275,0.00001568758,0.0004453122,0.9833471,0.0003183019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5939754,0.003778321,0.03869495,0.004785284,0.03163033,0.00697504,0.0005249859,0.001037471,0.3185982],"genre_scores_gemma":[0.9436051,0.0007795226,0.02716707,0.001035104,0.002521763,0.0001275277,0.000159656,0.00006751368,0.02453672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7336978,"threshold_uncertainty_score":0.9995471,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2166048187","doi":"10.1016/j.dss.2012.05.030","title":"From once upon a time to happily ever after: Tracking emotions in mail and books","year":2012,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":161,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"","keywords":"Sentiment analysis; Affect (linguistics); Tracking (education); Computer science; Psychology; Negative emotion; Natural language processing; Social psychology; Communication","retraction":null,"screen_n_in":null,"score":{"opus":0.02628875647228958,"gpt":0.277846949778926,"spread":0.2515581933066364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009573109,0.0001534592,0.0003118254,0.0003305914,0.00007888548,0.0003522735,0.0003507569,0.0000715761,0.0003616718],"category_scores_gemma":[0.00005454636,0.000137387,0.00007283732,0.0003950385,0.000009229074,0.000766832,0.0002378645,0.00008750816,0.001738417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005088566,"about_ca_system_score_gemma":0.00002511509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001006258,"about_ca_topic_score_gemma":0.00001251219,"domain_scores_codex":[0.9981777,0.00009153585,0.0004805437,0.00042498,0.0004752991,0.0003499373],"domain_scores_gemma":[0.9988333,0.000261061,0.0001116023,0.0004991437,0.00005359116,0.0002412747],"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":[0.0001808685,0.0006973903,0.3626349,0.00005728281,0.0002666613,0.0003652509,0.04393004,0.0009316505,0.009028799,0.002138751,0.1157113,0.4640571],"study_design_scores_gemma":[0.001644849,0.0001645645,0.5042589,0.001083048,0.00005581754,0.0001066905,0.001260327,0.1451057,0.0003244393,0.0004000085,0.3443738,0.001221854],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7737768,0.0005668322,0.2228675,0.0002349974,0.0009182389,0.0002755546,0.00001148611,0.00007003974,0.001278582],"genre_scores_gemma":[0.9868785,0.000005043589,0.01068716,0.0001584698,0.0002048281,0.00002620108,0.000006629847,0.00001118207,0.002021989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4628352,"threshold_uncertainty_score":0.9990388,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2093064636","doi":"10.1016/j.dss.2010.03.005","title":"Credit risk measurement and early warning of SMEs: An empirical study of listed SMEs in China","year":2010,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":107,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Warning system; China; Business; Credit risk; Asset (computer security); Early warning system; Finance; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03176391947718251,"gpt":0.2781605241318947,"spread":0.2463966046547122,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001825273,0.0001619911,0.0004464659,0.0003846089,0.00009463098,0.0001164497,0.0001954393,0.000114789,0.00005004879],"category_scores_gemma":[0.0004213115,0.0001315586,0.00005141662,0.0003980409,0.00003948263,0.0006042584,0.0001119925,0.0002196721,0.000007165646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001455885,"about_ca_system_score_gemma":0.00002608876,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007503567,"about_ca_topic_score_gemma":0.001680529,"domain_scores_codex":[0.9977635,0.00003962087,0.0008567775,0.0003299672,0.0008323239,0.0001778134],"domain_scores_gemma":[0.9986751,0.00004383105,0.0005903098,0.0003381818,0.0003301126,0.00002245164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001224418,0.0005194764,0.9843137,0.0001007277,0.00001492234,0.00001126058,0.0007850088,0.00004770987,0.0006029592,0.00005180259,0.0006060955,0.01282386],"study_design_scores_gemma":[0.001122085,0.0002008668,0.9917688,0.0001335201,0.00004489483,0.000001763639,0.001277155,0.002761099,0.00001351805,0.0000733776,0.002476382,0.0001264971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99745,0.00005027807,0.0003564314,0.000008939893,0.0009890066,0.0004780411,0.000009216108,0.00003558541,0.0006225217],"genre_scores_gemma":[0.9995379,0.000004563397,0.00003823161,0.000005814886,0.0003442791,0.00002350782,0.000009938683,0.00001710951,0.00001859001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01269737,"threshold_uncertainty_score":0.9991056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2792794664","doi":"10.1016/j.dss.2018.03.005","title":"An empirical examination of the influence of biased personalized product recommendations on consumers' decision making outcomes","year":2018,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":105,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Personalization; Product (mathematics); Quality (philosophy); E-commerce; Empirical research; Decision quality; Business; Selection (genetic algorithm); Computer science; Marketing; World Wide Web; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.06048515195995671,"gpt":0.409405834508004,"spread":0.3489206825480473,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004295154,0.0001208621,0.0003308486,0.0001647958,0.0004274859,0.00008374512,0.0004718461,0.0001083071,0.0001336435],"category_scores_gemma":[0.00911888,0.00008455345,0.0001166521,0.0006442025,0.000607406,0.0002730701,0.00004848383,0.00009568573,0.00003176876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008790921,"about_ca_system_score_gemma":0.0002653102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002054608,"about_ca_topic_score_gemma":0.0001954421,"domain_scores_codex":[0.9967568,0.0008490575,0.0006730601,0.0002977187,0.001210622,0.0002127551],"domain_scores_gemma":[0.9952359,0.002995221,0.0004894273,0.0004427221,0.0007423394,0.00009438956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003204932,0.0005810983,0.489363,0.00004755245,0.00005800156,0.000003175435,0.05400756,0.00004322696,0.0003604849,0.00431228,0.008036892,0.4428662],"study_design_scores_gemma":[0.0007896458,0.0003261538,0.9392343,0.001116514,0.00003879,0.000002982602,0.01797314,0.0001471368,0.0001670235,0.0008629474,0.03906417,0.0002772313],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881525,0.00001232252,0.0003078747,0.0002764167,0.001417809,0.0004864195,0.00003658878,0.00003599096,0.009274053],"genre_scores_gemma":[0.9988802,0.000007874039,0.0004691474,0.00008438406,0.0001066055,0.00001624876,0.000005768802,0.0000114473,0.000418336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4498713,"threshold_uncertainty_score":0.9992277,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2471707884","doi":"10.1016/j.dss.2016.06.010","title":"Modeling customer satisfaction from unstructured data using a Bayesian approach","year":2016,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Customer satisfaction; Computer science; Bayesian probability; Set (abstract data type); Sentiment analysis; Probabilistic logic; Unstructured data; The Internet; Customer intelligence; Data mining; Service (business); Product (mathematics); Bayesian network; Variety (cybernetics); Data set; Data science; Artificial intelligence; Service quality; Customer retention; World Wide Web; Big data; Marketing; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.08640592321187143,"gpt":0.3129794778408794,"spread":0.226573554629008,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007405099,0.0001988351,0.0003633442,0.0002762066,0.0001745497,0.0003947305,0.001223669,0.0001158125,0.0001357647],"category_scores_gemma":[0.00004976338,0.0001292309,0.00008994875,0.0004240757,0.00001705428,0.00134962,0.0005451084,0.0000748226,0.000164027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007451471,"about_ca_system_score_gemma":0.00007890828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005413247,"about_ca_topic_score_gemma":0.00001212812,"domain_scores_codex":[0.9971613,0.0001061395,0.0006902533,0.0009316593,0.0008201189,0.0002904988],"domain_scores_gemma":[0.9974288,0.0001289455,0.0002150364,0.001969991,0.000107647,0.0001495313],"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":[0.00008467906,0.0001267581,0.0673884,0.0000369068,0.0006437503,0.00008316279,0.00159595,0.05180077,0.01923458,0.005645859,0.01877922,0.8345799],"study_design_scores_gemma":[0.0003931202,0.000006923494,0.0003585788,0.00007638326,0.00002370536,0.00002750597,0.0001239732,0.9966027,0.00004283285,0.0002248499,0.00191158,0.0002078161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04412153,0.0001118361,0.9537761,0.00003224852,0.001414404,0.0001410618,0.00003634056,0.00009461653,0.0002718811],"genre_scores_gemma":[0.8677049,0.0000127152,0.1318469,0.00002710317,0.0002376347,0.000003783629,0.00005863854,0.00001562304,0.00009276125],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.944802,"threshold_uncertainty_score":0.5269881,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2904467883","doi":"10.1016/j.dss.2018.12.001","title":"A utility-based news recommendation system","year":2018,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; Brock University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.04152165827660666,"gpt":0.3013225318215129,"spread":0.2598008735449062,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001855419,0.0002839174,0.0004887591,0.0003842837,0.0003006208,0.0006256364,0.00118253,0.0001949713,0.0001435402],"category_scores_gemma":[0.00005792906,0.000234594,0.0001595061,0.0006855359,0.0000430465,0.0006530344,0.000239344,0.0001392517,0.0009938686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292009,"about_ca_system_score_gemma":0.0001706792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003619668,"about_ca_topic_score_gemma":0.00004593626,"domain_scores_codex":[0.9967343,0.0003067718,0.001089468,0.000813595,0.0006095342,0.0004463019],"domain_scores_gemma":[0.9970834,0.0002534665,0.0004218004,0.001568474,0.0004363266,0.0002365095],"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":[0.00005557143,0.0001732699,0.009483305,0.0002260991,0.00005193338,0.00006641918,0.000490683,0.000002848039,0.0001948677,0.04069266,0.5174763,0.4310861],"study_design_scores_gemma":[0.0005941581,0.0003263778,0.0005048754,0.0002477698,0.000006935527,0.0001745745,0.0002290906,0.1569357,0.00112257,0.0002655766,0.8392243,0.0003680725],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001218265,0.00003221168,0.9570084,0.0003894338,0.004821694,0.0006737462,0.0000133833,0.001163331,0.03467954],"genre_scores_gemma":[0.962656,0.000002180683,0.03603224,0.0003095219,0.0004248563,0.0001072719,0.00002420441,0.00002608038,0.0004176737],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9614377,"threshold_uncertainty_score":0.999784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4245238933","doi":"10.1016/j.dss.2004.12.001","title":"Customer relationship management (CRM) in e-government: a relational perspective","year":2004,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Customer relationship management; Perspective (graphical); Incentive; Business; Relational view; Government (linguistics); Knowledge management; Value (mathematics); Enterprise relationship management; Position (finance); Marketing; Process management; Customer retention; Computer science; Economics; Microeconomics; Service (business); Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.04183160110416032,"gpt":0.2790030572955186,"spread":0.2371714561913583,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001193484,0.0002226688,0.0002820053,0.0004448208,0.0002041478,0.0002375391,0.0002757415,0.0001310167,0.0005338993],"category_scores_gemma":[0.0001193904,0.0002147506,0.000112434,0.001084549,0.00003335843,0.001196941,0.0001798352,0.0002345788,0.006051112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545603,"about_ca_system_score_gemma":0.00003239913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001200668,"about_ca_topic_score_gemma":0.0003478237,"domain_scores_codex":[0.9971887,0.00002309287,0.0007127968,0.0004964007,0.001243026,0.0003360234],"domain_scores_gemma":[0.9989855,0.000126534,0.0002814557,0.0004153019,0.0001617215,0.00002949017],"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":[0.0001055559,0.0002013708,0.07286076,0.00012128,0.00002932841,0.0001215562,0.000395009,0.004379002,0.000002614194,0.9172825,0.003901852,0.0005991987],"study_design_scores_gemma":[0.004679654,0.00002124365,0.5082708,0.0005036544,0.00009142719,0.0000309119,0.01565563,0.001398115,0.000002020424,0.07134275,0.3972226,0.0007812242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2549637,0.0002682698,0.01195366,0.002489278,0.002461334,0.001607654,0.00002568712,0.0002898672,0.7259405],"genre_scores_gemma":[0.9964359,0.000005443438,0.0003524636,0.001007892,0.0004365249,0.00008472156,0.00003977688,0.00003088721,0.00160635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8459397,"threshold_uncertainty_score":0.9947228,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012453507","doi":"10.1016/s0167-9236(02)00140-9","title":"Mobile clinical support system for pediatric emergencies","year":2002,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Fundacja na rzecz Nauki Polskiej","keywords":"Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.08130157364663176,"gpt":0.3269626436789583,"spread":0.2456610700323265,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002452574,0.0003118455,0.0007258297,0.0002603116,0.0002923968,0.0003501212,0.001628769,0.0002668863,0.0002414801],"category_scores_gemma":[0.0001544363,0.0002413793,0.0004468547,0.0006545927,0.00003736912,0.0004864626,0.0003146476,0.0001701115,0.002740693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006788611,"about_ca_system_score_gemma":0.00007922812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001033645,"about_ca_topic_score_gemma":0.000001176527,"domain_scores_codex":[0.9955326,0.000144677,0.001815406,0.0009612456,0.0008816106,0.0006644041],"domain_scores_gemma":[0.9967794,0.0005994359,0.0004647381,0.001452703,0.0003219553,0.0003817196],"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":[0.00001974788,0.0003115725,0.01201403,0.0002345127,0.00004199541,0.0001901782,0.0006393098,0.0001670153,0.00000579131,0.007055849,0.9086095,0.0707105],"study_design_scores_gemma":[0.001473845,0.001929658,0.001111199,0.00003963988,0.00005449276,0.000380417,0.0005064614,0.1134144,0.00001023228,0.0002428097,0.8801125,0.000724384],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0153508,0.002141062,0.9345766,0.00008653836,0.02260023,0.002443797,0.000101653,0.000901915,0.02179744],"genre_scores_gemma":[0.9679644,0.0004189749,0.02535436,0.0001387665,0.001514478,0.0004886291,0.00002031095,0.00004061705,0.004059511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9526135,"threshold_uncertainty_score":0.9980358,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4322724432","doi":"10.1016/j.dss.2023.113944","title":"Evaluation of metaverse integration alternatives of sharing economy in transportation using fuzzy Schweizer-Sklar based ordinal priority approach","year":2023,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":77,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Sustainability; Rank (graph theory); Fuzzy logic; Knowledge management; Operations research; Artificial intelligence; Engineering; Ecology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1209038416567915,"gpt":0.3171502725747435,"spread":0.196246430917952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005502888,0.0001540884,0.00039428,0.0009969207,0.00005683297,0.00009981212,0.0002174035,0.00009121876,0.0001277449],"category_scores_gemma":[0.0001632413,0.000142661,0.0001116561,0.0007408014,0.00002509868,0.001666444,0.00002817636,0.00009555562,0.00004032599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008534818,"about_ca_system_score_gemma":0.00009339731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001212796,"about_ca_topic_score_gemma":0.0001200233,"domain_scores_codex":[0.9979857,0.00002458385,0.000931797,0.000339725,0.0005457782,0.0001724375],"domain_scores_gemma":[0.9984999,0.00008993242,0.000685077,0.0002561912,0.000455888,0.00001299453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003320685,0.0002932858,0.626619,0.001228953,0.000163095,0.00001366955,0.0008463415,0.3220181,0.001691092,0.01457659,0.0001906262,0.0320272],"study_design_scores_gemma":[0.001337497,0.00001075687,0.06326171,0.0002607711,0.0001330392,9.451851e-7,0.001467985,0.9283143,0.0003889028,0.004241668,0.0004080776,0.0001743481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977836,0.00002188292,0.01652328,0.000005711476,0.0003983041,0.0006165428,0.00001359475,0.0000402903,0.004544455],"genre_scores_gemma":[0.9988285,0.000001823735,0.0006609703,0.00001061983,0.0001212185,0.00003915425,0.0003061812,0.00001604977,0.00001549217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6062962,"threshold_uncertainty_score":0.5817545,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2412692381","doi":"10.1016/j.dss.2016.06.003","title":"A new dynamic integrated framework for surgical patients' prioritization considering risks and uncertainties","year":2016,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":66,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Centre for Interdisciplinary Research in Rehabilitation","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Regret; Prioritization; Analytic hierarchy process; Process (computing); Fuzzy logic; Hierarchy; Computer science; Operations research; Risk analysis (engineering); Operations management; Management science; Medicine; Engineering; Artificial intelligence; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.1383082204809855,"gpt":0.4252479379827924,"spread":0.2869397175018069,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004212896,0.0004206781,0.0009484583,0.0008243498,0.0003231323,0.001173627,0.0007854968,0.0004040416,0.0009849138],"category_scores_gemma":[0.0223507,0.0002468947,0.0002260552,0.0008674437,0.0001399286,0.0007464454,0.0003444071,0.0001780556,0.0003814704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001736248,"about_ca_system_score_gemma":0.0002615102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008104101,"about_ca_topic_score_gemma":0.00003219446,"domain_scores_codex":[0.9929925,0.0003526827,0.002339857,0.001301257,0.002420273,0.0005934907],"domain_scores_gemma":[0.9775751,0.0183707,0.0008181629,0.001147953,0.001595482,0.0004925895],"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":[0.0006666729,0.00005952075,0.05688721,0.00001851656,0.00003771084,0.00004769224,0.0004966646,0.00006697835,0.0001777196,0.006250291,0.02761752,0.9076735],"study_design_scores_gemma":[0.01110147,0.000653511,0.03178019,0.002050492,0.00006476638,0.0002626158,0.002537938,0.02574424,0.0001568016,0.1970345,0.7271689,0.001444545],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2542167,0.0002486519,0.7410898,0.0002026976,0.002924065,0.0009328792,0.000166456,0.0001095122,0.0001092634],"genre_scores_gemma":[0.9376817,0.0000559479,0.05906772,0.00006432628,0.0001913587,0.0000665585,0.00002286559,0.00005987532,0.002789662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.906229,"threshold_uncertainty_score":0.9999983,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2106898564","doi":"10.1016/s0167-9236(03)00099-x","title":"Decision station: situating decision support systems","year":2003,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Situated; Decision support system; Computer science; Domain (mathematical analysis); The Internet; Architecture; Decision analysis; R-CAST; Knowledge management; Process (computing); Set (abstract data type); Argument (complex analysis); Process management; Data science; Business decision mapping; Engineering; Data mining; Artificial intelligence; World Wide Web; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.03654265408552614,"gpt":0.2998481111881291,"spread":0.2633054571026029,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004800486,0.0006164151,0.001085539,0.0007027587,0.0006063716,0.001566331,0.002037741,0.0004109127,0.0002566321],"category_scores_gemma":[0.002350589,0.0005026234,0.0002991636,0.001330964,0.00007884752,0.001543476,0.000441145,0.0003372555,0.002726014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375775,"about_ca_system_score_gemma":0.000502426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001354894,"about_ca_topic_score_gemma":0.00003433762,"domain_scores_codex":[0.9918544,0.0004046608,0.002358669,0.001556572,0.002772578,0.001053107],"domain_scores_gemma":[0.9917867,0.003629037,0.0007851838,0.00250694,0.0007911531,0.0005009585],"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":[0.0002484185,0.0005973855,0.02282949,0.0002666934,0.0001871585,0.00251233,0.003503234,0.01015613,0.0009318926,0.1490572,0.3272313,0.4824788],"study_design_scores_gemma":[0.006272982,0.00163294,0.009834567,0.001861337,0.0001088358,0.005584457,0.006224499,0.160726,0.001224301,0.01954093,0.7838172,0.003171898],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05262625,0.0009995475,0.9229251,0.00005365062,0.01285903,0.0009247725,0.00001902042,0.0005312905,0.009061405],"genre_scores_gemma":[0.8896558,0.00009488848,0.1077824,0.0001809645,0.0002370038,0.0001059464,0.00002922647,0.00005876056,0.001855055],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8370295,"threshold_uncertainty_score":0.9997426,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2991582200","doi":"10.1016/j.dss.2019.113224","title":"A decision support system for home dialysis visit scheduling and nurse routing","year":2019,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Ottawa Hospital; Wilfrid Laurier University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Telfer School of Management, University of Ottawa","keywords":"Workload; Medicine; Dialysis; Nursing; Overtime; Decision support system; Workflow; Operations management; Medical emergency; Computer science; Internal medicine; Database; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01200563089369737,"gpt":0.2554885920733547,"spread":0.2434829611796573,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001119657,0.0003009141,0.0006364567,0.0004354082,0.0001544597,0.0002016714,0.0002142071,0.0002221095,0.0001521526],"category_scores_gemma":[0.00007744927,0.0002888028,0.0001810609,0.0005554016,0.00002158316,0.0003568197,0.00001831995,0.000157785,0.0003776627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001384443,"about_ca_system_score_gemma":0.00005943868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001744537,"about_ca_topic_score_gemma":0.00001592238,"domain_scores_codex":[0.9972814,0.0000216505,0.001247025,0.0005074844,0.0005224345,0.0004200006],"domain_scores_gemma":[0.9982275,0.0005193735,0.000155514,0.0005994465,0.0003030741,0.0001950662],"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":[0.001103602,0.0004750305,0.2307644,0.007282905,0.001651166,0.0001698785,0.0117532,0.345682,0.03553234,0.05296466,0.01710849,0.2955123],"study_design_scores_gemma":[0.01037572,0.0005461872,0.03447357,0.002330826,0.0005442207,0.000365489,0.01522073,0.8477258,0.001998472,0.0003741745,0.08342799,0.002616826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6159422,0.00009733123,0.378668,0.00001554445,0.002734272,0.001018381,0.0001415827,0.000449816,0.0009328537],"genre_scores_gemma":[0.9906131,0.0000127932,0.008386517,0.00002390933,0.0001353391,0.000159769,0.0002070908,0.00007621762,0.0003852731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5020438,"threshold_uncertainty_score":0.9999564,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1972932886","doi":"10.1016/j.dss.2012.05.050","title":"Dominance-based rough set approach for groups in multicriteria classification problems","year":2012,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Decision rule; Decision maker; Veto; Group decision-making; Dominance-based rough set approach; Dominance (genetics); Computer science; Decision analysis; Rough set; Set (abstract data type); Preference; Decision support system; Artificial intelligence; Data mining; Decision tree; Machine learning; Operations research; Mathematics; Mathematical economics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.09056001981553732,"gpt":0.3066961614931809,"spread":0.2161361416776435,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002123013,0.0002265316,0.0003970181,0.0002222854,0.0001175226,0.0002691785,0.0007983384,0.0001766898,0.000008137044],"category_scores_gemma":[0.00008976677,0.0001788125,0.000110974,0.0004990314,0.00003010479,0.0008364159,0.00009933262,0.0001106032,0.00008082211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001144802,"about_ca_system_score_gemma":0.0000663294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003708339,"about_ca_topic_score_gemma":0.000002530016,"domain_scores_codex":[0.9974682,0.0001234626,0.0007913867,0.0005688629,0.0004508274,0.0005972846],"domain_scores_gemma":[0.9982661,0.0002881976,0.0002651691,0.0008964654,0.0001202922,0.0001637736],"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":[0.0008689563,0.006730314,0.166054,0.00260632,0.0001195067,0.00006872816,0.02436831,0.02687509,0.006351222,0.1735046,0.1594386,0.4330144],"study_design_scores_gemma":[0.001952712,0.0001541699,0.01624308,0.00008852118,0.000007159184,0.0000382551,0.0002271805,0.9208952,0.00006571243,0.0005101641,0.05940285,0.0004150058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01346096,0.000282587,0.9814957,0.00009428743,0.001614426,0.001509523,0.00002739932,0.0001024256,0.001412653],"genre_scores_gemma":[0.8304915,0.000006503299,0.1683817,0.00009596072,0.0001793231,0.0006432716,0.00009950653,0.00001785067,0.00008433379],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8940201,"threshold_uncertainty_score":0.7291763,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1964390465","doi":"10.1016/j.dss.2007.12.017","title":"Screening in multiple criteria decision analysis","year":2008,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Multiple-criteria decision analysis; Preference; Set (abstract data type); Computer science; Decision analysis; Process (computing); Decision process; Decision support system; Data mining; Operations research; Mathematics; Management science; Engineering; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.2601201774639123,"gpt":0.4353605905976103,"spread":0.175240413133698,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01519299,0.0007637192,0.002516353,0.007701548,0.0007526771,0.001249986,0.003295319,0.0005278282,0.006224331],"category_scores_gemma":[0.01991911,0.0006006251,0.001096911,0.01004317,0.0002364651,0.001627002,0.001065169,0.0005533446,0.004017848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001739742,"about_ca_system_score_gemma":0.0002037315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004860899,"about_ca_topic_score_gemma":0.0003926506,"domain_scores_codex":[0.9807636,0.001090263,0.005934403,0.002702894,0.008249229,0.001259589],"domain_scores_gemma":[0.9765399,0.01621296,0.001266258,0.003930439,0.001294585,0.0007558268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009160893,0.0003210985,0.7579237,0.000007613548,0.0001868481,0.002442213,0.001683092,0.01656057,0.0008382516,0.0001263814,0.07398155,0.1450126],"study_design_scores_gemma":[0.003455094,0.0001232974,0.5234383,0.0002009435,0.00009637649,0.0005937428,0.001434683,0.3452197,0.00009657583,0.001917465,0.1223659,0.001057933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5426373,0.0002645006,0.4527175,0.00004149898,0.002250107,0.0005694599,0.00008994219,0.000123563,0.001306206],"genre_scores_gemma":[0.9465957,0.00004077757,0.05047631,0.000215533,0.0002747411,0.00008170534,0.00004805053,0.00007931512,0.00218788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4039584,"threshold_uncertainty_score":0.9997868,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3010728474","doi":"10.1016/j.dss.2020.113281","title":"Revealed preference in online reviews: Purchase verification in the tablet market","year":2020,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Purchasing; Preference; Product (mathematics); Advertising; Profiling (computer programming); Marketing; Business; Computer science; Economics; Microeconomics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1320071606586539,"gpt":0.3518918226252769,"spread":0.2198846619666229,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006983663,0.000116851,0.000348869,0.00007768444,0.0001213045,0.0001775731,0.0005784563,0.0001168081,0.0001958283],"category_scores_gemma":[0.008543685,0.00008660713,0.00006002968,0.001016359,0.00007926843,0.000239421,0.00003876052,0.0002183695,0.000156063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008262008,"about_ca_system_score_gemma":0.0001719821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00069874,"about_ca_topic_score_gemma":0.0007991948,"domain_scores_codex":[0.9966369,0.001294052,0.0007326616,0.0003199035,0.0007147728,0.0003017503],"domain_scores_gemma":[0.9984208,0.0008892532,0.0002021446,0.0002698373,0.00007511091,0.000142877],"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":[0.0004797952,0.0006427383,0.0793739,0.0003341255,0.00001167228,0.0002860286,0.1289871,0.00001696096,0.00005779314,0.005001946,0.4477145,0.3370935],"study_design_scores_gemma":[0.000352476,0.00005024878,0.02148239,0.0003356579,0.00000430154,0.000001296448,0.01877132,0.0001879871,3.190904e-7,0.0003025358,0.9583637,0.0001478281],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6679056,0.003302277,0.0006790833,0.01306457,0.002227627,0.005100371,0.0001606249,0.000172876,0.307387],"genre_scores_gemma":[0.9962178,0.001092384,0.0001220271,0.000718842,0.0003385461,0.0001196377,0.00003769895,0.000009684149,0.001343401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5106491,"threshold_uncertainty_score":0.9998078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1964271741","doi":"10.1016/j.dss.2007.04.003","title":"A temporal approach to expectations and desires from knowledge management systems","year":2007,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":46,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University; York University","funders":"","keywords":"Perception; Product (mathematics); Foundation (evidence); Realization (probability); Knowledge management; Business; Psychology; Computer science; Political science; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.2560177653132057,"gpt":0.4309712288629836,"spread":0.1749534635497779,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004776821,0.0002939792,0.0005233837,0.001348212,0.0003385074,0.001371211,0.0008875408,0.000120685,0.00009732784],"category_scores_gemma":[0.0002050746,0.0002232753,0.0001237736,0.001330583,0.00005298711,0.0007844677,0.000390123,0.0001099909,0.002928825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009565578,"about_ca_system_score_gemma":0.00003223323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001367385,"about_ca_topic_score_gemma":0.00003335574,"domain_scores_codex":[0.9947081,0.0001300189,0.001777321,0.0007676352,0.002156398,0.0004605238],"domain_scores_gemma":[0.99695,0.0009242066,0.0003684897,0.0008751566,0.0004021064,0.0004799986],"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":[0.0004844538,0.0008010148,0.105107,0.0001259256,0.0002456588,0.0002214949,0.02705937,0.0006002692,0.00009671602,0.06276251,0.5946791,0.2078165],"study_design_scores_gemma":[0.001706565,0.0001538544,0.1460138,0.0001748331,0.00009744258,0.00005974599,0.2085115,0.01354557,0.00002315612,0.0006899927,0.6280959,0.0009276426],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4129943,0.0007716384,0.4609694,0.000044562,0.002494455,0.001832803,0.0001018199,0.0001791012,0.1206119],"genre_scores_gemma":[0.9791383,0.000005647027,0.007708426,0.0000698662,0.000187671,0.0001450692,0.00007177442,0.0000224828,0.01265076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.566144,"threshold_uncertainty_score":0.9996654,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1973206570","doi":"10.1016/j.dss.2007.05.006","title":"Website browsing aid: A navigation graph-based recommendation system","year":2007,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; University of Washington","keywords":"Computer science; Recommender system; Information overload; Graph; World Wide Web; Navigation system; Information retrieval; Real-time computing","retraction":null,"screen_n_in":null,"score":{"opus":0.02553002171818773,"gpt":0.291850017953823,"spread":0.2663199962356352,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005096423,0.0003197778,0.0004859633,0.000710035,0.0003384393,0.0006735127,0.0008474056,0.0002468315,0.0000230354],"category_scores_gemma":[0.00003675853,0.0002864633,0.0001984938,0.001058304,0.00002377345,0.0009945361,0.0001480038,0.0002152666,0.0002568454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003361115,"about_ca_system_score_gemma":0.00009908171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002516806,"about_ca_topic_score_gemma":0.00001690265,"domain_scores_codex":[0.9962051,0.0002107806,0.001435148,0.0007688715,0.0008280309,0.0005520482],"domain_scores_gemma":[0.9972243,0.0004363184,0.0006625485,0.001071623,0.0003461215,0.0002590402],"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":[0.0001827998,0.0004025298,0.01866673,0.001039435,0.000148887,0.0006494864,0.001412221,0.0002881425,0.004046827,0.08912651,0.1019211,0.7821153],"study_design_scores_gemma":[0.003797352,0.0008260941,0.004641398,0.003505667,0.00005001386,0.001954466,0.001549189,0.2168606,0.0125926,0.001671356,0.7504327,0.002118541],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008169655,0.00008148891,0.9776292,0.0001448553,0.00378953,0.0007554896,0.00001026811,0.001190611,0.008228933],"genre_scores_gemma":[0.9503499,0.000002710236,0.04895471,0.0001355734,0.0002189435,0.00006035306,0.00008332317,0.0000339675,0.000160482],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9421803,"threshold_uncertainty_score":0.9999588,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3122905330","doi":"10.1016/j.dss.2012.11.006","title":"Experience information goods: “Version-to-upgrade”","year":2012,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Fudan University; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Upgrade; Quality (philosophy); Information good; Pessimism; Business; Economics; Marketing; Microeconomics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02238065264387502,"gpt":0.2334440364292036,"spread":0.2110633837853286,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0004388054,0.0001446917,0.0001932565,0.0002907543,0.0001347995,0.00117133,0.0002499113,0.000068176,0.0003958155],"category_scores_gemma":[0.0001221371,0.0001204314,0.00006770887,0.0002940355,0.00001320208,0.02039065,0.00019514,0.00005132821,0.02743642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000447846,"about_ca_system_score_gemma":0.000009787257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001308394,"about_ca_topic_score_gemma":0.00000300501,"domain_scores_codex":[0.9987011,6.017475e-7,0.0005064855,0.0001317225,0.0002953894,0.0003647058],"domain_scores_gemma":[0.9993336,0.0000344334,0.0002062693,0.0002851122,0.00007972777,0.00006081665],"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":[0.0001514036,0.0001705481,0.1298522,0.0002019227,0.00003364216,0.000007883592,0.001693134,0.000596977,0.00004701967,0.07590129,0.7029374,0.08840659],"study_design_scores_gemma":[0.0002083882,0.000007606798,0.004958536,0.0000326992,0.000004829355,0.000009249514,0.003874249,0.0009355713,0.000007619551,0.0002828512,0.9894698,0.0002086413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8876588,0.000017724,0.003438817,0.00003677901,0.003583568,0.0002971493,0.000007134042,0.0001050872,0.104855],"genre_scores_gemma":[0.9971885,0.000001756523,0.0001502501,0.001416317,0.0007345483,0.00002817897,0.00007969436,0.0000127578,0.0003879791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2865324,"threshold_uncertainty_score":0.9998655,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1995467602","doi":"10.1016/j.dss.2015.01.010","title":"A decision support framework to implement optimal personalized marketing interventions","year":2015,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Bank of Canada","funders":"Institució Catalana de Recerca i Estudis Avançats; Royal Bank of Canada","keywords":"Psychological intervention; Process management; Personalized marketing; Computer science; Decision support system; Marketing; Knowledge management; Business; Marketing management; Psychology; Artificial intelligence; Return on marketing investment","retraction":null,"screen_n_in":null,"score":{"opus":0.07898619194351643,"gpt":0.3499915306290801,"spread":0.2710053386855636,"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":[0.007330583,0.0004398581,0.0006926812,0.0009250145,0.0003470518,0.001203566,0.0007156419,0.0001871419,0.006502257],"category_scores_gemma":[0.002337161,0.0004016881,0.0004842421,0.001112311,0.00003395006,0.0009191115,0.0009226197,0.0003042202,0.003754104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001553129,"about_ca_system_score_gemma":0.0001237681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003992387,"about_ca_topic_score_gemma":0.00008306904,"domain_scores_codex":[0.9952974,0.00009087555,0.00153963,0.0008197355,0.001489535,0.0007628071],"domain_scores_gemma":[0.9970072,0.0007441749,0.0004826385,0.000826738,0.000728447,0.0002107901],"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":[0.002118542,0.0003785826,0.1447974,0.0004040001,0.0001238947,0.0004198306,0.0008117751,0.0002124304,0.00009771873,0.00314552,0.5423238,0.3051666],"study_design_scores_gemma":[0.001849128,0.00009063885,0.019341,0.001412156,0.000220646,0.00008988057,0.003863544,0.001697134,0.000004520711,0.0004602793,0.9702036,0.0007675159],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5889493,0.0004380945,0.3797861,0.0006069383,0.00956671,0.002199216,0.00006175006,0.0005299529,0.01786187],"genre_scores_gemma":[0.979576,0.000009280518,0.01500606,0.0008405343,0.001196595,0.0002306582,0.0001378228,0.0001044613,0.002898572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4278798,"threshold_uncertainty_score":0.9998435,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2020506644","doi":"10.1016/j.dss.2009.06.012","title":"Visual e-mail authentication and identification services: An investigation of the effects on e-mail use","year":2009,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"U.S. Department of Defense; National Science Foundation","keywords":"Phishing; Identification (biology); Context (archaeology); Authentication (law); Service (business); Cognition; Electronic mail; Psychology; Internet privacy; Need for cognition; Computer science; Social psychology; Applied psychology; Computer security; Business; Marketing; The Internet; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.05885637285492306,"gpt":0.3662317537101976,"spread":0.3073753808552745,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003043648,0.0001931116,0.000332102,0.0005035153,0.0002555625,0.0004373562,0.0007683286,0.0002656348,0.00003698485],"category_scores_gemma":[0.001000485,0.0001242313,0.00009343754,0.0009428449,0.0001169787,0.0009257072,0.00008109424,0.0001752013,0.000198239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004178867,"about_ca_system_score_gemma":0.00005242643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003029752,"about_ca_topic_score_gemma":0.00002004757,"domain_scores_codex":[0.9958399,0.0004578658,0.001199829,0.0006417261,0.001667111,0.0001935499],"domain_scores_gemma":[0.9962053,0.0009328168,0.0008512993,0.001331358,0.0005288136,0.0001503565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001902387,0.000334152,0.7414678,0.00005315872,0.0000208708,0.000009761327,0.003685375,0.00006004548,0.08903842,0.01073676,0.00626446,0.1481389],"study_design_scores_gemma":[0.0004241409,0.0002979182,0.9815301,0.0001314962,0.00002781706,0.00002311019,0.0006873029,0.002510632,0.00519189,0.007609889,0.001420866,0.0001448653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994918,0.00003220649,0.002898236,0.0003510654,0.00103222,0.0006132252,0.00001600744,0.00009808542,0.0000408883],"genre_scores_gemma":[0.9984871,0.000007807877,0.0002143142,0.0003292662,0.0000435567,0.00002144924,0.00002338234,0.00001157871,0.0008616067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2400623,"threshold_uncertainty_score":0.5066005,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1976617111","doi":"10.1016/j.dss.2014.06.006","title":"Filtering trust opinions through reinforcement learning","year":2014,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Access Control and Trust","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"National Research Foundation","keywords":"Reinforcement learning; Trustworthiness; Computer science; Outcome (game theory); Accountability; Key (lock); Order (exchange); Intervention (counseling); Mechanism (biology); Cognitive psychology; Computer security; Artificial intelligence; Psychology; Business; Microeconomics; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.03777623411525292,"gpt":0.3354713864031502,"spread":0.2976951522878972,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001497694,0.0001361211,0.0002865208,0.00007545229,0.0009549183,0.0003059659,0.00038326,0.0001183839,0.001180928],"category_scores_gemma":[0.0005757512,0.0001176025,0.0001052389,0.0002260017,0.00007962844,0.000470984,0.00009747007,0.0001579637,0.0009066846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007219799,"about_ca_system_score_gemma":0.00008289683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001762156,"about_ca_topic_score_gemma":0.0000859767,"domain_scores_codex":[0.9978336,0.0001959027,0.0004952464,0.0002879215,0.0007699407,0.0004173573],"domain_scores_gemma":[0.9988502,0.0003829101,0.0001977317,0.0002861845,0.0001204798,0.0001624809],"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":[0.0001700499,0.000136608,0.05709526,0.0001126332,0.0001720807,0.00006480988,0.03454718,0.03166474,0.0002069367,0.6287796,0.08635966,0.1606905],"study_design_scores_gemma":[0.0004119451,0.00006103107,0.0007002251,0.00005793253,0.000008501457,0.000003624108,0.003006125,0.004027903,0.000008647946,0.0004764937,0.991072,0.0001655856],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01327779,0.0001049088,0.4172083,0.0004924799,0.00415858,0.0005592586,0.000004694684,0.00031232,0.5638817],"genre_scores_gemma":[0.9862962,0.00004391208,0.000330884,0.0001182357,0.000776006,0.00004755535,0.00002584107,0.0000163722,0.01234496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9730184,"threshold_uncertainty_score":0.9998713,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997408825","doi":"10.1016/j.dss.2009.04.010","title":"A model-based DSS for integrating the impact of learning in project control","year":2009,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":42,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Earned value management; Control (management); Decision support system; Project management; Engineering management; Systems engineering; Project portfolio management; Data mining; Artificial intelligence; Engineering; OPM3","retraction":null,"screen_n_in":null,"score":{"opus":0.05576027937582548,"gpt":0.3651494029902846,"spread":0.3093891236144591,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002249881,0.0002021896,0.0004393649,0.0004828818,0.0001417278,0.0002851318,0.0002595077,0.00006736916,0.00004500979],"category_scores_gemma":[0.000655324,0.0001200397,0.0002540683,0.0005425768,0.00001759493,0.0005323362,0.00001696149,0.0001354879,0.00001964901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008318673,"about_ca_system_score_gemma":0.0001713019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00109525,"about_ca_topic_score_gemma":0.0000658045,"domain_scores_codex":[0.9980873,0.00004588719,0.0009343054,0.0002348791,0.0003694401,0.0003282276],"domain_scores_gemma":[0.9984422,0.0003491309,0.0006532994,0.0002544017,0.0002862401,0.00001469141],"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":[0.002258933,0.0006133654,0.3126416,0.0006150054,0.0001805102,0.00002184553,0.002086989,0.453835,0.007776845,0.01330901,0.1183989,0.08826201],"study_design_scores_gemma":[0.002814444,0.000166524,0.009366457,0.0002199359,0.00002051613,0.000003608655,0.001794671,0.9815193,0.000011751,0.0002751398,0.003636151,0.0001714595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5514862,0.00008315164,0.4358675,0.0003958341,0.0004699435,0.004435685,0.00004254231,0.0001495468,0.00706959],"genre_scores_gemma":[0.9989553,5.446429e-7,0.0002085468,0.0002966358,0.0002252875,0.0000968887,0.00004277927,0.00002185555,0.0001521252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5276844,"threshold_uncertainty_score":0.4895078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2029168398","doi":"10.1016/j.dss.2015.02.016","title":"Getting the most out of third party trust seals: An empirical analysis","year":2015,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Business; Exploit; Value (mathematics); Third party; Seal (emblem); Marketing; Empirical evidence; Advertising; Internet privacy; Computer security; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.2514834593939663,"gpt":0.4545668100572395,"spread":0.2030833506632732,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01435902,0.0002527904,0.000932943,0.0009384055,0.0002455901,0.0003481246,0.002019486,0.0003660777,0.0004616853],"category_scores_gemma":[0.004205464,0.0001387398,0.0003616411,0.002857323,0.000246446,0.0004547607,0.0003375035,0.0003483387,0.001013478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006027538,"about_ca_system_score_gemma":0.0002506588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008582999,"about_ca_topic_score_gemma":0.0001432544,"domain_scores_codex":[0.9926139,0.0007530627,0.002131722,0.0008055132,0.003286373,0.0004095032],"domain_scores_gemma":[0.993481,0.001402788,0.0009402056,0.002444637,0.001320109,0.0004112813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005926677,0.0001342661,0.8323475,0.000001503147,0.00008843862,0.00003655873,0.00215711,0.0005743561,0.00004897332,0.0003693478,0.154506,0.009676704],"study_design_scores_gemma":[0.001441329,0.0004618673,0.4847506,0.00003073583,0.0005440597,0.0001108807,0.04068714,0.03586954,0.0001621036,0.005264878,0.4300416,0.0006352985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626253,0.0001458425,0.03110833,0.001131081,0.001652176,0.0003477812,0.00008154225,0.0001692298,0.002738715],"genre_scores_gemma":[0.9953042,0.000003964893,0.0008982848,0.000306077,0.0001062459,0.00002599262,0.00002314903,0.00001695567,0.003315191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3475969,"threshold_uncertainty_score":0.9997643,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980367442","doi":"10.1016/j.dss.2014.06.009","title":"An experimental study of software agent negotiations with humans","year":2014,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Negotiation; Individualism; Software agent; Set (abstract data type); Computer science; Software; Product (mathematics); Process (computing); Knowledge management; Process management; Risk analysis (engineering); Business; Artificial intelligence; Political science; Law; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03383335041847852,"gpt":0.3051997118098388,"spread":0.2713663613913603,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007676447,0.0001965813,0.0003758568,0.0002259571,0.000209801,0.0001934437,0.000752289,0.00006513382,0.00005222124],"category_scores_gemma":[0.00003045863,0.0001491453,0.00005695778,0.0003159991,0.00001803903,0.0006498826,0.00009820594,0.00006779576,0.00009281396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005428777,"about_ca_system_score_gemma":0.00004563768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002678811,"about_ca_topic_score_gemma":0.00007422209,"domain_scores_codex":[0.9972633,0.0002518249,0.0007355336,0.0005550444,0.0009677406,0.0002266045],"domain_scores_gemma":[0.9977961,0.0001359367,0.0004077325,0.001282286,0.0002078999,0.0001700927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002855517,0.0253725,0.6994324,0.0003079647,0.0004597098,0.0001912724,0.1350871,0.03768897,0.02244956,0.02617662,0.02106259,0.03148578],"study_design_scores_gemma":[0.02230439,0.04050149,0.4589866,0.0009262061,0.0001806057,0.0003709616,0.04671938,0.3732046,0.01134413,0.0002277038,0.04152776,0.003706199],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5116024,0.00002054223,0.4869544,0.000003948752,0.0006142778,0.000530312,0.000003057993,0.00009399842,0.0001770617],"genre_scores_gemma":[0.9943666,5.522048e-7,0.005217908,0.00002309723,0.00009952061,0.00009029999,0.00001362293,0.00001909931,0.0001693063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4827642,"threshold_uncertainty_score":0.6081967,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2116163414","doi":"10.1016/s0167-9236(02)00194-x","title":"Consulting past exceptions to facilitate workflow exception handling","year":2003,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":36,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"National Science Council","keywords":"Workflow; Exception handling; Computer science; Context (archaeology); Similarity (geometry); Data mining; Database; Programming language; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.06729195778960602,"gpt":0.263674913389163,"spread":0.196382955599557,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001460336,0.0003037248,0.0004716202,0.0007327651,0.0005565762,0.0008992729,0.0002634726,0.0001273073,0.0006089009],"category_scores_gemma":[0.0006379773,0.0002728504,0.0001730418,0.001565821,0.00003230844,0.0009410465,0.00009047944,0.00015305,0.004511309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000487729,"about_ca_system_score_gemma":0.00003692397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000265541,"about_ca_topic_score_gemma":0.00003221502,"domain_scores_codex":[0.9973289,0.00002772089,0.0008665565,0.0006305559,0.0006537393,0.0004924686],"domain_scores_gemma":[0.9982703,0.0001199141,0.0002985186,0.0004722118,0.0007782209,0.00006078043],"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":[0.0002967905,0.0006806065,0.2461339,0.001287792,0.0003418697,0.0001651706,0.001639542,0.2517065,0.004539787,0.01164959,0.1056546,0.375904],"study_design_scores_gemma":[0.002223296,0.00003058555,0.005206492,0.001218685,0.0003099696,0.00004861417,0.00374042,0.07458862,0.00003437836,0.005033002,0.9058152,0.001750684],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3139453,0.0001320496,0.6756176,0.0002152166,0.001521438,0.0003676148,0.000008918329,0.0003060837,0.00788573],"genre_scores_gemma":[0.9944897,0.000009612656,0.00168878,0.0004704764,0.0008475526,0.00008866974,0.00006378706,0.00004518762,0.00229623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8001607,"threshold_uncertainty_score":0.9999723,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2000653600","doi":"10.1016/j.dss.2014.11.009","title":"The moderating effects of keyword competition on the determinants of ad position in sponsored search advertising","year":2014,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Competition (biology); Popularity; Advertising; Position (finance); Search advertising; Business; Keyword search; Empirical research; Online advertising; Channel (broadcasting); The Internet; Marketing; Economics; Computer science; Psychology; Information retrieval; Telecommunications; World Wide Web; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.01809019439162445,"gpt":0.2664245896500357,"spread":0.2483343952584113,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002651868,0.000124916,0.0002697734,0.0002188064,0.0002432611,0.0001486683,0.0002321674,0.00005465168,0.00002289368],"category_scores_gemma":[0.0004965825,0.00007650421,0.00007495593,0.000334796,0.00004705506,0.0002378085,0.00009628024,0.0001238608,0.00002491899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002135199,"about_ca_system_score_gemma":0.00001573248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003129138,"about_ca_topic_score_gemma":0.000135833,"domain_scores_codex":[0.9983422,0.0001554285,0.0006123183,0.0001863848,0.0005014152,0.0002023025],"domain_scores_gemma":[0.9969828,0.002191128,0.0003084769,0.0003448083,0.0001635662,0.000009263574],"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":[0.00107618,0.0002316885,0.4264098,0.001218051,0.00002696592,0.00004565426,0.0006149729,0.0008353383,0.01983197,0.007467829,0.0004924877,0.5417491],"study_design_scores_gemma":[0.001886476,0.00013851,0.7038088,0.005147666,0.00009166048,0.00002143076,0.001120595,0.2780567,0.005454493,0.0009220362,0.002941077,0.0004105097],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953218,0.0000593093,0.001987689,0.00006148637,0.0004771666,0.0004873858,0.000001270023,0.00001596027,0.001587961],"genre_scores_gemma":[0.9997448,0.000008382905,0.00002828621,0.0000538508,0.00006987947,0.00002180728,0.000005742533,0.00001534884,0.00005193288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5413386,"threshold_uncertainty_score":0.3119751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396520848","doi":"10.1016/j.dss.2024.114236","title":"Transparency in design science research","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Information Systems Theories and Implementation","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Transparency (behavior); Openness to experience; Design science research; Computer science; Space (punctuation); Process (computing); Open science; Management science; Data science; Engineering ethics; Political science; Engineering; Information system; Computer security; Psychology; Mathematics; Law; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.245152589560831,"gpt":0.5202787027126053,"spread":0.2751261131517743,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0279676,0.00007545094,0.0001436812,0.001010292,0.000786376,0.001024257,0.0004352664,0.00007089348,0.0006504933],"category_scores_gemma":[0.0004326022,0.00006476,0.00003473412,0.003032291,0.0003567321,0.001463806,0.00003135796,0.0001554312,0.001183376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004386241,"about_ca_system_score_gemma":0.001322224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001824431,"about_ca_topic_score_gemma":0.0002224081,"domain_scores_codex":[0.9959575,0.0004470754,0.0006906778,0.0002772434,0.00208896,0.000538556],"domain_scores_gemma":[0.998467,0.000738429,0.0000462236,0.0002133792,0.0003966889,0.0001383265],"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":[0.00003599308,0.00002363743,0.000924662,0.0000831875,0.000005671822,0.00005165676,0.1401437,0.0001681676,0.0003273957,0.7520992,0.03562608,0.07051072],"study_design_scores_gemma":[0.0002210185,0.00009005814,0.0005400545,0.0003147878,0.000002238478,0.00001104044,0.08557891,0.002482873,0.0001241684,0.005998455,0.9044697,0.0001667461],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08718657,0.001180722,0.4327336,0.001030644,0.01489414,0.004335091,0.0000509588,0.0004579982,0.4581303],"genre_scores_gemma":[0.9970158,0.00006577811,0.0003516346,0.00001560578,0.0001953829,0.00009487295,0.000004555053,0.000008110324,0.002248271],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9098292,"threshold_uncertainty_score":0.9995943,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975045544","doi":"10.1016/j.dss.2006.08.003","title":"Maintaining robust decision capabilities: An integrative human–systems approach","year":2006,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Bishop's University; HEC Montréal","funders":"HEC Montréal; Universiteit Antwerpen; Memorial University of Newfoundland","keywords":"Multidisciplinary approach; Computer science; Risk analysis (engineering); Resource (disambiguation); Process management; Management science; Decision support system; Knowledge management; Artificial intelligence; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1184158006361843,"gpt":0.3772495444537616,"spread":0.2588337438175773,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0202072,0.001228002,0.002826244,0.002590488,0.001651447,0.005639401,0.003925413,0.0007058292,0.001559637],"category_scores_gemma":[0.003652493,0.0008398509,0.0008626003,0.003047939,0.0003809708,0.002230561,0.0008567013,0.0007970434,0.001912255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006065338,"about_ca_system_score_gemma":0.0003735553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003673457,"about_ca_topic_score_gemma":0.0004706583,"domain_scores_codex":[0.9763975,0.00185835,0.007368215,0.003501663,0.009301897,0.001572429],"domain_scores_gemma":[0.9802579,0.008993106,0.002305981,0.004792062,0.00277856,0.0008724158],"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":[0.0005575602,0.001052777,0.02057361,0.00005948226,0.00009996249,0.0004536384,0.00343575,0.2604747,0.0007334459,0.2950729,0.3941008,0.02338541],"study_design_scores_gemma":[0.003866036,0.001184258,0.008515864,0.0009927202,0.00007216695,0.001885652,0.09091528,0.3603682,0.00003079534,0.1074604,0.4219459,0.002762764],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.200445,0.001459662,0.7105039,0.00001678693,0.005992663,0.00198434,0.0001953445,0.0004447291,0.07895752],"genre_scores_gemma":[0.9659827,0.000003744434,0.01189675,0.00006408073,0.001958573,0.0002945153,0.0001065314,0.0001570933,0.01953598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7655377,"threshold_uncertainty_score":0.9996483,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2286179031","doi":"10.1016/j.dss.2016.02.003","title":"A framework based on hidden Markov model with adaptive weighting for microcystin forecasting and early-warning","year":2016,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"National Research Foundation Singapore","keywords":"Weighting; Computer science; Warning system; Machine learning; Hidden Markov model; Artificial intelligence; Artificial neural network; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.03871776234724431,"gpt":0.2534854039126438,"spread":0.2147676415653995,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001247981,0.0002965134,0.000387113,0.00009051363,0.000355168,0.00009751907,0.0002506923,0.0002001922,0.0001480229],"category_scores_gemma":[0.0008380968,0.0001717671,0.00007426688,0.0002067801,0.0001570217,0.0001762902,0.0001523701,0.0001784747,0.0001054106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001753091,"about_ca_system_score_gemma":0.00002600639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004632535,"about_ca_topic_score_gemma":0.000005553378,"domain_scores_codex":[0.9974581,0.00008070525,0.0005001778,0.0007886094,0.0006002453,0.0005721885],"domain_scores_gemma":[0.9968013,0.002249476,0.0003213674,0.0003578505,0.00003827142,0.0002317731],"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":[0.004643261,0.0002549328,0.2145116,0.0001082229,0.0000720087,0.0002695528,0.001591897,0.1480537,0.00949729,0.0003466848,0.006036133,0.6146147],"study_design_scores_gemma":[0.00118295,0.001147054,0.001658435,0.001355204,0.00002627204,0.00007514007,0.00003866096,0.9914203,0.0002471408,0.001088414,0.001316691,0.0004436835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5569933,0.00000722466,0.441124,0.00007822584,0.00008804359,0.0004207119,0.00001742769,0.00007048538,0.001200595],"genre_scores_gemma":[0.8086271,5.378321e-7,0.190525,0.0001100975,0.00006294348,0.0000849533,0.000001850444,0.00004410471,0.0005434288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8433667,"threshold_uncertainty_score":0.700446,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2049302341","doi":"10.1016/j.dss.2014.01.009","title":"Yes we can: Improving performance in dynamic tasks","year":2014,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Facilitation; Task (project management); Heuristics; Facilitator; Computer science; Dynamic decision-making; Cognitive psychology; Psychology; Artificial intelligence; Social psychology; Engineering; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.06558574568201868,"gpt":0.3541939430634403,"spread":0.2886081973814216,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01232719,0.0004646922,0.001261419,0.001694563,0.0003462553,0.001169435,0.002018174,0.0002697037,0.0006865157],"category_scores_gemma":[0.003910358,0.0003358641,0.0002872367,0.002029896,0.00008930115,0.0006609664,0.0005931957,0.0003887015,0.002887724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185838,"about_ca_system_score_gemma":0.0001980441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002888111,"about_ca_topic_score_gemma":0.0006769332,"domain_scores_codex":[0.9895647,0.0005531364,0.00337322,0.001480189,0.004167241,0.000861477],"domain_scores_gemma":[0.9914395,0.004265082,0.0009848578,0.002338826,0.0005932147,0.0003785247],"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":[0.0001758064,0.0001220144,0.07502972,0.00008057875,0.00001714978,0.0001292207,0.001536052,0.00593265,0.000744455,0.004702303,0.03826717,0.8732629],"study_design_scores_gemma":[0.001422643,0.0002571802,0.05507717,0.0004439081,0.000008551222,0.0003187142,0.002063656,0.4299785,0.00002463507,0.006934123,0.5027455,0.0007254078],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7765198,0.001626357,0.1891595,0.0004308691,0.009583312,0.001300199,0.00005921131,0.0002497542,0.0210711],"genre_scores_gemma":[0.9898175,0.00001651393,0.001181303,0.0001291217,0.0002409546,0.00006284396,0.000005038569,0.00005108969,0.008495647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8725375,"threshold_uncertainty_score":0.9999093,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2074841635","doi":"10.1016/j.dss.2005.02.008","title":"The impact of intelligent decision support systems on intellectual task success: An empirical investigation","year":2005,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Task (project management); Outcome (game theory); Test (biology); Computer science; Empirical research; Knowledge management; Decision support system; Intelligent decision support system; Structural equation modeling; Causal model; Applied psychology; Psychology; Artificial intelligence; Engineering; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.1353123363228054,"gpt":0.4348823590853221,"spread":0.2995700227625167,"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":[0.01170265,0.0006368762,0.001193881,0.001560869,0.000673295,0.001044874,0.003083858,0.0007398966,0.001168866],"category_scores_gemma":[0.008064298,0.0003577537,0.0006351011,0.00226699,0.0005423282,0.0009591536,0.0004098413,0.0007500695,0.00446187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004926786,"about_ca_system_score_gemma":0.0006402109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000207007,"about_ca_topic_score_gemma":0.00009596204,"domain_scores_codex":[0.9879851,0.0009927355,0.00423478,0.001425911,0.004518637,0.0008428749],"domain_scores_gemma":[0.9849911,0.008118751,0.00148824,0.003077633,0.001601148,0.0007231691],"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":[0.00131303,0.0007972986,0.2506184,0.00001042307,0.0001191097,0.0000870469,0.003725503,0.01400826,0.0007507621,0.001315941,0.4819629,0.2452913],"study_design_scores_gemma":[0.00426762,0.01012633,0.3017282,0.0007056319,0.000166853,0.002078217,0.01887885,0.1378085,0.002827732,0.007205129,0.5116776,0.002529367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514982,0.0002981522,0.04297039,0.0003098656,0.002712385,0.001079946,0.0001246293,0.0002454043,0.0007609917],"genre_scores_gemma":[0.9966381,0.00009824921,0.0005364716,0.0001137503,0.000311573,0.00008797469,0.00006173342,0.00006203562,0.002090118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2427619,"threshold_uncertainty_score":0.9999921,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2620631196","doi":"10.1016/j.dss.2017.05.016","title":"Location analytics and decision support: Reflections on recent advancements, a research framework, and the path ahead","year":2017,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Variety (cybernetics); Computer science; Implementation; Process (computing); Analytics; Digital transformation; Data science; Path (computing); Software engineering; World Wide Web; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.2407179183520798,"gpt":0.4449000028484378,"spread":0.204182084496358,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004114354,0.0002473703,0.000378365,0.000446224,0.001980883,0.002507079,0.000723443,0.0001891252,0.0002869531],"category_scores_gemma":[0.003588975,0.0001616161,0.00004821524,0.0006423047,0.0004285823,0.001347282,0.0006854435,0.0004419747,0.0006206653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006013989,"about_ca_system_score_gemma":0.0000623318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004415791,"about_ca_topic_score_gemma":0.0001655488,"domain_scores_codex":[0.996955,0.0000473745,0.0006783166,0.000674624,0.001212054,0.0004326465],"domain_scores_gemma":[0.9959674,0.0008744244,0.0004839199,0.001532273,0.00109117,0.00005078439],"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":[0.001695789,0.0002642646,0.01179931,0.0003392057,0.00006869283,0.00006022202,0.0002572576,0.0001370202,0.00003902946,0.1500393,0.09790675,0.7373932],"study_design_scores_gemma":[0.001244407,0.00007574697,0.01080424,0.001064213,0.00006251213,0.00003379762,0.0009140632,0.009021715,0.00001130297,0.04110631,0.9353339,0.0003278082],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1592048,0.004145513,0.7119097,0.01453761,0.01731528,0.006708837,0.0001153831,0.0003825911,0.08568037],"genre_scores_gemma":[0.9937773,0.002351962,0.001149984,0.0006866037,0.0009820785,0.00009442596,0.00005549687,0.00003740855,0.0008647458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8374271,"threshold_uncertainty_score":0.9993184,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200343312","doi":"10.1016/j.dss.2021.113713","title":"A machine learning investigation of factors that contribute to predicting cognitive performance: Difficulty level, reaction time and eye-movements","year":2021,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Russian Science Foundation; Russian Foundation for Basic Research","keywords":"Eye tracking; Task (project management); Computer science; Eye movement; Cognition; Artificial intelligence; Pupil size; Machine learning; Fixation (population genetics); Pupil; Cognitive psychology; Psychology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03898795988675024,"gpt":0.2724360636054454,"spread":0.2334481037186952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005715874,0.0001527132,0.0003155973,0.0001853061,0.0001760151,0.00009247755,0.0001807568,0.0001082409,0.000006021537],"category_scores_gemma":[0.0004410822,0.0001307005,0.00003906525,0.0004009019,0.00003778893,0.0003235866,0.000221141,0.0001863058,0.00002902448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004968202,"about_ca_system_score_gemma":0.00005545478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005416678,"about_ca_topic_score_gemma":0.000005403927,"domain_scores_codex":[0.9983948,0.0001069634,0.0004023717,0.0004277942,0.0004525481,0.0002155512],"domain_scores_gemma":[0.9987138,0.0003000257,0.00029437,0.0002172621,0.0003615638,0.0001129862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002565408,0.00004028915,0.8946605,0.00005360738,0.00005860692,0.00002579862,0.001226362,0.00003933548,0.0785081,0.00007939611,0.0001102983,0.02517199],"study_design_scores_gemma":[0.0008566561,0.0003101492,0.9277356,0.0006237319,0.00002022779,0.00005463237,0.000577843,0.02827549,0.04037305,0.00003280528,0.0009170523,0.0002227266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070597,0.0000583429,0.09208769,0.00004663312,0.0002860078,0.0001950902,0.00005166779,0.0001336741,0.00008122973],"genre_scores_gemma":[0.9982761,0.00001832366,0.0009755753,0.00002628784,0.00001601997,0.00001255979,0.0001091392,0.000009185801,0.0005568394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09121641,"threshold_uncertainty_score":0.5329812,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076041020","doi":"10.1016/j.dss.2004.02.001","title":"A relational database approach to a linear programming-based decision support system for production planning in secondary wood product manufacturing","year":2004,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Flexibility (engineering); Production planning; Production (economics); Computer science; Linear programming; Product (mathematics); Decision support system; Variety (cybernetics); Relational database; Manufacturing engineering; Database; Industrial engineering; Engineering; Data mining; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.03809675949874465,"gpt":0.2586021742146529,"spread":0.2205054147159082,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003149067,0.0004548044,0.0005766983,0.001480655,0.0004016291,0.0003898659,0.0004149606,0.0001605454,0.00002801809],"category_scores_gemma":[0.0006605786,0.0004220557,0.0001258906,0.001149721,0.00003302078,0.001886623,0.0001791792,0.0002705466,0.0003116421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004149379,"about_ca_system_score_gemma":0.0003741266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007862466,"about_ca_topic_score_gemma":0.00002060604,"domain_scores_codex":[0.9954935,0.000024326,0.001376788,0.001373648,0.001074186,0.0006575389],"domain_scores_gemma":[0.9981446,0.00008780864,0.0005294888,0.0007176685,0.0004482183,0.00007224711],"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":[0.008499366,0.003335969,0.03653683,0.01247098,0.0002796291,0.0003777543,0.002643698,0.6477246,0.00213845,0.009554475,0.07937459,0.1970637],"study_design_scores_gemma":[0.02403803,0.0003747021,0.03019376,0.008759391,0.0003812209,0.0004796269,0.007155639,0.04530965,0.01090431,0.0009613099,0.8663518,0.005090582],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3954693,0.0001301857,0.5873167,0.0004000124,0.005068402,0.008107137,0.00004318385,0.0006775212,0.00278754],"genre_scores_gemma":[0.9285042,9.425611e-7,0.06562561,0.0001819764,0.002082632,0.00111615,0.002091255,0.0001052801,0.0002919008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7869772,"threshold_uncertainty_score":0.9998232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992200166","doi":"10.1016/j.dss.2013.04.007","title":"Cost escalation in information technology outsourcing: A moderated mediation study","year":2013,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Outsourcing and Supply Chain Management","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Outsourcing; Mediation; Business; Moderated mediation; De-escalation; Psychology; Marketing; Social psychology; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02092803507780469,"gpt":0.2453379207276109,"spread":0.2244098856498062,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001178968,0.0002177306,0.0003324935,0.001957942,0.0001519585,0.0008592287,0.0002690264,0.0001523634,0.0002948497],"category_scores_gemma":[0.0003100278,0.0001936064,0.0000433608,0.001375496,0.00001771886,0.002871131,0.0001739336,0.0001726261,0.00392763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001103601,"about_ca_system_score_gemma":0.00001866615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001276783,"about_ca_topic_score_gemma":0.0001049549,"domain_scores_codex":[0.9977204,0.00002710432,0.0009643476,0.0002965663,0.0006536753,0.0003379265],"domain_scores_gemma":[0.9987402,0.00006244655,0.000395036,0.0004018333,0.0003797649,0.00002075155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005504167,0.0003600712,0.8498696,0.0001204708,0.00003498307,0.00001603654,0.001371069,0.0549261,0.00003581214,0.001488497,0.02624623,0.06547606],"study_design_scores_gemma":[0.002640054,0.00005393023,0.1211984,0.00009506466,0.00002812678,0.000004143258,0.01975097,0.798875,0.000003417557,0.001394477,0.05551329,0.0004430582],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8070243,0.0000192113,0.1753333,0.00150769,0.001694141,0.00522456,0.000002855316,0.0005727429,0.008621191],"genre_scores_gemma":[0.998406,0.000001314088,0.0001398164,0.0003052364,0.0002251441,0.0005229104,0.0001334845,0.0000211777,0.000244897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7439489,"threshold_uncertainty_score":0.9968479,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4398768689","doi":"10.1016/j.dss.2024.114253","title":"Cyber resilience framework for online retail using explainable deep learning approaches and blockchain-based consensus protocol","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Blockchain; Resilience (materials science); Protocol (science); Computer science; Computer security; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.06621060339544389,"gpt":0.3109844650924485,"spread":0.2447738616970046,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001644603,0.0003622757,0.0004456693,0.0006057268,0.0005437207,0.001105044,0.0003153834,0.0002014044,0.0001608157],"category_scores_gemma":[0.0005921319,0.0002874416,0.0001446472,0.0008042674,0.0001276708,0.000205166,0.0002054692,0.000294993,0.00008099336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007501511,"about_ca_system_score_gemma":0.00007795263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001934478,"about_ca_topic_score_gemma":0.00002626781,"domain_scores_codex":[0.9970654,0.00003853655,0.0007504639,0.0008863706,0.0006617222,0.0005974594],"domain_scores_gemma":[0.9982647,0.0007817674,0.0002772138,0.0004336408,0.0001922191,0.00005047429],"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":[0.001504389,0.000709757,0.0393828,0.01474896,0.0002973853,0.001235397,0.000869856,0.5165779,0.0003184852,0.07673002,0.01886145,0.3287636],"study_design_scores_gemma":[0.0005044805,0.00004318616,0.0001675068,0.0007172117,0.00005646913,0.00001547263,0.002878538,0.7201515,0.00001457355,0.001522772,0.2736037,0.000324588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3193128,0.001045582,0.5776547,0.001044049,0.002405692,0.09439507,0.00002676269,0.001073508,0.00304184],"genre_scores_gemma":[0.9440633,0.000004186036,0.02661901,0.0004815393,0.001825532,0.02443139,0.00005364148,0.0001494044,0.002371985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6247506,"threshold_uncertainty_score":0.9999578,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387142828","doi":"10.1016/j.dss.2023.114099","title":"Upstream information sharing in platform-based e-commerce with retail plan adjustment","year":2023,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Business; Commission; Information sharing; Competition (biology); Ceiling (cloud); Incentive; Industrial organization; Finance; Economics; Microeconomics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.0487975229589617,"gpt":0.2419374423102378,"spread":0.1931399193512761,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001109269,0.0002481451,0.0003085328,0.001226831,0.000128907,0.0004713273,0.0004183008,0.00008625732,0.0006565598],"category_scores_gemma":[0.00005384247,0.0001977052,0.00006769582,0.0012163,0.00002224861,0.002150574,0.0002125019,0.0001325904,0.003590764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001160282,"about_ca_system_score_gemma":0.00002708665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005682545,"about_ca_topic_score_gemma":0.0001381531,"domain_scores_codex":[0.9977441,0.000007681442,0.0007126178,0.000319403,0.0007776004,0.0004385417],"domain_scores_gemma":[0.9989892,0.00006781776,0.000295586,0.0005178488,0.00009880152,0.000030723],"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":[0.0008807921,0.0002713053,0.4278874,0.001451461,0.0001076558,0.0002941903,0.0007505373,0.03284499,0.00001783966,0.0195691,0.3996956,0.1162292],"study_design_scores_gemma":[0.002606919,0.00005714807,0.05290193,0.0004800831,0.00002930836,0.00000467361,0.003712709,0.1310342,0.000009240279,0.0002570675,0.808454,0.0004526223],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7957782,0.00006537233,0.006716923,0.0007810094,0.003748789,0.002939506,0.00002734591,0.001248023,0.1886948],"genre_scores_gemma":[0.9956531,0.000006559714,0.00007634582,0.001367791,0.0003328753,0.0002025855,0.0007007856,0.00003498278,0.001624971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4087585,"threshold_uncertainty_score":0.9971851,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4311548908","doi":"10.1016/j.dss.2022.113912","title":"Security defense against long-term and stealthy cyberattacks","year":2022,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Information and Cyber Security","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea; Ministry of Science, ICT and Future Planning; National Science Foundation","keywords":"Hacker; Computer security; Damages; Computer science; Internet privacy; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.01617874624748566,"gpt":0.2676629327890481,"spread":0.2514841865415624,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001501157,0.0001918693,0.0002961544,0.0002372154,0.0006789301,0.0004559614,0.0008121345,0.00006797657,0.0001704349],"category_scores_gemma":[0.00003232627,0.0001832291,0.00008444195,0.0004447142,0.00003200682,0.0007495638,0.0009309959,0.0003108913,0.0002205218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001128397,"about_ca_system_score_gemma":0.0001518789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002283346,"about_ca_topic_score_gemma":0.00001223099,"domain_scores_codex":[0.9973218,0.0002134082,0.000690058,0.0004405984,0.0009667922,0.0003673283],"domain_scores_gemma":[0.9983755,0.0001483717,0.000257323,0.0008241673,0.0001343928,0.0002602916],"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":[0.0002987474,0.0009547006,0.08585212,0.0004965795,0.0001787107,0.002237375,0.06496043,0.001124418,0.0001168659,0.2816951,0.2942732,0.2678118],"study_design_scores_gemma":[0.005106437,0.0009277813,0.04512954,0.0001225691,0.00002631886,0.003647127,0.003034675,0.08286849,0.0001203593,0.002138411,0.8548588,0.002019513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8788135,0.0006146723,0.09590576,0.0003024688,0.004266985,0.0008181254,0.00007637711,0.0003743037,0.01882779],"genre_scores_gemma":[0.9976104,0.0000332482,0.0003422683,0.001367271,0.00006033646,0.00007422428,0.00004195056,0.00001122755,0.0004590744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5605856,"threshold_uncertainty_score":0.7471867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393353640","doi":"10.1016/j.dss.2024.114215","title":"Prioritising national healthcare service issues from free text feedback – A computational text analysis & predictive modelling approach","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Patient Satisfaction in Healthcare","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Health Research Board","keywords":"Lexicon; Computer science; Context (archaeology); Health care; Knowledge management; Quality (philosophy); Analytics; Quality management; Salience (neuroscience); Data science; Service (business); Management science; Artificial intelligence; Marketing; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.1421765546787043,"gpt":0.4376561759686145,"spread":0.2954796212899102,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002081803,0.0004773424,0.001028904,0.001309262,0.001389552,0.0001992394,0.0005507481,0.0006661205,0.001087027],"category_scores_gemma":[0.0004367359,0.0004599102,0.0003030203,0.002995961,0.00005615556,0.0007122217,0.0002971685,0.001276438,0.00269427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437335,"about_ca_system_score_gemma":0.001718454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01498286,"about_ca_topic_score_gemma":0.001237427,"domain_scores_codex":[0.9910005,0.001226301,0.002513941,0.001416427,0.003026706,0.0008161369],"domain_scores_gemma":[0.9906896,0.00460523,0.0006215668,0.0008821104,0.00267934,0.0005221527],"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":[0.0003039065,0.00009933802,0.2192869,0.001857741,0.001435797,0.00003190087,0.02323542,0.6570905,0.000007493558,0.005374093,0.08801731,0.003259581],"study_design_scores_gemma":[0.000810653,0.00005689613,0.0383203,0.002011498,0.0002391749,0.00001828691,0.006246221,0.8997446,3.927286e-7,0.008458508,0.04360326,0.00049022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.104747,0.004909479,0.8660769,0.002841507,0.00593382,0.002805557,0.007854977,0.0008922317,0.003938545],"genre_scores_gemma":[0.9506412,0.0001304378,0.03796971,0.0009251382,0.001542101,0.0006247809,0.006361281,0.0001188217,0.001686587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8458942,"threshold_uncertainty_score":0.9999105,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015139433","doi":"10.1016/j.dss.2004.11.003","title":"Decision support systems in emerging economies","year":2004,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Emerging markets; Economics; Business; Macroeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.05626105543888894,"gpt":0.3005265326387696,"spread":0.2442654771998806,"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":[0.001871337,0.0004899746,0.0008275491,0.00126448,0.0002617938,0.001337112,0.001005134,0.0002815843,0.00114634],"category_scores_gemma":[0.0003569293,0.0004282304,0.0001725025,0.001217082,0.00007738581,0.003110854,0.000478156,0.0002744314,0.008575139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002171838,"about_ca_system_score_gemma":0.0001341071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003448287,"about_ca_topic_score_gemma":0.0004776629,"domain_scores_codex":[0.9955872,0.00001766021,0.001773599,0.0009402042,0.0009078037,0.0007735695],"domain_scores_gemma":[0.9977462,0.0001975217,0.0006078103,0.001027829,0.0003594067,0.00006122958],"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":[0.001179895,0.001342367,0.1864816,0.002566185,0.0002033468,0.002599339,0.0007553177,0.105082,0.0008280173,0.1096951,0.3309181,0.2583488],"study_design_scores_gemma":[0.001704559,0.00003683118,0.00902155,0.001202489,0.000042794,0.000170649,0.001531432,0.006874926,0.0000490387,0.002950277,0.9754714,0.0009440776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8006772,0.001818805,0.1191568,0.0006382297,0.03075002,0.002554326,0.000101865,0.0007165997,0.04358608],"genre_scores_gemma":[0.9962466,0.00009760193,0.0004203348,0.0003709113,0.001522645,0.0001043032,0.0002000887,0.00007944809,0.0009580736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6445532,"threshold_uncertainty_score":0.999817,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389855353","doi":"10.1016/j.dss.2023.114148","title":"Play it safe or leave the comfort zone? Optimal content strategies for social media influencers on streaming video platforms","year":2023,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Influencer marketing; Variation (astronomy); Computer science; Time horizon; Markov decision process; Advertising; Marketing; Business; Markov process; Marketing management","retraction":null,"screen_n_in":null,"score":{"opus":0.1403754251632413,"gpt":0.3657733569260477,"spread":0.2253979317628065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00444503,0.0002648831,0.0005098383,0.000176829,0.001676656,0.0007709698,0.0006533751,0.0002865434,0.0001305368],"category_scores_gemma":[0.003389148,0.000166976,0.00024913,0.0006301616,0.0004524254,0.0005342328,0.000092243,0.0002301528,0.0002776727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283922,"about_ca_system_score_gemma":0.0008306584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005203974,"about_ca_topic_score_gemma":0.00203037,"domain_scores_codex":[0.9961724,0.0001230906,0.000792097,0.0004281275,0.001683115,0.0008012291],"domain_scores_gemma":[0.9911714,0.007751779,0.0003257615,0.0002513036,0.0002614622,0.0002382535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.002267193,0.0001541218,0.002813498,0.0001161728,0.0002638756,0.0002162428,0.2844948,0.000976858,0.00005389189,0.08847349,0.4905983,0.1295716],"study_design_scores_gemma":[0.0009803558,0.0002480833,0.002410678,0.0002403704,0.00003271988,0.000004446433,0.6673591,0.0002386207,0.000009615555,0.001426581,0.3266546,0.0003948478],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9525852,0.00002442686,0.0008332604,0.001005784,0.005369064,0.001546952,0.0002771851,0.0003186528,0.03803944],"genre_scores_gemma":[0.9907132,0.0000430414,0.00006404037,0.0002215747,0.001321599,0.0002722705,0.00007869825,0.00003708977,0.00724848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3828644,"threshold_uncertainty_score":0.999623,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409235722","doi":"10.1016/j.dss.2025.114451","title":"Can comments and dialogues make sense? The effect of two-way interactions on sales and followers in live streaming commerce","year":2025,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Sense (electronics); Computer science; Business; Microeconomics; Economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01986971340207341,"gpt":0.3343495987115793,"spread":0.3144798853095059,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001862774,0.0001008488,0.0002787692,0.0001244525,0.0002813944,0.0001262441,0.0001002875,0.00005502462,0.000003910001],"category_scores_gemma":[0.001374567,0.000071419,0.00004366285,0.0002081612,0.0002100052,0.00006003615,0.00006494509,0.0001200523,0.000003949584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006442334,"about_ca_system_score_gemma":0.00003899592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006320468,"about_ca_topic_score_gemma":0.01298404,"domain_scores_codex":[0.9984392,0.0006504439,0.0002906207,0.0001710364,0.0002788674,0.0001698377],"domain_scores_gemma":[0.9928156,0.006839738,0.0001065877,0.0001338412,0.0000387143,0.0000654972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002435725,0.00008507525,0.7375394,0.00009653827,0.00009043024,0.00003912026,0.04400809,0.000009562282,0.00004269244,0.003559689,0.007446614,0.2068393],"study_design_scores_gemma":[0.007059966,0.001531253,0.4820845,0.007838848,0.00024211,0.00002057894,0.3455672,0.0004685352,0.0001440489,0.003447674,0.1506078,0.0009875798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701235,0.0001078329,0.000009966718,0.0006636169,0.001095015,0.0003903967,0.00002819913,0.00001756873,0.02756393],"genre_scores_gemma":[0.9988121,0.00006063931,0.000006757537,0.00008566934,0.00004433124,0.00002218922,0.000008584661,0.000005519055,0.0009542253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3015591,"threshold_uncertainty_score":0.95547,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2808948407","doi":"10.1016/j.dss.2018.06.005","title":"A decision maxim for efficient task realization within analytical network infrastructures","year":2018,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"University of Pretoria","keywords":"Computer science; Task (project management); Realization (probability); Dimensioning; Heuristic; Cloud computing; Distributed computing; Architecture; Maxim; Systems engineering; Artificial intelligence; Engineering; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.01637350381008765,"gpt":0.2775932834170432,"spread":0.2612197796069555,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002044041,0.0002575952,0.0003905125,0.0002603082,0.000468593,0.0004594827,0.001091208,0.0001486857,0.0000227033],"category_scores_gemma":[0.0002713831,0.0001960243,0.0001447609,0.0009279944,0.00007433226,0.00002447433,0.000582581,0.0001039742,0.0001422335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009311157,"about_ca_system_score_gemma":0.0000760159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002294956,"about_ca_topic_score_gemma":0.000006132913,"domain_scores_codex":[0.9966371,0.00009781762,0.0009277909,0.0008279099,0.0009799429,0.0005294213],"domain_scores_gemma":[0.9973981,0.0005382073,0.0003265966,0.001131499,0.0003884259,0.0002171354],"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":[0.0001460215,0.00007809162,0.001225984,0.00004284758,0.00005554024,0.00002494758,0.0008129798,0.660087,0.00001504947,0.04235002,0.1723713,0.1227902],"study_design_scores_gemma":[0.000553003,0.0003552704,0.002370248,0.000178081,0.00001755653,0.00005388684,0.00004160405,0.9360939,0.00001596377,0.00311248,0.05697162,0.0002364323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1710605,0.00004327603,0.8225924,0.00005052775,0.004096977,0.0005780369,0.000004256241,0.0002111593,0.001362875],"genre_scores_gemma":[0.9551047,9.801231e-7,0.04304352,0.0002138535,0.0009932016,0.00003053973,0.00001042043,0.00002548664,0.0005772684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7840443,"threshold_uncertainty_score":0.7993639,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410081179","doi":"10.1016/j.dss.2025.114470","title":"Product return prediction in live streaming e-commerce with cross-modal contrastive transformer","year":2025,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Modal; Transformer; Computer science; Product (mathematics); Mathematics; Engineering; Voltage; Electrical engineering; Chemistry; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01389323321094472,"gpt":0.2673340555854815,"spread":0.2534408223745367,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006295397,0.0002099844,0.0003164416,0.0005368047,0.000162353,0.0004378467,0.0001559571,0.00008237409,0.0002132174],"category_scores_gemma":[0.00008941523,0.0001670105,0.00005851026,0.0007392243,0.00004937094,0.001330422,0.000026069,0.0001718918,0.0001942508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110211,"about_ca_system_score_gemma":0.00007100664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008711715,"about_ca_topic_score_gemma":0.0005170808,"domain_scores_codex":[0.9982046,0.00001760848,0.0006087956,0.0004470878,0.0004339715,0.0002878599],"domain_scores_gemma":[0.9991945,0.0001144157,0.0001849369,0.0002297053,0.0002602431,0.0000161738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001214926,0.0002531681,0.9325889,0.0004676856,0.00009365482,0.00007061305,0.0008539825,0.0005437804,0.001425455,0.001494839,0.01118814,0.04980483],"study_design_scores_gemma":[0.006168887,0.0000889884,0.933193,0.001479663,0.0001371783,0.00002735473,0.007258043,0.01119552,0.0003482045,0.0003708895,0.03917772,0.0005546072],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9428058,0.0001172084,0.01164764,0.0001911404,0.001460995,0.001221573,0.000022031,0.0001247368,0.04240889],"genre_scores_gemma":[0.9963744,0.000007191797,0.00005187287,0.0002505547,0.0003400189,0.0000877979,0.0001340087,0.00002050846,0.002733692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05356856,"threshold_uncertainty_score":0.681049,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}