{"meta":{"query_hash":"828120d46610","filters":{"venue":"Decision Support Systems"},"cohort_total":60,"direct_labels_cover":0,"predictions_cover":60,"exported":60,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/828120d46610","api":"https://metacan.xera.ac/api/v1/cohort?venue=Decision+Support+Systems"},"results":[{"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.2560177653132057,"score_gpt":0.4309712288629836,"score_spread":0.17495346354977792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964271741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41299427,0.00077163836,0.46096945,0.000044561995,0.0024944548,0.0018328027,0.00010181988,0.00017910119,0.12061191],"genre_scores_gemma":[0.9791383,0.0000056470267,0.007708426,0.0000698662,0.00018767102,0.0001450692,0.00007177442,0.000022482798,0.012650757],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947081,0.0001300189,0.0017773208,0.0007676352,0.0021563983,0.0004605238],"domain_scores_gemma":[0.99695003,0.0009242066,0.0003684897,0.0008751566,0.00040210644,0.00047999862],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004776821,0.00029397916,0.0005233837,0.0013482124,0.00033850738,0.0013712109,0.0008875408,0.00012068499,0.000097327844],"category_scores_gemma":[0.00020507458,0.0002232753,0.00012377361,0.0013305828,0.000052987107,0.00078446773,0.00039012296,0.00010999094,0.0029288253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048445378,0.0008010148,0.10510702,0.00012592561,0.00024565883,0.00022149492,0.027059367,0.0006002692,0.00009671602,0.06276251,0.5946791,0.20781647],"study_design_scores_gemma":[0.0017065653,0.00015385445,0.14601378,0.00017483308,0.00009744258,0.000059745995,0.2085115,0.013545566,0.00002315612,0.00068999274,0.6280959,0.0009276426],"about_ca_topic_score_codex":0.00013673847,"about_ca_topic_score_gemma":0.00003335574,"teacher_disagreement_score":0.56614405,"about_ca_system_score_codex":0.00009565578,"about_ca_system_score_gemma":0.000032233234,"threshold_uncertainty_score":0.99966544},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.2601201774639123,"score_gpt":0.4353605905976103,"score_spread":0.17524041313369798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964390465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5426373,0.00026450056,0.45271745,0.000041498985,0.0022501065,0.00056945987,0.00008994219,0.00012356303,0.0013062059],"genre_scores_gemma":[0.94659567,0.000040777573,0.050476305,0.000215533,0.00027474112,0.000081705344,0.000048050526,0.00007931512,0.00218788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9807636,0.0010902632,0.005934403,0.0027028944,0.008249229,0.0012595892],"domain_scores_gemma":[0.9765399,0.016212963,0.0012662584,0.0039304392,0.0012945847,0.00075582677],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.015192991,0.0007637192,0.0025163533,0.007701548,0.0007526771,0.0012499859,0.003295319,0.0005278282,0.006224331],"category_scores_gemma":[0.019919109,0.00060062506,0.0010969115,0.010043169,0.0002364651,0.0016270017,0.0010651691,0.00055334455,0.0040178476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00091608934,0.00032109846,0.7579237,0.000007613548,0.00018684808,0.002442213,0.0016830916,0.016560568,0.00083825155,0.00012638143,0.073981546,0.14501257],"study_design_scores_gemma":[0.003455094,0.00012329743,0.5234383,0.00020094351,0.00009637649,0.00059374276,0.0014346826,0.34521973,0.00009657583,0.0019174651,0.12236587,0.0010579327],"about_ca_topic_score_codex":0.00048608988,"about_ca_topic_score_gemma":0.00039265063,"teacher_disagreement_score":0.4039584,"about_ca_system_score_codex":0.0001739742,"about_ca_system_score_gemma":0.00020373153,"threshold_uncertainty_score":0.9997868},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.09056001981553732,"score_gpt":0.30669616149318085,"score_spread":0.21613614167764353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972932886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013460961,0.00028258705,0.98149574,0.00009428743,0.0016144263,0.0015095227,0.000027399323,0.000102425554,0.0014126531],"genre_scores_gemma":[0.83049154,0.0000065032987,0.16838172,0.00009596072,0.00017932306,0.0006432716,0.00009950653,0.000017850667,0.00008433379],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974682,0.00012346258,0.0007913867,0.00056886295,0.00045082739,0.00059728464],"domain_scores_gemma":[0.9982661,0.00028819763,0.00026516907,0.00089646544,0.0001202922,0.00016377358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002123013,0.00022653164,0.0003970181,0.00022228541,0.00011752264,0.00026917848,0.0007983384,0.00017668978,0.0000081370445],"category_scores_gemma":[0.00008976677,0.00017881252,0.00011097395,0.0004990314,0.000030104786,0.0008364159,0.00009933262,0.00011060317,0.00008082211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086895627,0.0067303143,0.16605395,0.0026063202,0.00011950671,0.00006872816,0.024368308,0.026875094,0.0063512223,0.17350462,0.15943857,0.43301442],"study_design_scores_gemma":[0.001952712,0.00015416986,0.016243078,0.000088521185,0.000007159184,0.000038255104,0.00022718054,0.92089516,0.000065712426,0.0005101641,0.059402853,0.00041500578],"about_ca_topic_score_codex":0.00003708339,"about_ca_topic_score_gemma":0.0000025300162,"teacher_disagreement_score":0.8940201,"about_ca_system_score_codex":0.000114480164,"about_ca_system_score_gemma":0.000066329405,"threshold_uncertainty_score":0.7291763},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.025530021718187735,"score_gpt":0.291850017953823,"score_spread":0.26631999623563524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973206570","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008169655,0.000081488906,0.9776292,0.00014485526,0.0037895304,0.0007554896,0.000010268112,0.0011906106,0.008228933],"genre_scores_gemma":[0.9503499,0.0000027102365,0.048954714,0.00013557338,0.0002189435,0.000060353057,0.00008332317,0.000033967503,0.00016048203],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962051,0.00021078056,0.0014351481,0.00076887145,0.0008280309,0.0005520482],"domain_scores_gemma":[0.99722433,0.00043631837,0.00066254847,0.001071623,0.0003461215,0.00025904024],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0050964234,0.00031977784,0.0004859633,0.000710035,0.00033843933,0.0006735127,0.00084740564,0.00024683148,0.0000230354],"category_scores_gemma":[0.000036758527,0.00028646327,0.00019849377,0.0010583036,0.00002377345,0.0009945361,0.00014800378,0.00021526658,0.00025684544],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018279978,0.00040252984,0.018666726,0.0010394352,0.00014888697,0.0006494864,0.001412221,0.00028814253,0.0040468266,0.08912651,0.10192113,0.7821153],"study_design_scores_gemma":[0.0037973516,0.0008260941,0.004641398,0.0035056672,0.00005001386,0.0019544659,0.0015491893,0.21686058,0.012592595,0.0016713564,0.7504327,0.0021185414],"about_ca_topic_score_codex":0.00025168064,"about_ca_topic_score_gemma":0.000016902648,"teacher_disagreement_score":0.9421803,"about_ca_system_score_codex":0.0003361115,"about_ca_system_score_gemma":0.00009908171,"threshold_uncertainty_score":0.99995875},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.11841580063618426,"score_gpt":0.3772495444537616,"score_spread":0.2588337438175773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975045544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20044503,0.0014596621,0.71050394,0.000016786931,0.0059926626,0.00198434,0.00019534446,0.00044472908,0.07895752],"genre_scores_gemma":[0.96598274,0.0000037444338,0.011896751,0.00006408073,0.001958573,0.00029451534,0.000106531435,0.00015709331,0.019535983],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.97639745,0.0018583499,0.007368215,0.0035016628,0.009301897,0.0015724294],"domain_scores_gemma":[0.98025787,0.008993106,0.0023059808,0.004792062,0.0027785604,0.00087241584],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.020207198,0.001228002,0.0028262443,0.0025904884,0.0016514473,0.005639401,0.0039254134,0.00070582924,0.0015596367],"category_scores_gemma":[0.0036524928,0.0008398509,0.0008626003,0.0030479392,0.00038097077,0.002230561,0.0008567013,0.0007970434,0.0019122546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005575602,0.0010527772,0.020573614,0.000059482256,0.00009996249,0.0004536384,0.0034357496,0.26047465,0.0007334459,0.29507285,0.39410084,0.023385406],"study_design_scores_gemma":[0.0038660357,0.0011842576,0.008515864,0.0009927202,0.00007216695,0.0018856523,0.09091528,0.3603682,0.000030795338,0.10746038,0.4219459,0.0027627635],"about_ca_topic_score_codex":0.0036734568,"about_ca_topic_score_gemma":0.0004706583,"teacher_disagreement_score":0.7655377,"about_ca_system_score_codex":0.0006065338,"about_ca_system_score_gemma":0.00037355532,"threshold_uncertainty_score":0.9996483},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03777623411525292,"score_gpt":0.33547138640315016,"score_spread":0.2976951522878972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976617111","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013277794,0.000104908795,0.41720828,0.00049247994,0.00415858,0.0005592586,0.0000046946843,0.00031231996,0.5638817],"genre_scores_gemma":[0.98629624,0.000043912078,0.000330884,0.00011823566,0.00077600597,0.000047555346,0.000025841073,0.000016372202,0.012344965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978336,0.00019590268,0.0004952464,0.00028792146,0.0007699407,0.00041735734],"domain_scores_gemma":[0.9988502,0.0003829101,0.00019773174,0.0002861845,0.00012047977,0.00016248091],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014976941,0.0001361211,0.00028652078,0.00007545229,0.00095491833,0.0003059659,0.00038326002,0.000118383854,0.0011809276],"category_scores_gemma":[0.00057575124,0.00011760247,0.000105238876,0.00022600175,0.00007962844,0.00047098403,0.00009747007,0.00015796373,0.0009066846],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001700499,0.00013660795,0.05709526,0.00011263322,0.00017208072,0.00006480988,0.03454718,0.031664744,0.00020693675,0.6287796,0.08635966,0.16069047],"study_design_scores_gemma":[0.00041194513,0.00006103107,0.00070022506,0.00005793253,0.000008501457,0.000003624108,0.0030061253,0.0040279026,0.000008647946,0.00047649367,0.991072,0.00016558565],"about_ca_topic_score_codex":0.0017621557,"about_ca_topic_score_gemma":0.000085976695,"teacher_disagreement_score":0.9730184,"about_ca_system_score_codex":0.00007219799,"about_ca_system_score_gemma":0.00008289683,"threshold_uncertainty_score":0.99987125},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03383335041847852,"score_gpt":0.3051997118098388,"score_spread":0.2713663613913603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980367442","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5116024,0.000020542231,0.4869544,0.000003948752,0.0006142778,0.00053031195,0.0000030579934,0.00009399842,0.00017706168],"genre_scores_gemma":[0.9943666,5.522048e-7,0.0052179084,0.000023097225,0.00009952061,0.00009029999,0.000013622928,0.000019099314,0.00016930632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99726325,0.0002518249,0.0007355336,0.0005550444,0.0009677406,0.00022660446],"domain_scores_gemma":[0.99779606,0.00013593669,0.0004077325,0.0012822861,0.00020789991,0.0001700927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076764467,0.0001965813,0.00037585676,0.00022595715,0.00020980096,0.00019344367,0.000752289,0.00006513382,0.00005222124],"category_scores_gemma":[0.000030458632,0.00014914526,0.00005695778,0.00031599906,0.00001803903,0.0006498826,0.00009820594,0.00006779576,0.000092813956],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028555174,0.025372498,0.6994324,0.0003079647,0.0004597098,0.0001912724,0.13508709,0.037688974,0.02244956,0.02617662,0.021062592,0.031485785],"study_design_scores_gemma":[0.022304386,0.040501494,0.4589866,0.00092620606,0.00018060571,0.00037096158,0.046719383,0.37320456,0.011344127,0.0002277038,0.041527763,0.003706199],"about_ca_topic_score_codex":0.00026788106,"about_ca_topic_score_gemma":0.000074222095,"teacher_disagreement_score":0.48276418,"about_ca_system_score_codex":0.000054287768,"about_ca_system_score_gemma":0.000045637684,"threshold_uncertainty_score":0.6081967},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Outsourcing; Mediation; Business; Moderated mediation; De-escalation; Psychology; Marketing; Social psychology; Political science","score_opus":0.020928035077804687,"score_gpt":0.24533792072761088,"score_spread":0.22440988564980618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992200166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8070243,0.000019211298,0.17533332,0.0015076904,0.0016941408,0.00522456,0.0000028553156,0.0005727429,0.008621191],"genre_scores_gemma":[0.998406,0.0000013140876,0.0001398164,0.00030523643,0.00022514413,0.0005229104,0.00013348449,0.000021177702,0.00024489698],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99772036,0.00002710432,0.0009643476,0.00029656632,0.0006536753,0.00033792653],"domain_scores_gemma":[0.9987402,0.000062446554,0.00039503595,0.00040183327,0.00037976494,0.000020751555],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011789682,0.00021773063,0.00033249348,0.001957942,0.00015195853,0.00085922866,0.00026902644,0.00015236341,0.00029484968],"category_scores_gemma":[0.00031002783,0.00019360644,0.000043360804,0.0013754963,0.000017718863,0.0028711306,0.00017393357,0.00017262608,0.0039276304],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005504167,0.00036007116,0.8498696,0.00012047077,0.000034983066,0.000016036542,0.0013710688,0.054926105,0.00003581214,0.0014884968,0.026246225,0.06547606],"study_design_scores_gemma":[0.0026400539,0.000053930235,0.12119842,0.000095064664,0.00002812678,0.0000041432577,0.019750973,0.79887503,0.0000034175566,0.0013944766,0.055513293,0.00044305818],"about_ca_topic_score_codex":0.0012767834,"about_ca_topic_score_gemma":0.00010495487,"teacher_disagreement_score":0.74394894,"about_ca_system_score_codex":0.00011036009,"about_ca_system_score_gemma":0.000018666145,"threshold_uncertainty_score":0.9968479},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.07898619194351643,"score_gpt":0.34999153062908006,"score_spread":0.27100533868556365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995467602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5889493,0.00043809446,0.37978613,0.00060693827,0.00956671,0.0021992158,0.000061750055,0.0005299529,0.01786187],"genre_scores_gemma":[0.979576,0.000009280518,0.0150060635,0.0008405343,0.0011965954,0.00023065823,0.00013782276,0.00010446129,0.0028985722],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99529743,0.000090875554,0.0015396305,0.0008197355,0.0014895347,0.00076280715],"domain_scores_gemma":[0.9970072,0.00074417493,0.00048263845,0.000826738,0.000728447,0.00021079014],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0073305834,0.00043985806,0.00069268123,0.0009250145,0.00034705177,0.0012035655,0.00071564195,0.00018714191,0.006502257],"category_scores_gemma":[0.0023371612,0.00040168807,0.00048424213,0.0011123107,0.000033950062,0.0009191115,0.00092261966,0.00030422016,0.003754104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021185416,0.00037858263,0.14479735,0.00040400008,0.00012389467,0.00041983058,0.0008117751,0.00021243039,0.00009771873,0.0031455196,0.54232377,0.3051666],"study_design_scores_gemma":[0.0018491284,0.00009063885,0.019340996,0.0014121558,0.00022064602,0.00008988057,0.003863544,0.001697134,0.0000045207107,0.00046027926,0.9702036,0.00076751586],"about_ca_topic_score_codex":0.00039923866,"about_ca_topic_score_gemma":0.00008306904,"teacher_disagreement_score":0.4278798,"about_ca_system_score_codex":0.0001553129,"about_ca_system_score_gemma":0.0001237681,"threshold_uncertainty_score":0.9998435},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.05576027937582548,"score_gpt":0.3651494029902846,"score_spread":0.30938912361445914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997408825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5514862,0.000083151645,0.43586752,0.0003958341,0.0004699435,0.0044356855,0.000042542306,0.00014954679,0.00706959],"genre_scores_gemma":[0.9989553,5.446429e-7,0.0002085468,0.00029663584,0.00022528748,0.000096888696,0.00004277927,0.000021855547,0.00015212521],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980873,0.000045887195,0.00093430537,0.0002348791,0.00036944012,0.00032822756],"domain_scores_gemma":[0.99844223,0.00034913086,0.00065329944,0.0002544017,0.0002862401,0.000014691411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022498814,0.00020218962,0.00043936493,0.0004828818,0.00014172784,0.00028513177,0.00025950774,0.00006736916,0.000045009794],"category_scores_gemma":[0.00065532397,0.00012003973,0.00025406832,0.0005425768,0.000017594926,0.0005323362,0.000016961494,0.00013548795,0.000019649011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002258933,0.0006133654,0.31264162,0.0006150054,0.00018051024,0.00002184553,0.002086989,0.45383495,0.0077768452,0.013309009,0.11839892,0.08826201],"study_design_scores_gemma":[0.0028144438,0.00016652401,0.009366457,0.00021993586,0.000020516134,0.000003608655,0.0017946712,0.98151934,0.0000117510035,0.00027513978,0.003636151,0.00017145953],"about_ca_topic_score_codex":0.0010952499,"about_ca_topic_score_gemma":0.000065804496,"teacher_disagreement_score":0.5276844,"about_ca_system_score_codex":0.00008318673,"about_ca_system_score_gemma":0.00017130189,"threshold_uncertainty_score":0.48950782},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.018090194391624452,"score_gpt":0.26642458965003574,"score_spread":0.24833439525841128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000653600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99532175,0.000059309303,0.0019876892,0.000061486375,0.00047716664,0.00048738584,0.0000012700234,0.000015960266,0.001587961],"genre_scores_gemma":[0.9997448,0.000008382905,0.000028286215,0.000053850796,0.00006987947,0.000021807284,0.0000057425327,0.000015348842,0.000051932875],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99834216,0.00015542845,0.00061231834,0.00018638483,0.00050141517,0.00020230252],"domain_scores_gemma":[0.99698275,0.0021911282,0.0003084769,0.0003448083,0.00016356619,0.000009263574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002651868,0.000124916,0.00026977336,0.00021880637,0.00024326106,0.00014866826,0.0002321674,0.00005465168,0.000022893677],"category_scores_gemma":[0.00049658254,0.00007650421,0.000074955926,0.00033479603,0.000047055062,0.00023780846,0.00009628024,0.00012386078,0.000024918987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00107618,0.00023168852,0.42640975,0.001218051,0.000026965923,0.000045654262,0.0006149729,0.0008353383,0.019831974,0.007467829,0.0004924877,0.5417491],"study_design_scores_gemma":[0.0018864763,0.00013851,0.70380884,0.0051476657,0.00009166048,0.000021430764,0.0011205946,0.2780567,0.0054544928,0.00092203624,0.0029410769,0.0004105097],"about_ca_topic_score_codex":0.0003129138,"about_ca_topic_score_gemma":0.00013583298,"teacher_disagreement_score":0.54133856,"about_ca_system_score_codex":0.000021351987,"about_ca_system_score_gemma":0.00001573248,"threshold_uncertainty_score":0.31197512},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Fundacja na rzecz Nauki Polskiej","keywords":"Computer science","score_opus":0.08130157364663176,"score_gpt":0.3269626436789583,"score_spread":0.2456610700323265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012453507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015350802,0.002141062,0.9345766,0.000086538355,0.022600232,0.0024437967,0.000101652964,0.00090191496,0.021797441],"genre_scores_gemma":[0.96796435,0.0004189749,0.025354356,0.00013876651,0.001514478,0.0004886291,0.000020310954,0.00004061705,0.004059511],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99553263,0.00014467699,0.0018154057,0.00096124556,0.0008816106,0.00066440407],"domain_scores_gemma":[0.99677944,0.00059943594,0.00046473806,0.0014527029,0.0003219553,0.0003817196],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024525744,0.00031184548,0.00072582974,0.00026031162,0.00029239675,0.0003501212,0.0016287687,0.00026688632,0.00024148005],"category_scores_gemma":[0.0001544363,0.00024137928,0.00044685474,0.0006545927,0.000037369122,0.00048646264,0.00031464762,0.00017011145,0.002740693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019747878,0.00031157248,0.012014027,0.00023451268,0.000041995412,0.00019017818,0.0006393098,0.00016701526,0.00000579131,0.0070558493,0.9086095,0.070710495],"study_design_scores_gemma":[0.001473845,0.001929658,0.0011111991,0.000039639883,0.000054492764,0.00038041698,0.00050646137,0.11341437,0.000010232282,0.00024280974,0.88011247,0.00072438404],"about_ca_topic_score_codex":0.00001033645,"about_ca_topic_score_gemma":0.0000011765272,"teacher_disagreement_score":0.95261353,"about_ca_system_score_codex":0.00006788611,"about_ca_system_score_gemma":0.00007922812,"threshold_uncertainty_score":0.9980358},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.2567293354449826,"score_gpt":0.4267060105893846,"score_spread":0.169976675144402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014179994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916387,0.00016022257,0.0030729247,0.00020178972,0.00194369,0.002699487,0.00010591333,0.00011992578,0.000057315625],"genre_scores_gemma":[0.9965708,0.000006736234,0.00024682077,0.00007637813,0.000068255904,0.0011208281,0.000016110203,0.000027205133,0.00186684],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99477434,0.00047425574,0.0015987589,0.0009391855,0.0017085441,0.0005049095],"domain_scores_gemma":[0.99177015,0.005661624,0.0005179302,0.0013732435,0.0005169591,0.0001600948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049295314,0.00027414202,0.00068948965,0.00075167435,0.0005962123,0.00018613241,0.0015271063,0.0002478333,0.0004037987],"category_scores_gemma":[0.0026263045,0.00015953579,0.00014557298,0.0022433216,0.00017274653,0.00033998495,0.00023143094,0.00038023182,0.00026724185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010386065,0.0002334331,0.959623,0.0000013881828,0.0000091978545,0.00005560132,0.004703615,0.000077797245,0.0000027356655,0.00006246188,0.029686691,0.0054402556],"study_design_scores_gemma":[0.0008476052,0.00048234122,0.930666,0.00002587021,0.0000075375533,0.00007123077,0.048320495,0.00005558525,0.000009650385,0.00033012996,0.018974634,0.00020891713],"about_ca_topic_score_codex":0.00030580894,"about_ca_topic_score_gemma":0.00018889253,"teacher_disagreement_score":0.04361688,"about_ca_system_score_codex":0.00011957067,"about_ca_system_score_gemma":0.0001914499,"threshold_uncertainty_score":0.65056807},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Emerging markets; Economics; Business; Macroeconomics","score_opus":0.056261055438888936,"score_gpt":0.30052653263876955,"score_spread":0.24426547719988062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015139433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80067724,0.0018188054,0.119156845,0.0006382297,0.030750018,0.002554326,0.000101864985,0.0007165997,0.04358608],"genre_scores_gemma":[0.9962466,0.00009760193,0.00042033484,0.0003709113,0.0015226449,0.000104303166,0.00020008869,0.00007944809,0.0009580736],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99558717,0.000017660208,0.0017735986,0.00094020425,0.0009078037,0.00077356945],"domain_scores_gemma":[0.9977462,0.0001975217,0.0006078103,0.0010278291,0.00035940667,0.000061229584],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018713366,0.00048997457,0.0008275491,0.0012644796,0.00026179376,0.0013371118,0.0010051336,0.00028158427,0.00114634],"category_scores_gemma":[0.00035692926,0.00042823039,0.00017250246,0.0012170823,0.00007738581,0.0031108542,0.000478156,0.0002744314,0.008575139],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001179895,0.0013423673,0.18648155,0.002566185,0.00020334682,0.0025993388,0.0007553177,0.10508201,0.0008280173,0.10969511,0.3309181,0.25834876],"study_design_scores_gemma":[0.0017045594,0.000036831178,0.00902155,0.0012024895,0.000042793996,0.00017064903,0.0015314317,0.006874926,0.000049038696,0.0029502774,0.9754714,0.00094407756],"about_ca_topic_score_codex":0.0034482866,"about_ca_topic_score_gemma":0.00047766292,"teacher_disagreement_score":0.64455324,"about_ca_system_score_codex":0.00021718384,"about_ca_system_score_gemma":0.00013410709,"threshold_uncertainty_score":0.99981695},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.05885637285492306,"score_gpt":0.36623175371019756,"score_spread":0.3073753808552745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020506644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99491805,0.000032206488,0.0028982356,0.00035106536,0.0010322201,0.0006132252,0.000016007436,0.000098085424,0.0000408883],"genre_scores_gemma":[0.99848706,0.000007807877,0.00021431418,0.00032926624,0.0000435567,0.000021449241,0.00002338234,0.0000115787125,0.0008616067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9958399,0.00045786583,0.0011998286,0.0006417261,0.0016671108,0.00019354995],"domain_scores_gemma":[0.99620533,0.00093281677,0.00085129926,0.0013313579,0.00052881363,0.00015035651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030436483,0.00019311164,0.000332102,0.0005035153,0.00025556245,0.00043735618,0.00076832855,0.00026563476,0.00003698485],"category_scores_gemma":[0.0010004848,0.00012423129,0.00009343754,0.0009428449,0.0001169787,0.00092570717,0.00008109424,0.00017520133,0.00019823895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019023874,0.00033415205,0.74146783,0.000053158717,0.000020870799,0.000009761327,0.0036853745,0.000060045477,0.089038424,0.010736763,0.00626446,0.14813893],"study_design_scores_gemma":[0.00042414086,0.0002979182,0.9815301,0.0001314962,0.00002781706,0.000023110195,0.0006873029,0.0025106324,0.00519189,0.007609889,0.0014208662,0.00014486533],"about_ca_topic_score_codex":0.000030297517,"about_ca_topic_score_gemma":0.000020047573,"teacher_disagreement_score":0.24006225,"about_ca_system_score_codex":0.000041788673,"about_ca_system_score_gemma":0.00005242643,"threshold_uncertainty_score":0.5066005},"labels":[],"label_agreement":null},{"id":"W2026319696","doi":"10.1016/s0167-9236(99)00076-7","title":"Driving resource management with application-level quality of service specifications","year":2000,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Task (project management); Computer science; Quality (philosophy); Service (business); Resource (disambiguation); Quality of service; Reliability (semiconductor); Process management; Work (physics); Risk analysis (engineering); Service level; Service quality; Service design; Architecture; Engineering management; Systems engineering; Service delivery framework; Engineering; Business; Telecommunications","score_opus":0.049504096702066486,"score_gpt":0.2900040123505573,"score_spread":0.2404999156484908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026319696","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08461727,0.00005368965,0.8846264,0.00028493928,0.00018281072,0.0008761615,0.0000144410915,0.00020921764,0.029135104],"genre_scores_gemma":[0.9717644,0.000015848698,0.025889572,0.000106879284,0.000056396428,0.00014993788,0.000017874085,0.00001363434,0.0019854982],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972095,0.000108880115,0.0009683196,0.00057956215,0.0008918352,0.0002419428],"domain_scores_gemma":[0.9969529,0.0002577848,0.00031234405,0.0020771672,0.00027812523,0.00012170542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015122099,0.0001669931,0.000349159,0.00013173076,0.00016811967,0.00009413718,0.0011471746,0.0000788083,0.00009989292],"category_scores_gemma":[0.000012402053,0.00012476905,0.00006860333,0.001028918,0.00003798483,0.00033697239,0.00011520863,0.0000866488,0.0006372259],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021377036,0.00094628683,0.14154993,0.0014630536,0.0002465609,0.000026358937,0.0049350476,0.012580937,0.00022388062,0.037767608,0.025378445,0.7746681],"study_design_scores_gemma":[0.0016118836,0.00015554049,0.41977167,0.00054893526,0.000030139221,0.00011764567,0.0013964995,0.021288846,0.00017880005,0.00068918127,0.5534298,0.00078104826],"about_ca_topic_score_codex":0.00017249394,"about_ca_topic_score_gemma":0.000031283515,"teacher_disagreement_score":0.88714707,"about_ca_system_score_codex":0.0000681778,"about_ca_system_score_gemma":0.000059570873,"threshold_uncertainty_score":0.81904626},"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,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.2514834593939663,"score_gpt":0.4545668100572395,"score_spread":0.20308335066327315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029168398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9626253,0.00014584247,0.03110833,0.0011310815,0.0016521765,0.00034778123,0.00008154225,0.00016922981,0.002738715],"genre_scores_gemma":[0.99530417,0.0000039648926,0.0008982848,0.00030607695,0.00010624593,0.00002599262,0.000023149034,0.00001695567,0.003315191],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99261385,0.00075306266,0.0021317224,0.00080551323,0.0032863729,0.0004095032],"domain_scores_gemma":[0.993481,0.001402788,0.0009402056,0.0024446368,0.0013201094,0.00041128127],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01435902,0.00025279043,0.000932943,0.00093840546,0.00024559008,0.00034812457,0.0020194857,0.00036607767,0.00046168533],"category_scores_gemma":[0.004205464,0.00013873976,0.00036164108,0.002857323,0.000246446,0.00045476065,0.00033750353,0.0003483387,0.0010134781],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059266767,0.00013426608,0.8323475,0.0000015031466,0.000088438625,0.00003655873,0.0021571103,0.0005743561,0.00004897332,0.0003693478,0.15450598,0.009676704],"study_design_scores_gemma":[0.0014413291,0.00046186734,0.48475057,0.00003073583,0.00054405973,0.00011088073,0.040687136,0.035869535,0.00016210364,0.0052648783,0.4300416,0.0006352985],"about_ca_topic_score_codex":0.00008582999,"about_ca_topic_score_gemma":0.00014325444,"teacher_disagreement_score":0.3475969,"about_ca_system_score_codex":0.000060275375,"about_ca_system_score_gemma":0.00025065884,"threshold_uncertainty_score":0.9997643},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.06558574568201868,"score_gpt":0.3541939430634403,"score_spread":0.2886081973814216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049302341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7765198,0.0016263571,0.18915945,0.00043086905,0.009583312,0.001300199,0.00005921131,0.0002497542,0.021071095],"genre_scores_gemma":[0.9898175,0.000016513934,0.0011813029,0.00012912169,0.00024095459,0.00006284396,0.0000050385693,0.00005108969,0.008495647],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9895647,0.0005531364,0.0033732203,0.0014801887,0.004167241,0.000861477],"domain_scores_gemma":[0.9914395,0.0042650816,0.0009848578,0.0023388262,0.0005932147,0.0003785247],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01232719,0.00046469225,0.0012614194,0.0016945634,0.0003462553,0.0011694352,0.002018174,0.0002697037,0.0006865157],"category_scores_gemma":[0.0039103576,0.00033586414,0.00028723673,0.0020298958,0.00008930115,0.00066096644,0.0005931957,0.00038870153,0.0028877244],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001758064,0.00012201441,0.07502972,0.00008057875,0.000017149776,0.00012922069,0.0015360524,0.0059326496,0.000744455,0.0047023026,0.038267173,0.8732629],"study_design_scores_gemma":[0.0014226427,0.00025718022,0.055077165,0.00044390812,0.000008551222,0.00031871424,0.0020636565,0.42997852,0.000024635068,0.0069341226,0.5027455,0.0007254078],"about_ca_topic_score_codex":0.00028881113,"about_ca_topic_score_gemma":0.00067693315,"teacher_disagreement_score":0.8725375,"about_ca_system_score_codex":0.00021858377,"about_ca_system_score_gemma":0.00019804414,"threshold_uncertainty_score":0.99990934},"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,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.0383330722093607,"score_gpt":0.39532866849675335,"score_spread":0.35699559628739264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059263796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96321625,0.000025659856,0.0014270458,0.000017081953,0.00045458638,0.00046911679,0.0000018970571,0.00005115707,0.034337234],"genre_scores_gemma":[0.9985395,0.0000016784786,0.000013741547,0.000007864716,0.0002401894,0.0000011886636,0.0000024253434,0.000010307515,0.0011830992],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861413,0.000089764326,0.00038057304,0.00018912245,0.0004980345,0.00022839147],"domain_scores_gemma":[0.9991279,0.00030817103,0.00015814992,0.00009409284,0.00022778178,0.00008385659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00241816,0.000088347675,0.00021855299,0.00022869236,0.000585657,0.000095453695,0.00016723563,0.000058156973,0.0001332137],"category_scores_gemma":[0.00027094924,0.000074741496,0.000031822376,0.00066260056,0.000025423065,0.00009328565,0.000091245274,0.000065399385,0.000055140717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011947185,0.001167856,0.5924713,0.00006507348,0.00019098308,0.00008660388,0.33485466,0.00020535149,0.00017013359,0.0325464,0.0135606155,0.024561545],"study_design_scores_gemma":[0.0029637597,0.0009840284,0.59992397,0.00016693246,0.00011391838,0.0000058483265,0.35416794,0.0037986191,0.00004803947,0.00019541712,0.036976464,0.00065508985],"about_ca_topic_score_codex":0.00020966162,"about_ca_topic_score_gemma":0.00026115248,"teacher_disagreement_score":0.035323285,"about_ca_system_score_codex":0.00006126646,"about_ca_system_score_gemma":0.000044857563,"threshold_uncertainty_score":0.45044598},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.13531233632280543,"score_gpt":0.4348823590853221,"score_spread":0.29957002276251665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074841635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9514982,0.00029815218,0.04297039,0.0003098656,0.002712385,0.0010799463,0.00012462933,0.00024540428,0.00076099165],"genre_scores_gemma":[0.9966381,0.00009824921,0.0005364716,0.0001137503,0.00031157304,0.00008797469,0.000061733415,0.00006203562,0.0020901181],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9879851,0.0009927355,0.0042347796,0.0014259111,0.0045186365,0.00084287487],"domain_scores_gemma":[0.9849911,0.008118751,0.0014882402,0.0030776334,0.0016011478,0.0007231691],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01170265,0.0006368762,0.0011938807,0.0015608687,0.000673295,0.0010448737,0.003083858,0.00073989655,0.0011688663],"category_scores_gemma":[0.008064298,0.00035775374,0.0006351011,0.0022669896,0.00054232817,0.00095915364,0.0004098413,0.0007500695,0.00446187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013130299,0.00079729856,0.2506184,0.0000104230685,0.00011910969,0.0000870469,0.0037255026,0.0140082585,0.0007507621,0.0013159409,0.48196295,0.24529128],"study_design_scores_gemma":[0.0042676204,0.010126328,0.30172816,0.0007056319,0.000166853,0.0020782168,0.018878855,0.1378085,0.0028277324,0.0072051287,0.5116776,0.0025293669],"about_ca_topic_score_codex":0.00020700699,"about_ca_topic_score_gemma":0.00009596204,"teacher_disagreement_score":0.24276191,"about_ca_system_score_codex":0.0004926786,"about_ca_system_score_gemma":0.0006402109,"threshold_uncertainty_score":0.99999213},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03809675949874465,"score_gpt":0.25860217421465287,"score_spread":0.22050541471590823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076041020","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39546934,0.00013018565,0.5873167,0.0004000124,0.0050684023,0.008107137,0.000043183853,0.0006775212,0.00278754],"genre_scores_gemma":[0.9285042,9.4256114e-7,0.06562561,0.00018197637,0.0020826324,0.0011161501,0.002091255,0.00010528012,0.00029190077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99549353,0.000024325998,0.0013767882,0.0013736477,0.0010741857,0.00065753894],"domain_scores_gemma":[0.99814457,0.000087808636,0.0005294888,0.0007176685,0.00044821826,0.00007224711],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003149067,0.00045480442,0.00057669834,0.001480655,0.00040162914,0.00038986595,0.00041496064,0.0001605454,0.00002801809],"category_scores_gemma":[0.0006605786,0.00042205572,0.00012589064,0.0011497209,0.000033020784,0.0018866227,0.00017917916,0.00027054662,0.0003116421],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008499366,0.003335969,0.03653683,0.012470977,0.00027962908,0.00037775433,0.0026436977,0.64772457,0.0021384496,0.009554475,0.07937459,0.19706368],"study_design_scores_gemma":[0.024038026,0.0003747021,0.030193755,0.0087593915,0.0003812209,0.0004796269,0.0071556387,0.045309648,0.010904313,0.00096130994,0.8663518,0.0050905817],"about_ca_topic_score_codex":0.00007862466,"about_ca_topic_score_gemma":0.000020606045,"teacher_disagreement_score":0.78697723,"about_ca_system_score_codex":0.00041493788,"about_ca_system_score_gemma":0.00037412657,"threshold_uncertainty_score":0.99982315},"labels":[],"label_agreement":null},{"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.025922322417450735,"score_gpt":0.3256713621303726,"score_spread":0.2997490397129219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091139645","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17993751,0.0014755692,0.003103897,0.012971311,0.009153203,0.0011549833,0.000020511063,0.0003296998,0.7918533],"genre_scores_gemma":[0.94877833,0.000094890325,0.00012746744,0.00017181074,0.011590193,0.0000032043436,0.0000073053166,0.000009585598,0.039217222],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984869,0.000081600134,0.00033881253,0.00024280538,0.0005344214,0.0003155029],"domain_scores_gemma":[0.9993717,0.00016029304,0.00008916535,0.000097222,0.0000477467,0.00023386024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070185354,0.000101723475,0.00023074054,0.00014198812,0.00019853182,0.00029362374,0.00015699498,0.000109154855,0.00006154964],"category_scores_gemma":[0.000040281946,0.00009320133,0.000057426314,0.00047938098,0.00005772008,0.00024632335,0.000037966278,0.0001084578,0.00004162479],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011228778,0.00003434088,0.0017298175,0.0000012820497,0.0000033595325,0.000014747925,0.007678899,0.0000038004932,0.0000028477155,0.006198419,0.111348286,0.87297297],"study_design_scores_gemma":[0.00029241625,0.0000459793,0.020491885,0.000025018595,0.0000035382436,0.000005170027,0.0071040518,0.000043948137,6.2737206e-7,0.0002770988,0.971605,0.00010525115],"about_ca_topic_score_codex":0.0002684185,"about_ca_topic_score_gemma":0.00023101247,"teacher_disagreement_score":0.8728677,"about_ca_system_score_codex":0.00005768704,"about_ca_system_score_gemma":0.0001336267,"threshold_uncertainty_score":0.38006398},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03176391947718251,"score_gpt":0.2781605241318947,"score_spread":0.24639660465471216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093064636","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99745,0.000050278068,0.00035643135,0.000008939893,0.0009890066,0.0004780411,0.000009216108,0.000035585414,0.0006225217],"genre_scores_gemma":[0.99953794,0.000004563397,0.000038231607,0.000005814886,0.00034427908,0.00002350782,0.000009938683,0.000017109514,0.000018590013],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977635,0.000039620874,0.0008567775,0.0003299672,0.0008323239,0.00017781342],"domain_scores_gemma":[0.9986751,0.000043831053,0.00059030985,0.00033818182,0.0003301126,0.000022451635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018252729,0.00016199112,0.00044646594,0.00038460892,0.00009463098,0.000116449744,0.00019543931,0.00011478897,0.00005004879],"category_scores_gemma":[0.00042131147,0.00013155864,0.000051416617,0.0003980409,0.000039482635,0.00060425844,0.00011199252,0.00021967212,0.0000071656464],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012244182,0.00051947637,0.9843137,0.000100727746,0.000014922338,0.000011260582,0.00078500883,0.00004770987,0.00060295925,0.00005180259,0.00060609553,0.012823864],"study_design_scores_gemma":[0.0011220847,0.00020086682,0.99176884,0.00013352011,0.00004489483,0.0000017636389,0.0012771545,0.0027610986,0.000013518053,0.000073377596,0.0024763816,0.00012649709],"about_ca_topic_score_codex":0.0075035673,"about_ca_topic_score_gemma":0.0016805285,"teacher_disagreement_score":0.012697367,"about_ca_system_score_codex":0.000014558851,"about_ca_system_score_gemma":0.00002608876,"threshold_uncertainty_score":0.9991056},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.036542654085526136,"score_gpt":0.2998481111881291,"score_spread":0.26330545710260295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106898564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052626252,0.0009995475,0.92292506,0.000053650616,0.012859029,0.00092477247,0.00001902042,0.0005312905,0.0090614045],"genre_scores_gemma":[0.88965577,0.00009488848,0.107782364,0.00018096455,0.00023700383,0.000105946376,0.000029226474,0.000058760565,0.0018550551],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9918544,0.00040466076,0.002358669,0.0015565723,0.0027725778,0.0010531074],"domain_scores_gemma":[0.9917867,0.0036290372,0.0007851838,0.0025069404,0.00079115306,0.0005009585],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0048004864,0.00061641505,0.0010855388,0.0007027587,0.00060637156,0.0015663307,0.0020377412,0.00041091273,0.00025663208],"category_scores_gemma":[0.002350589,0.00050262344,0.0002991636,0.0013309642,0.000078847515,0.001543476,0.000441145,0.00033725548,0.0027260145],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024841848,0.0005973855,0.02282949,0.00026669336,0.00018715848,0.0025123304,0.0035032344,0.0101561295,0.0009318926,0.14905716,0.3272313,0.48247883],"study_design_scores_gemma":[0.0062729823,0.0016329401,0.009834567,0.0018613368,0.00010883584,0.005584457,0.006224499,0.16072603,0.0012243008,0.01954093,0.78381723,0.003171898],"about_ca_topic_score_codex":0.00013548936,"about_ca_topic_score_gemma":0.000034337623,"teacher_disagreement_score":0.8370295,"about_ca_system_score_codex":0.00023757748,"about_ca_system_score_gemma":0.000502426,"threshold_uncertainty_score":0.99974257},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.06729195778960602,"score_gpt":0.263674913389163,"score_spread":0.19638295559955699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116163414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3139453,0.00013204964,0.67561764,0.00021521663,0.0015214381,0.00036761476,0.000008918329,0.00030608368,0.00788573],"genre_scores_gemma":[0.9944897,0.000009612656,0.0016887799,0.0004704764,0.00084755255,0.00008866974,0.00006378706,0.000045187622,0.0022962303],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99732894,0.000027720891,0.00086655654,0.0006305559,0.0006537393,0.0004924686],"domain_scores_gemma":[0.99827033,0.00011991406,0.00029851863,0.00047221183,0.0007782209,0.00006078043],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014603359,0.00030372484,0.00047162015,0.0007327651,0.00055657624,0.0008992729,0.00026347264,0.00012730727,0.00060890085],"category_scores_gemma":[0.0006379773,0.00027285045,0.0001730418,0.001565821,0.00003230844,0.0009410465,0.000090479436,0.00015305004,0.0045113093],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002967905,0.0006806065,0.24613386,0.0012877921,0.00034186966,0.00016517063,0.0016395423,0.25170645,0.004539787,0.011649588,0.10565457,0.375904],"study_design_scores_gemma":[0.0022232963,0.00003058555,0.0052064923,0.0012186847,0.0003099696,0.00004861417,0.0037404196,0.07458862,0.000034378358,0.0050330022,0.90581524,0.0017506843],"about_ca_topic_score_codex":0.000265541,"about_ca_topic_score_gemma":0.00003221502,"teacher_disagreement_score":0.8001607,"about_ca_system_score_codex":0.000048772898,"about_ca_system_score_gemma":0.00003692397,"threshold_uncertainty_score":0.99997234},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.07175070099255448,"score_gpt":0.3266277910032583,"score_spread":0.2548770900107038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117204836","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38552323,0.00048998254,0.13200004,0.00030067918,0.011976846,0.003541789,0.00012299577,0.0017321492,0.4643123],"genre_scores_gemma":[0.9691835,0.0002760489,0.002227487,0.0015970652,0.003972617,0.00016626893,0.000682775,0.00014860228,0.021745617],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99559325,0.000021633312,0.0012970547,0.0009851839,0.0013797547,0.0007231023],"domain_scores_gemma":[0.99800473,0.0001380241,0.00042816027,0.0008555214,0.0005350981,0.000038435126],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011261253,0.00048816667,0.00061972643,0.0005592815,0.00044337404,0.0010794321,0.00080444134,0.00031084105,0.027932854],"category_scores_gemma":[0.00019892727,0.00040078405,0.00021776819,0.0020878753,0.000075912656,0.0039267805,0.00019870285,0.00027467156,0.01795211],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003560634,0.00020502794,0.00848183,0.00011914232,0.000033117296,0.00011511103,0.0000525185,0.00018845475,0.00009249291,0.0020846385,0.70221996,0.28605166],"study_design_scores_gemma":[0.0005247953,0.000045523004,0.0025721444,0.00019022035,0.000057976038,0.00023410755,0.00014598534,0.0032487453,0.00006682405,0.0013426942,0.99104005,0.000530947],"about_ca_topic_score_codex":0.0016492838,"about_ca_topic_score_gemma":0.00009016807,"teacher_disagreement_score":0.5836603,"about_ca_system_score_codex":0.00008210241,"about_ca_system_score_gemma":0.0001445408,"threshold_uncertainty_score":0.99995756},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.026288756472289582,"score_gpt":0.277846949778926,"score_spread":0.2515581933066364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166048187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77377677,0.0005668322,0.22286747,0.00023499738,0.00091823895,0.0002755546,0.0000114861095,0.00007003974,0.001278582],"genre_scores_gemma":[0.9868785,0.0000050435888,0.010687158,0.00015846982,0.0002048281,0.00002620108,0.0000066298467,0.000011182066,0.0020219893],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981777,0.000091535854,0.0004805437,0.00042498,0.00047529908,0.0003499373],"domain_scores_gemma":[0.9988333,0.000261061,0.000111602276,0.0004991437,0.000053591164,0.00024127467],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009573109,0.00015345923,0.0003118254,0.00033059137,0.00007888548,0.00035227346,0.00035075695,0.0000715761,0.00036167182],"category_scores_gemma":[0.000054546355,0.00013738697,0.00007283732,0.00039503849,0.000009229074,0.000766832,0.00023786451,0.00008750816,0.0017384167],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018086852,0.0006973903,0.3626349,0.00005728281,0.00026666129,0.0003652509,0.04393004,0.0009316505,0.009028799,0.002138751,0.115711324,0.4640571],"study_design_scores_gemma":[0.0016448491,0.00016456445,0.5042589,0.0010830482,0.000055817538,0.000106690466,0.0012603274,0.1451057,0.00032443926,0.00040000852,0.34437382,0.0012218539],"about_ca_topic_score_codex":0.00010062575,"about_ca_topic_score_gemma":0.000012512188,"teacher_disagreement_score":0.46283522,"about_ca_system_score_codex":0.00005088566,"about_ca_system_score_gemma":0.00002511509,"threshold_uncertainty_score":0.9990388},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03871776234724431,"score_gpt":0.2534854039126438,"score_spread":0.2147676415653995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2286179031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5569933,0.00000722466,0.441124,0.00007822584,0.00008804359,0.00042071188,0.00001742769,0.00007048538,0.0012005947],"genre_scores_gemma":[0.8086271,5.3783214e-7,0.19052495,0.00011009753,0.00006294348,0.000084953295,0.000001850444,0.000044104712,0.0005434288],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974581,0.00008070525,0.0005001778,0.0007886094,0.00060024526,0.0005721885],"domain_scores_gemma":[0.99680126,0.0022494765,0.0003213674,0.00035785045,0.00003827142,0.00023177307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001247981,0.00029651343,0.00038711302,0.00009051363,0.00035516798,0.00009751907,0.00025069233,0.00020019221,0.0001480229],"category_scores_gemma":[0.00083809684,0.00017176713,0.00007426688,0.0002067801,0.00015702173,0.00017629021,0.00015237012,0.0001784747,0.00010541059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0046432605,0.00025493285,0.21451163,0.000108222914,0.000072008705,0.00026955284,0.0015918975,0.14805369,0.00949729,0.00034668483,0.006036133,0.61461467],"study_design_scores_gemma":[0.0011829498,0.001147054,0.0016584347,0.0013552045,0.000026272042,0.000075140066,0.000038660964,0.9914203,0.00024714082,0.0010884136,0.0013166907,0.00044368347],"about_ca_topic_score_codex":0.000046325353,"about_ca_topic_score_gemma":0.0000055533783,"teacher_disagreement_score":0.8433667,"about_ca_system_score_codex":0.00017530909,"about_ca_system_score_gemma":0.00002600639,"threshold_uncertainty_score":0.700446},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.13830822048098548,"score_gpt":0.4252479379827924,"score_spread":0.2869397175018069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2412692381","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25421673,0.0002486519,0.74108976,0.0002026976,0.0029240653,0.0009328792,0.00016645597,0.000109512206,0.00010926343],"genre_scores_gemma":[0.9376817,0.000055947905,0.059067722,0.000064326276,0.00019135866,0.000066558496,0.000022865588,0.00005987532,0.0027896615],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99299246,0.00035268272,0.002339857,0.0013012573,0.0024202727,0.0005934907],"domain_scores_gemma":[0.9775751,0.018370697,0.00081816287,0.0011479534,0.0015954819,0.0004925895],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0042128963,0.00042067806,0.00094845827,0.0008243498,0.00032313232,0.0011736269,0.0007854968,0.0004040416,0.0009849138],"category_scores_gemma":[0.022350699,0.00024689466,0.00022605518,0.0008674437,0.0001399286,0.00074644544,0.00034440713,0.00017805565,0.00038147037],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066667295,0.000059520746,0.05688721,0.00001851656,0.000037710844,0.000047692243,0.00049666455,0.000066978355,0.00017771956,0.006250291,0.027617523,0.9076735],"study_design_scores_gemma":[0.011101471,0.000653511,0.031780194,0.002050492,0.000064766384,0.00026261582,0.002537938,0.025744235,0.00015680165,0.19703451,0.7271689,0.0014445445],"about_ca_topic_score_codex":0.000081041006,"about_ca_topic_score_gemma":0.000032194464,"teacher_disagreement_score":0.90622896,"about_ca_system_score_codex":0.00017362481,"about_ca_system_score_gemma":0.00026151023,"threshold_uncertainty_score":0.99999833},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.08640592321187143,"score_gpt":0.3129794778408794,"score_spread":0.226573554629008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471707884","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04412153,0.00011183606,0.95377606,0.000032248518,0.0014144038,0.00014106177,0.000036340556,0.00009461653,0.00027188114],"genre_scores_gemma":[0.86770487,0.000012715202,0.13184689,0.00002710317,0.00023763471,0.0000037836294,0.000058638536,0.000015623038,0.00009276125],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971613,0.00010613954,0.0006902533,0.0009316593,0.0008201189,0.00029049878],"domain_scores_gemma":[0.99742883,0.0001289455,0.00021503643,0.0019699913,0.000107647,0.00014953135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074050995,0.00019883509,0.00036334418,0.00027620656,0.00017454973,0.00039473054,0.001223669,0.0001158125,0.00013576467],"category_scores_gemma":[0.00004976338,0.00012923086,0.00008994875,0.00042407573,0.000017054279,0.0013496196,0.0005451084,0.0000748226,0.00016402705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008467906,0.00012675807,0.0673884,0.000036906797,0.0006437503,0.00008316279,0.00159595,0.051800765,0.019234585,0.0056458586,0.018779216,0.83457994],"study_design_scores_gemma":[0.00039312022,0.000006923494,0.00035857878,0.00007638326,0.000023705363,0.00002750597,0.00012397318,0.9966027,0.000042832853,0.00022484991,0.0019115799,0.00020781615],"about_ca_topic_score_codex":0.00054132467,"about_ca_topic_score_gemma":0.000012128121,"teacher_disagreement_score":0.944802,"about_ca_system_score_codex":0.00007451471,"about_ca_system_score_gemma":0.000078908284,"threshold_uncertainty_score":0.52698815},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.05327603447169874,"score_gpt":0.422788200665073,"score_spread":0.36951216619337424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586885238","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17512067,0.03424419,0.0003363136,0.0015019312,0.010906721,0.004297133,0.000853257,0.00025534307,0.7724844],"genre_scores_gemma":[0.964647,0.016945112,0.0004642603,0.00012439444,0.0012583022,0.00008940288,0.00007063143,0.000040335155,0.016360536],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99728775,0.00032570606,0.00077139784,0.00028167054,0.0009828008,0.0003506727],"domain_scores_gemma":[0.99660397,0.00042998517,0.00085578783,0.0008718441,0.0009798963,0.0002585146],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0048507345,0.00016196052,0.0007453991,0.000058794514,0.00056706334,0.00027284547,0.0008348888,0.0001187887,0.0011084741],"category_scores_gemma":[0.021550275,0.000120558136,0.00038761116,0.00017006646,0.00031929582,0.0005322369,0.000120407436,0.00011970253,0.00038439024],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043421704,0.0003141412,0.012028529,0.0016368842,0.00006912284,0.000054948247,0.0013356168,1.9130249e-7,0.00002928247,0.0008899917,0.6822169,0.301381],"study_design_scores_gemma":[0.00048153085,0.0001982765,0.025354974,0.016071545,0.00008229455,0.000007767532,0.0015741409,0.000012366814,0.000009890972,0.00054707006,0.95518893,0.00047123624],"about_ca_topic_score_codex":0.0017814351,"about_ca_topic_score_gemma":0.00011031839,"teacher_disagreement_score":0.78952634,"about_ca_system_score_codex":0.0000965681,"about_ca_system_score_gemma":0.00047267316,"threshold_uncertainty_score":0.9998047},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.2407179183520798,"score_gpt":0.4449000028484378,"score_spread":0.20418208449635797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620631196","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15920478,0.004145513,0.71190965,0.014537609,0.017315282,0.0067088366,0.00011538309,0.00038259113,0.085680366],"genre_scores_gemma":[0.9937773,0.0023519623,0.0011499837,0.00068660366,0.0009820785,0.00009442596,0.00005549687,0.00003740855,0.0008647458],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996955,0.000047374502,0.00067831663,0.000674624,0.0012120544,0.0004326465],"domain_scores_gemma":[0.99596745,0.00087442435,0.00048391987,0.0015322733,0.0010911697,0.000050784394],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004114354,0.0002473703,0.000378365,0.00044622397,0.001980883,0.0025070792,0.000723443,0.00018912522,0.00028695315],"category_scores_gemma":[0.0035889754,0.00016161606,0.000048215235,0.00064230466,0.00042858228,0.0013472824,0.0006854435,0.0004419747,0.00062066526],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016957888,0.0002642646,0.011799311,0.00033920573,0.000068692825,0.000060222017,0.00025725758,0.00013702022,0.00003902946,0.15003927,0.097906746,0.7373932],"study_design_scores_gemma":[0.0012444073,0.00007574697,0.010804235,0.0010642128,0.00006251213,0.00003379762,0.0009140632,0.009021715,0.000011302967,0.041106306,0.9353339,0.00032780817],"about_ca_topic_score_codex":0.00044157915,"about_ca_topic_score_gemma":0.00016554884,"teacher_disagreement_score":0.83742714,"about_ca_system_score_codex":0.000060139886,"about_ca_system_score_gemma":0.000062331805,"threshold_uncertainty_score":0.9993184},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.3523520200785031,"score_gpt":0.374713631088695,"score_spread":0.022361611010191906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2727729132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9424102,0.001600589,0.028791595,0.0015119241,0.0037479869,0.0017648926,0.0009453708,0.000096275806,0.01913121],"genre_scores_gemma":[0.9988023,0.000044392513,0.0002868966,0.0001316039,0.00043280225,0.000004990557,0.00010804818,0.00001504209,0.00017393379],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979434,0.000034267527,0.0007671776,0.00036521672,0.00068089,0.00020904299],"domain_scores_gemma":[0.9932677,0.0006082004,0.0012064379,0.004426081,0.000482001,0.000009589238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002038368,0.00016577993,0.00036543404,0.00006490985,0.00053639454,0.0008548871,0.0032006558,0.00008133393,0.0002640213],"category_scores_gemma":[0.0022063889,0.00008626669,0.000086504275,0.00023734936,0.0003169692,0.003746397,0.0019473681,0.0001281474,0.00012293342],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049980235,0.0003601187,0.63051754,0.0006353864,0.0002770274,0.000024056011,0.0003218164,0.00058583607,0.0005481403,0.016523657,0.14298499,0.20672163],"study_design_scores_gemma":[0.00012581407,0.0000048832253,0.040641066,0.0002314064,0.00010471947,0.00001223082,0.00051589386,0.030058678,0.000060795814,0.0013422664,0.92676795,0.00013431342],"about_ca_topic_score_codex":0.01664166,"about_ca_topic_score_gemma":0.0003182635,"teacher_disagreement_score":0.78378296,"about_ca_system_score_codex":0.000009301923,"about_ca_system_score_gemma":0.00003973829,"threshold_uncertainty_score":0.9899066},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.060485151959956705,"score_gpt":0.409405834508004,"score_spread":0.3489206825480473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792794664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881525,0.00001232252,0.0003078747,0.00027641666,0.0014178088,0.00048641948,0.00003658878,0.000035990957,0.009274053],"genre_scores_gemma":[0.9988802,0.000007874039,0.00046914737,0.00008438406,0.000106605454,0.000016248758,0.000005768802,0.000011447301,0.00041833599],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967568,0.00084905745,0.00067306013,0.0002977187,0.0012106218,0.00021275505],"domain_scores_gemma":[0.9952359,0.0029952212,0.0004894273,0.00044272208,0.0007423394,0.00009438956],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0042951535,0.00012086205,0.00033084856,0.00016479578,0.00042748588,0.000083745115,0.00047184606,0.00010830706,0.00013364351],"category_scores_gemma":[0.00911888,0.000084553445,0.0001166521,0.00064420246,0.00060740596,0.0002730701,0.00004848383,0.000095685726,0.000031768755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003204932,0.0005810983,0.489363,0.000047552454,0.00005800156,0.0000031754355,0.054007556,0.000043226955,0.0003604849,0.0043122796,0.008036892,0.44286624],"study_design_scores_gemma":[0.00078964577,0.0003261538,0.93923426,0.0011165141,0.000038790004,0.0000029826022,0.017973138,0.0001471368,0.00016702348,0.00086294743,0.03906417,0.0002772313],"about_ca_topic_score_codex":0.00020546079,"about_ca_topic_score_gemma":0.00019544212,"teacher_disagreement_score":0.44987127,"about_ca_system_score_codex":0.00008790921,"about_ca_system_score_gemma":0.0002653102,"threshold_uncertainty_score":0.9992277},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.016373503810087654,"score_gpt":0.2775932834170432,"score_spread":0.2612197796069555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808948407","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17106046,0.000043276028,0.82259244,0.000050527753,0.0040969774,0.0005780369,0.000004256241,0.00021115929,0.0013628748],"genre_scores_gemma":[0.9551047,9.801231e-7,0.04304352,0.00021385348,0.0009932016,0.000030539726,0.000010420426,0.000025486639,0.0005772684],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966371,0.000097817625,0.0009277909,0.0008279099,0.0009799429,0.0005294213],"domain_scores_gemma":[0.99739814,0.0005382073,0.0003265966,0.0011314988,0.0003884259,0.00021713541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020440407,0.00025759515,0.00039051255,0.00026030818,0.000468593,0.00045948275,0.001091208,0.0001486857,0.000022703302],"category_scores_gemma":[0.00027138315,0.0001960243,0.00014476087,0.00092799444,0.00007433226,0.000024474328,0.000582581,0.00010397416,0.00014223353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014602146,0.000078091616,0.0012259844,0.00004284758,0.00005554024,0.000024947583,0.0008129798,0.66008705,0.000015049466,0.04235002,0.17237127,0.12279017],"study_design_scores_gemma":[0.000553003,0.00035527037,0.0023702479,0.00017808098,0.000017556526,0.00005388684,0.000041604053,0.93609387,0.000015963766,0.0031124796,0.056971624,0.00023643227],"about_ca_topic_score_codex":0.000022949562,"about_ca_topic_score_gemma":0.0000061329133,"teacher_disagreement_score":0.78404427,"about_ca_system_score_codex":0.00009311157,"about_ca_system_score_gemma":0.0000760159,"threshold_uncertainty_score":0.7993639},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.08523670504956499,"score_gpt":0.40288647846279824,"score_spread":0.31764977341323325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810318119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59397537,0.0037783214,0.03869495,0.0047852844,0.031630334,0.00697504,0.0005249859,0.0010374708,0.31859824],"genre_scores_gemma":[0.9436051,0.00077952264,0.027167065,0.0010351042,0.0025217629,0.00012752775,0.00015965599,0.000067513676,0.02453672],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99606985,0.0011702371,0.00089429854,0.0004909995,0.00090654846,0.00046809172],"domain_scores_gemma":[0.9965756,0.0012885489,0.0004271268,0.0004005202,0.00084826007,0.00045993377],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007920405,0.00020462507,0.00052211067,0.00015507796,0.00062391325,0.00038120258,0.0004075176,0.00027359978,0.00037464628],"category_scores_gemma":[0.015532465,0.00017851892,0.00010559706,0.0011259918,0.00036302378,0.00033573897,0.00007342666,0.0001827806,0.0012305988],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110969006,0.00028779154,0.055806067,0.00013629248,0.0000652936,0.000022798367,0.05036815,0.0000029649807,0.0003728131,0.0036463942,0.24964929,0.6395312],"study_design_scores_gemma":[0.00048881065,0.00009656027,0.005278911,0.00050407206,0.00002425253,0.0000057957895,0.009198023,0.00027722752,0.000015687578,0.0004453122,0.98334706,0.0003183019],"about_ca_topic_score_codex":0.001740704,"about_ca_topic_score_gemma":0.003844945,"teacher_disagreement_score":0.7336978,"about_ca_system_score_codex":0.00012953432,"about_ca_system_score_gemma":0.000503722,"threshold_uncertainty_score":0.99954706},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Brock University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.04152165827660666,"score_gpt":0.30132253182151286,"score_spread":0.2598008735449062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904467883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012182652,0.00003221168,0.9570084,0.00038943384,0.004821694,0.0006737462,0.000013383301,0.001163331,0.03467954],"genre_scores_gemma":[0.96265596,0.0000021806834,0.036032237,0.00030952189,0.00042485632,0.00010727189,0.000024204413,0.000026080384,0.00041767373],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967343,0.0003067718,0.0010894685,0.000813595,0.00060953415,0.0004463019],"domain_scores_gemma":[0.9970834,0.00025346648,0.00042180042,0.0015684745,0.00043632658,0.00023650947],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018554194,0.00028391735,0.00048875913,0.0003842837,0.00030062077,0.00062563637,0.0011825303,0.00019497129,0.00014354015],"category_scores_gemma":[0.000057929057,0.00023459403,0.0001595061,0.0006855359,0.0000430465,0.00065303437,0.00023934404,0.00013925173,0.0009938686],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005557143,0.00017326989,0.009483305,0.00022609906,0.000051933377,0.00006641918,0.00049068296,0.0000028480392,0.0001948677,0.040692657,0.51747626,0.4310861],"study_design_scores_gemma":[0.00059415813,0.0003263778,0.0005048754,0.00024776984,0.000006935527,0.00017457454,0.00022909064,0.1569357,0.0011225704,0.00026557656,0.8392243,0.00036807248],"about_ca_topic_score_codex":0.00036196676,"about_ca_topic_score_gemma":0.00004593626,"teacher_disagreement_score":0.9614377,"about_ca_system_score_codex":0.00012920085,"about_ca_system_score_gemma":0.00017067921,"threshold_uncertainty_score":0.999784},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.012005630893697375,"score_gpt":0.25548859207335467,"score_spread":0.2434829611796573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991582200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6159422,0.00009733123,0.37866804,0.000015544452,0.0027342723,0.0010183806,0.00014158266,0.00044981597,0.0009328537],"genre_scores_gemma":[0.9906131,0.000012793195,0.008386517,0.00002390933,0.00013533914,0.00015976903,0.00020709075,0.00007621762,0.00038527313],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99728143,0.000021650503,0.0012470252,0.00050748436,0.00052243454,0.0004200006],"domain_scores_gemma":[0.99822754,0.00051937345,0.00015551405,0.0005994465,0.0003030741,0.00019506623],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011196574,0.00030091414,0.0006364567,0.0004354082,0.0001544597,0.00020167136,0.0002142071,0.00022210955,0.0001521526],"category_scores_gemma":[0.000077449266,0.00028880275,0.00018106087,0.0005554016,0.000021583159,0.00035681974,0.00001831995,0.00015778496,0.00037766274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001103602,0.00047503045,0.23076443,0.0072829053,0.0016511662,0.00016987846,0.011753198,0.34568202,0.035532344,0.052964665,0.017108485,0.29551226],"study_design_scores_gemma":[0.010375723,0.0005461872,0.034473572,0.0023308264,0.00054422073,0.000365489,0.015220733,0.8477258,0.0019984723,0.00037417453,0.08342799,0.002616826],"about_ca_topic_score_codex":0.000017445369,"about_ca_topic_score_gemma":0.000015922378,"teacher_disagreement_score":0.5020438,"about_ca_system_score_codex":0.00013844429,"about_ca_system_score_gemma":0.000059438677,"threshold_uncertainty_score":0.9999564},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_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","score_opus":0.13200716065865392,"score_gpt":0.35189182262527685,"score_spread":0.21988466196662293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010728474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66790557,0.0033022766,0.00067908334,0.013064574,0.002227627,0.0051003713,0.0001606249,0.00017287604,0.30738702],"genre_scores_gemma":[0.9962178,0.0010923843,0.000122027144,0.00071884197,0.00033854606,0.00011963769,0.000037698952,0.000009684149,0.0013434008],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99663687,0.001294052,0.0007326616,0.00031990345,0.0007147728,0.00030175026],"domain_scores_gemma":[0.9984208,0.0008892532,0.00020214457,0.0002698373,0.00007511091,0.00014287696],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0069836634,0.000116851035,0.00034886904,0.00007768444,0.00012130445,0.00017757314,0.00057845627,0.00011680809,0.00019582825],"category_scores_gemma":[0.008543685,0.00008660713,0.000060029677,0.0010163593,0.00007926843,0.00023942096,0.000038760518,0.00021836952,0.000156063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047979524,0.0006427383,0.079373896,0.00033412554,0.00001167228,0.00028602857,0.12898707,0.000016960958,0.000057793135,0.005001946,0.44771448,0.3370935],"study_design_scores_gemma":[0.000352476,0.000050248782,0.021482391,0.00033565788,0.00000430154,0.0000012964479,0.018771317,0.00018798708,3.1909042e-7,0.0003025358,0.95836365,0.00014782813],"about_ca_topic_score_codex":0.00069873995,"about_ca_topic_score_gemma":0.0007991948,"teacher_disagreement_score":0.51064914,"about_ca_system_score_codex":0.000082620085,"about_ca_system_score_gemma":0.00017198206,"threshold_uncertainty_score":0.9998078},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; 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","score_opus":0.022380652643875017,"score_gpt":0.23344403642920358,"score_spread":0.21106338378532857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122905330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8876588,0.000017724,0.0034388169,0.000036779013,0.0035835684,0.00029714926,0.0000071340423,0.000105087194,0.104854956],"genre_scores_gemma":[0.9971885,0.000001756523,0.00015025011,0.0014163168,0.0007345483,0.000028178969,0.000079694364,0.000012757804,0.00038797915],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987011,6.017475e-7,0.0005064855,0.00013172248,0.00029538944,0.0003647058],"domain_scores_gemma":[0.9993336,0.000034433397,0.00020626931,0.00028511224,0.00007972777,0.000060816652],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00043880544,0.00014469166,0.00019325649,0.00029075425,0.00013479951,0.0011713296,0.00024991127,0.000068176,0.00039581553],"category_scores_gemma":[0.00012213715,0.00012043145,0.00006770887,0.00029403548,0.000013202079,0.020390648,0.00019513999,0.000051328207,0.027436424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015140363,0.00017054813,0.12985222,0.00020192274,0.000033642158,0.000007883592,0.0016931338,0.00059697696,0.00004701967,0.07590129,0.70293736,0.088406585],"study_design_scores_gemma":[0.0002083882,0.000007606798,0.0049585365,0.0000326992,0.000004829355,0.000009249514,0.0038742488,0.00093557127,0.0000076195506,0.00028285122,0.98946977,0.00020864126],"about_ca_topic_score_codex":0.00013083944,"about_ca_topic_score_gemma":0.0000030050103,"teacher_disagreement_score":0.2865324,"about_ca_system_score_codex":0.000044784596,"about_ca_system_score_gemma":0.000009787257,"threshold_uncertainty_score":0.99986553},"labels":[],"label_agreement":null},{"id":"W3131720207","doi":"10.1016/j.dss.2021.113521","title":"The different effects of hardware and software on production interdependence in manufacturing","year":2021,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Software; Industrial organization; Supply chain; Production (economics); Productivity; Complementarity (molecular biology); Business; Computer science; Marketing; Economics; Microeconomics; Operating system","score_opus":0.014190682483645111,"score_gpt":0.2263525635778082,"score_spread":0.2121618810941631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131720207","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924723,0.00041011468,0.0010395271,0.00027359521,0.003867221,0.0005657401,9.991888e-7,0.000046775145,0.0013237182],"genre_scores_gemma":[0.9979411,0.000053884898,0.000019603256,0.0001458838,0.00027000654,0.000052552932,0.0000101950145,0.000015606134,0.0014911917],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99862194,0.000028818711,0.00038896338,0.00034126983,0.0004296839,0.00018931701],"domain_scores_gemma":[0.9991316,0.0002201989,0.00017420636,0.0003798259,0.00008157619,0.000012560729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043435497,0.00014779539,0.000226344,0.00017914681,0.00012246029,0.00022472219,0.00017359626,0.00004320228,0.00004744298],"category_scores_gemma":[0.00041731558,0.000099009536,0.00005288801,0.00014849544,0.000029831404,0.00027956042,0.0002590424,0.00010510734,0.000053282038],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071049127,0.0010242193,0.23060428,0.009177492,0.00025476256,0.0011604346,0.0009928442,0.0011125207,0.0022576167,0.014800329,0.115065835,0.62283915],"study_design_scores_gemma":[0.0036995893,0.00018685982,0.36501688,0.006416938,0.00013093498,0.00005992461,0.0068321037,0.0031495828,0.033743948,0.0052977204,0.574304,0.0011615409],"about_ca_topic_score_codex":0.00005451321,"about_ca_topic_score_gemma":0.00009519227,"teacher_disagreement_score":0.62167764,"about_ca_system_score_codex":0.000040169896,"about_ca_system_score_gemma":0.000008174652,"threshold_uncertainty_score":0.40374917},"labels":[],"label_agreement":null},{"id":"W3211925872","doi":"10.1016/j.dss.2021.113694","title":"An interface between natural language and abstract argumentation frameworks for real-time debate analysis","year":2021,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Argumentation theory; Argument (complex analysis); Computer science; Vision; A priori and a posteriori; Citizen journalism; Representation (politics); Order (exchange); Epistemology; Data science; Management science; Sociology; Political science; World Wide Web; Medicine; Engineering; Law","score_opus":0.017695079618758974,"score_gpt":0.3325738450469924,"score_spread":0.3148787654282334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211925872","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47686425,0.000186896,0.5220416,0.000039603645,0.00044701996,0.00025111134,0.000028927141,0.000071898656,0.00006866018],"genre_scores_gemma":[0.9831766,0.000014806451,0.015648587,0.0000306129,0.00015459195,0.000029436664,0.00026643605,0.000014052979,0.0006649092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793375,0.00011405718,0.0006483951,0.0006197474,0.0004395357,0.0002445222],"domain_scores_gemma":[0.9981435,0.0004814429,0.00031239126,0.0006771037,0.00022675861,0.00015878631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090258307,0.00017637096,0.0004363323,0.00024960312,0.00014076731,0.0005942294,0.00033913995,0.00020317185,0.00006189581],"category_scores_gemma":[0.00007854885,0.00015498715,0.00013729504,0.00047768443,0.000011552477,0.00074935355,0.0000810464,0.0001430365,0.00006214505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020886581,0.00065874297,0.14041637,0.0007081614,0.0036250006,0.00055946107,0.037199855,0.007629339,0.2069374,0.003423104,0.01883294,0.5798008],"study_design_scores_gemma":[0.0015819367,0.0002216383,0.22666879,0.00023305243,0.00037931502,0.0000739238,0.0018757473,0.7557019,0.009700204,0.00023812,0.0025088023,0.00081655354],"about_ca_topic_score_codex":0.00016899058,"about_ca_topic_score_gemma":0.00002821393,"teacher_disagreement_score":0.74807256,"about_ca_system_score_codex":0.000057478956,"about_ca_system_score_gemma":0.000043615793,"threshold_uncertainty_score":0.6320193},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.03898795988675024,"score_gpt":0.2724360636054454,"score_spread":0.23344810371869518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200343312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90705967,0.0000583429,0.09208769,0.00004663312,0.00028600782,0.0001950902,0.00005166779,0.00013367408,0.00008122973],"genre_scores_gemma":[0.99827605,0.000018323663,0.0009755753,0.000026287844,0.000016019965,0.000012559788,0.00010913915,0.000009185801,0.0005568394],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983948,0.00010696343,0.00040237175,0.00042779418,0.0004525481,0.00021555122],"domain_scores_gemma":[0.9987138,0.00030002574,0.00029436997,0.00021726207,0.00036156384,0.00011298617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005715874,0.00015271315,0.00031559725,0.0001853061,0.00017601509,0.00009247755,0.0001807568,0.0001082409,0.0000060215366],"category_scores_gemma":[0.0004410822,0.0001307005,0.00003906525,0.00040090186,0.00003778893,0.00032358657,0.00022114096,0.00018630583,0.00002902448],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002565408,0.000040289146,0.89466053,0.00005360738,0.000058606918,0.00002579862,0.0012263616,0.000039335482,0.0785081,0.00007939611,0.00011029828,0.025171991],"study_design_scores_gemma":[0.0008566561,0.00031014925,0.9277356,0.0006237319,0.000020227788,0.000054632368,0.000577843,0.028275492,0.04037305,0.00003280528,0.0009170523,0.0002227266],"about_ca_topic_score_codex":0.000054166776,"about_ca_topic_score_gemma":0.0000054039274,"teacher_disagreement_score":0.09121641,"about_ca_system_score_codex":0.000049682025,"about_ca_system_score_gemma":0.000055454777,"threshold_uncertainty_score":0.53298116},"labels":[],"label_agreement":null},{"id":"W4244116783","doi":"10.1016/s0167-9236(04)00236-2","title":"Agent-intermediated electronic markets in international freight transportation","year":2004,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Calgary","funders":"","keywords":"Profit (economics); Incentive; Investment (military); Supply and demand; Industrial organization; Microeconomics; Business; Economics; Commerce","score_opus":0.03448527064033319,"score_gpt":0.3431688922633434,"score_spread":0.3086836216230102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244116783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.781452,0.00009521792,0.206409,0.00070078124,0.0029321592,0.0006085122,0.00011207952,0.00011030702,0.007579957],"genre_scores_gemma":[0.99621826,0.000036704056,0.00024364922,0.00013007321,0.0001492715,0.00011090984,0.00013214818,0.000017995388,0.002961007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958034,0.00013758201,0.0014824292,0.000660966,0.0015474308,0.00036820315],"domain_scores_gemma":[0.99794626,0.0005743692,0.00040602058,0.0006132724,0.00030675658,0.00015331211],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031735888,0.00018791785,0.00032823495,0.0006955148,0.00012107272,0.00022077536,0.0009510581,0.00014487427,0.0028664514],"category_scores_gemma":[0.0005503679,0.0001519406,0.0001546564,0.0011032948,0.000067035086,0.00054898066,0.000029556386,0.0002281602,0.0031532391],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023841353,0.0022841766,0.08783981,0.00003082118,0.00026216448,0.0007123598,0.009848298,0.03340417,0.005958155,0.5182743,0.08733407,0.25166753],"study_design_scores_gemma":[0.003860129,0.00013885276,0.12972373,0.000119173725,0.000019471065,0.00014087859,0.0037050394,0.0018093175,0.0009828432,0.24877176,0.6101298,0.0005990114],"about_ca_topic_score_codex":0.00004810694,"about_ca_topic_score_gemma":0.00017483468,"teacher_disagreement_score":0.52279574,"about_ca_system_score_codex":0.00025825598,"about_ca_system_score_gemma":0.00018812291,"threshold_uncertainty_score":0.9980451},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.04183160110416032,"score_gpt":0.2790030572955186,"score_spread":0.2371714561913583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245238933","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2549637,0.0002682698,0.011953663,0.0024892783,0.0024613338,0.0016076536,0.000025687124,0.0002898672,0.7259405],"genre_scores_gemma":[0.99643594,0.000005443438,0.00035246363,0.0010078924,0.00043652486,0.00008472156,0.00003977688,0.00003088721,0.0016063501],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9971887,0.000023092874,0.00071279675,0.0004964007,0.0012430258,0.00033602343],"domain_scores_gemma":[0.99898547,0.00012653398,0.00028145572,0.00041530194,0.00016172155,0.000029490175],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011934837,0.00022266878,0.0002820053,0.00044482076,0.00020414783,0.0002375391,0.00027574154,0.00013101666,0.0005338993],"category_scores_gemma":[0.000119390366,0.00021475063,0.00011243403,0.0010845494,0.000033358432,0.0011969412,0.0001798352,0.00023457881,0.0060511124],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010555587,0.00020137081,0.07286076,0.000121280034,0.000029328408,0.00012155619,0.000395009,0.004379002,0.0000026141936,0.91728246,0.003901852,0.00059919874],"study_design_scores_gemma":[0.004679654,0.000021243648,0.5082708,0.00050365436,0.00009142719,0.000030911895,0.015655627,0.0013981146,0.000002020424,0.07134275,0.39722258,0.0007812242],"about_ca_topic_score_codex":0.0012006682,"about_ca_topic_score_gemma":0.00034782375,"teacher_disagreement_score":0.8459397,"about_ca_system_score_codex":0.00055456033,"about_ca_system_score_gemma":0.00003239913,"threshold_uncertainty_score":0.9947228},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.016178746247485658,"score_gpt":0.26766293278904807,"score_spread":0.2514841865415624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311548908","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8788135,0.00061467226,0.09590576,0.00030246878,0.004266985,0.00081812544,0.00007637711,0.0003743037,0.018827792],"genre_scores_gemma":[0.9976104,0.000033248198,0.0003422683,0.0013672713,0.00006033646,0.00007422428,0.00004195056,0.000011227546,0.00045907442],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99732184,0.00021340816,0.000690058,0.00044059844,0.00096679217,0.00036732835],"domain_scores_gemma":[0.9983755,0.00014837169,0.00025732297,0.00082416733,0.00013439282,0.0002602916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015011571,0.00019186926,0.0002961544,0.00023721544,0.00067893014,0.0004559614,0.0008121345,0.00006797657,0.00017043491],"category_scores_gemma":[0.000032326272,0.00018322913,0.00008444195,0.00044471418,0.000032006825,0.0007495638,0.0009309959,0.0003108913,0.00022052179],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029874744,0.0009547006,0.08585212,0.0004965795,0.00017871073,0.0022373754,0.06496043,0.0011244179,0.00011686588,0.28169507,0.29427323,0.26781178],"study_design_scores_gemma":[0.0051064375,0.0009277813,0.045129538,0.00012256911,0.000026318863,0.0036471272,0.0030346748,0.082868494,0.000120359255,0.002138411,0.85485876,0.0020195132],"about_ca_topic_score_codex":0.000022833457,"about_ca_topic_score_gemma":0.000012230994,"teacher_disagreement_score":0.56058556,"about_ca_system_score_codex":0.00011283974,"about_ca_system_score_gemma":0.00015187894,"threshold_uncertainty_score":0.74718666},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Sustainability; Rank (graph theory); Fuzzy logic; Knowledge management; Operations research; Artificial intelligence; Engineering; Ecology; Mathematics","score_opus":0.12090384165679152,"score_gpt":0.3171502725747435,"score_spread":0.19624643091795196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322724432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97783595,0.000021882921,0.01652328,0.000005711476,0.0003983041,0.00061654276,0.000013594748,0.000040290302,0.0045444546],"genre_scores_gemma":[0.9988285,0.0000018237353,0.0006609703,0.000010619828,0.00012121849,0.000039154245,0.00030618117,0.00001604977,0.000015492167],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798566,0.000024583853,0.00093179697,0.000339725,0.0005457782,0.0001724375],"domain_scores_gemma":[0.99849993,0.00008993242,0.00068507704,0.0002561912,0.000455888,0.000012994533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005502888,0.0001540884,0.00039428,0.0009969207,0.000056832967,0.00009981212,0.00021740352,0.00009121876,0.00012774495],"category_scores_gemma":[0.00016324133,0.00014266095,0.00011165611,0.00074080145,0.000025098681,0.0016664435,0.000028176357,0.00009555562,0.000040325987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033206848,0.00029328576,0.626619,0.0012289534,0.00016309503,0.00001366955,0.0008463415,0.3220181,0.001691092,0.01457659,0.0001906262,0.032027204],"study_design_scores_gemma":[0.001337497,0.000010756874,0.06326171,0.00026077108,0.00013303917,9.4518515e-7,0.0014679845,0.92831427,0.0003889028,0.004241668,0.00040807755,0.00017434813],"about_ca_topic_score_codex":0.0012127964,"about_ca_topic_score_gemma":0.000120023295,"teacher_disagreement_score":0.60629624,"about_ca_system_score_codex":0.00008534818,"about_ca_system_score_gemma":0.000093397306,"threshold_uncertainty_score":0.5817545},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; 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","score_opus":0.0487975229589617,"score_gpt":0.24193744231023775,"score_spread":0.19313991935127606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387142828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7957782,0.00006537233,0.0067169233,0.00078100944,0.0037487892,0.002939506,0.000027345914,0.0012480232,0.18869479],"genre_scores_gemma":[0.9956531,0.0000065597137,0.000076345816,0.0013677907,0.00033287532,0.00020258552,0.0007007856,0.000034982782,0.0016249714],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99774414,0.000007681442,0.0007126178,0.000319403,0.0007776004,0.00043854167],"domain_scores_gemma":[0.9989892,0.00006781776,0.00029558595,0.00051784876,0.000098801516,0.000030723],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011092693,0.00024814505,0.00030853285,0.001226831,0.00012890698,0.00047132734,0.00041830077,0.00008625732,0.0006565598],"category_scores_gemma":[0.00005384247,0.00019770525,0.000067695815,0.0012162997,0.00002224861,0.0021505735,0.0002125019,0.0001325904,0.0035907635],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008807921,0.0002713053,0.42788738,0.0014514608,0.00010765575,0.00029419034,0.00075053726,0.032844994,0.000017839657,0.0195691,0.39969558,0.116229154],"study_design_scores_gemma":[0.0026069186,0.000057148067,0.052901935,0.00048008314,0.000029308365,0.0000046736104,0.0037127088,0.13103423,0.000009240279,0.0002570675,0.80845404,0.00045262233],"about_ca_topic_score_codex":0.0005682545,"about_ca_topic_score_gemma":0.00013815306,"teacher_disagreement_score":0.4087585,"about_ca_system_score_codex":0.00011602825,"about_ca_system_score_gemma":0.00002708665,"threshold_uncertainty_score":0.99718505},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Influencer marketing; Variation (astronomy); Computer science; Time horizon; Markov decision process; Advertising; Marketing; Business; Markov process; Marketing management","score_opus":0.14037542516324128,"score_gpt":0.36577335692604773,"score_spread":0.22539793176280645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389855353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9525852,0.000024426861,0.0008332604,0.0010057841,0.005369064,0.0015469523,0.00027718514,0.0003186528,0.03803944],"genre_scores_gemma":[0.9907132,0.000043041404,0.000064040374,0.00022157474,0.0013215988,0.0002722705,0.00007869825,0.000037089765,0.0072484803],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.99617237,0.0001230906,0.000792097,0.0004281275,0.001683115,0.0008012291],"domain_scores_gemma":[0.9911714,0.0077517787,0.00032576153,0.0002513036,0.00026146218,0.00023825355],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00444503,0.0002648831,0.0005098383,0.00017682902,0.0016766558,0.00077096984,0.0006533751,0.00028654342,0.00013053679],"category_scores_gemma":[0.0033891478,0.00016697601,0.00024912995,0.0006301616,0.00045242545,0.00053423276,0.000092243,0.00023015276,0.00027767266],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022671926,0.00015412176,0.002813498,0.00011617282,0.00026387558,0.00021624277,0.28449476,0.000976858,0.00005389189,0.08847349,0.49059826,0.12957163],"study_design_scores_gemma":[0.0009803558,0.0002480833,0.0024106782,0.00024037041,0.000032719883,0.000004446433,0.6673591,0.00023862068,0.000009615555,0.0014265806,0.32665455,0.00039484783],"about_ca_topic_score_codex":0.00052039744,"about_ca_topic_score_gemma":0.0020303696,"teacher_disagreement_score":0.38286436,"about_ca_system_score_codex":0.00022839222,"about_ca_system_score_gemma":0.00083065836,"threshold_uncertainty_score":0.999623},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.14217655467870427,"score_gpt":0.4376561759686145,"score_spread":0.29547962128991023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393353640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10474695,0.004909479,0.86607695,0.002841507,0.00593382,0.0028055569,0.007854977,0.0008922317,0.0039385455],"genre_scores_gemma":[0.95064116,0.0001304378,0.037969712,0.00092513824,0.0015421015,0.0006247809,0.0063612815,0.000118821656,0.0016865873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9910005,0.0012263011,0.0025139411,0.0014164273,0.0030267064,0.0008161369],"domain_scores_gemma":[0.9906896,0.00460523,0.00062156684,0.0008821104,0.0026793398,0.0005221527],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002081803,0.0004773424,0.0010289041,0.0013092617,0.0013895523,0.00019923942,0.0005507481,0.0006661205,0.0010870273],"category_scores_gemma":[0.00043673586,0.0004599102,0.00030302026,0.0029959609,0.000056155564,0.0007122217,0.0002971685,0.0012764375,0.0026942703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030390653,0.00009933802,0.21928687,0.0018577409,0.0014357968,0.000031900872,0.02323542,0.65709054,0.0000074935583,0.005374093,0.08801731,0.0032595813],"study_design_scores_gemma":[0.00081065303,0.000056896126,0.038320303,0.002011498,0.00023917493,0.000018286906,0.0062462213,0.8997446,3.927286e-7,0.008458508,0.04360326,0.00049022],"about_ca_topic_score_codex":0.014982862,"about_ca_topic_score_gemma":0.0012374267,"teacher_disagreement_score":0.84589416,"about_ca_system_score_codex":0.001437335,"about_ca_system_score_gemma":0.0017184537,"threshold_uncertainty_score":0.9999105},"labels":[],"label_agreement":null},{"id":"W4395690157","doi":"10.1016/j.dss.2024.114235","title":"Freedom of speech or freedom of reach? Strategies for mitigating malicious content in social networks","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Content (measure theory); Degrees of freedom (physics and chemistry); Computer science; Mathematics; Physics","score_opus":0.10195658717083465,"score_gpt":0.37052321647517644,"score_spread":0.2685666293043418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395690157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8079217,0.0011630001,0.0765977,0.00073486584,0.00767141,0.0035607533,0.00043070348,0.00024788507,0.10167198],"genre_scores_gemma":[0.99664575,0.00003679665,0.00075223425,0.000029979132,0.00056717213,0.0000125778115,0.000022588492,0.0000145832,0.0019183484],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.99757785,0.0001123355,0.0011162382,0.00017433768,0.00069737085,0.0003218436],"domain_scores_gemma":[0.99838376,0.0007472944,0.000320051,0.00015016002,0.0002985493,0.00010017247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027613682,0.00012663192,0.00043933114,0.00023112106,0.00015138196,0.0002231311,0.00025525573,0.00020449542,0.0002726056],"category_scores_gemma":[0.0005430532,0.00009828129,0.00014159898,0.0004759317,0.000168485,0.00040278037,0.00003348927,0.00011606622,0.00001367236],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006782522,0.00017297959,0.0018268384,0.0012651817,0.00018077932,0.00008883429,0.23083478,0.0043703755,0.000978867,0.31289494,0.3335225,0.11318566],"study_design_scores_gemma":[0.0032099742,0.00075875723,0.0028586548,0.0028516657,0.00008243722,0.000043347813,0.70725965,0.07530706,0.00021276381,0.0037013534,0.20296098,0.00075335434],"about_ca_topic_score_codex":0.0037847895,"about_ca_topic_score_gemma":0.0016528855,"teacher_disagreement_score":0.47642487,"about_ca_system_score_codex":0.000090988484,"about_ca_system_score_gemma":0.0005515348,"threshold_uncertainty_score":0.57214946},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.24515258956083102,"score_gpt":0.5202787027126053,"score_spread":0.2751261131517743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396520848","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087186575,0.0011807219,0.4327336,0.0010306439,0.014894145,0.0043350905,0.000050958803,0.00045799816,0.45813027],"genre_scores_gemma":[0.9970158,0.000065778106,0.00035163458,0.000015605778,0.00019538288,0.00009487295,0.0000045550532,0.0000081103235,0.0022482711],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959575,0.00044707544,0.00069067784,0.00027724338,0.0020889603,0.00053855596],"domain_scores_gemma":[0.99846697,0.00073842896,0.000046223602,0.0002133792,0.0003966889,0.00013832652],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0279676,0.00007545094,0.00014368122,0.0010102924,0.000786376,0.0010242573,0.00043526635,0.00007089348,0.0006504933],"category_scores_gemma":[0.00043260216,0.00006476,0.000034734116,0.003032291,0.00035673214,0.0014638056,0.000031357962,0.00015543122,0.0011833763],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035993082,0.000023637427,0.000924662,0.0000831875,0.000005671822,0.000051656756,0.14014368,0.00016816758,0.00032739568,0.75209916,0.035626076,0.070510715],"study_design_scores_gemma":[0.00022101855,0.00009005814,0.0005400545,0.00031478785,0.000002238478,0.000011040444,0.08557891,0.0024828732,0.00012416841,0.005998455,0.90446967,0.00016674612],"about_ca_topic_score_codex":0.0018244308,"about_ca_topic_score_gemma":0.00022240811,"teacher_disagreement_score":0.9098292,"about_ca_system_score_codex":0.0004386241,"about_ca_system_score_gemma":0.0013222239,"threshold_uncertainty_score":0.99959433},"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,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Blockchain; Resilience (materials science); Protocol (science); Computer science; Computer security; Medicine","score_opus":0.06621060339544389,"score_gpt":0.3109844650924485,"score_spread":0.2447738616970046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398768689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31931278,0.0010455815,0.5776547,0.0010440488,0.0024056924,0.09439507,0.000026762686,0.0010735079,0.0030418397],"genre_scores_gemma":[0.9440633,0.0000041860358,0.026619013,0.0004815393,0.0018255317,0.02443139,0.000053641477,0.00014940441,0.0023719845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970654,0.000038536553,0.00075046386,0.0008863706,0.00066172215,0.00059745944],"domain_scores_gemma":[0.9982647,0.00078176736,0.00027721375,0.00043364085,0.00019221913,0.000050474286],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016446026,0.0003622757,0.00044566928,0.0006057268,0.00054372073,0.0011050438,0.0003153834,0.00020140439,0.0001608157],"category_scores_gemma":[0.0005921319,0.0002874416,0.00014464725,0.00080426736,0.00012767085,0.00020516598,0.00020546924,0.00029499305,0.00008099336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015043895,0.000709757,0.039382797,0.014748962,0.0002973853,0.0012353974,0.00086985604,0.5165779,0.00031848517,0.07673002,0.018861454,0.32876357],"study_design_scores_gemma":[0.0005044805,0.000043186155,0.00016750676,0.00071721175,0.00005646913,0.000015472631,0.0028785383,0.7201515,0.000014573548,0.0015227715,0.27360374,0.00032458804],"about_ca_topic_score_codex":0.00019344779,"about_ca_topic_score_gemma":0.000026267815,"teacher_disagreement_score":0.62475055,"about_ca_system_score_codex":0.00007501511,"about_ca_system_score_gemma":0.00007795263,"threshold_uncertainty_score":0.9999578},"labels":[],"label_agreement":null},{"id":"W4402469884","doi":"10.1016/j.dss.2024.114327","title":"Effective presentation of ontological overlap of multiple conceptual models","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Einstein Stiftung Berlin","keywords":"Presentation (obstetrics); Computer science; Epistemology; Philosophy; Medicine","score_opus":0.04705258154734277,"score_gpt":0.3108324587479665,"score_spread":0.26377987720062374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402469884","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24292243,0.0009829358,0.75246406,0.000021429509,0.0014166941,0.0004066769,0.000012902188,0.00010823257,0.0016646422],"genre_scores_gemma":[0.9945576,0.000013512008,0.00521134,0.000008628822,0.000037649395,0.000033668224,0.0000041529556,0.0000054777897,0.00012796672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982019,0.00012484609,0.00058410823,0.00036559423,0.000556828,0.00016672675],"domain_scores_gemma":[0.9973082,0.0019076503,0.00014588716,0.00041891934,0.00016744182,0.000051887968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005836393,0.0001195502,0.00040524526,0.00015727736,0.000026079675,0.000064035565,0.0004485396,0.000111460045,0.000015802067],"category_scores_gemma":[0.00024292035,0.000084900115,0.00013397579,0.00029602967,0.00010991766,0.00047156605,0.00016445683,0.00007817489,0.00003513217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002821581,0.0004362819,0.029897075,0.0007740384,0.00032212507,0.00046659444,0.01661633,0.013716638,0.013432775,0.7407682,0.021111868,0.16217592],"study_design_scores_gemma":[0.00081692805,0.0006444155,0.011555485,0.00040983254,0.000024889403,0.000110935645,0.0020340641,0.96094954,0.009788226,0.01108345,0.002332623,0.00024959038],"about_ca_topic_score_codex":0.00016537936,"about_ca_topic_score_gemma":0.000008596734,"teacher_disagreement_score":0.9472329,"about_ca_system_score_codex":0.000026234091,"about_ca_system_score_gemma":0.00007091679,"threshold_uncertainty_score":0.3462126},"labels":[],"label_agreement":null},{"id":"W4405454922","doi":"10.1016/j.dss.2024.114384","title":"Unveiling the metaverse: A comparison of multiple environments","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Metaverse; Computer science; Astrobiology; Human–computer interaction; Physics; Virtual reality","score_opus":0.05603707915127067,"score_gpt":0.3372180401326203,"score_spread":0.28118096098134965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405454922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02678283,0.00083053374,0.96988976,0.00013989076,0.0007126276,0.0003081111,0.000016630798,0.000062773826,0.001256817],"genre_scores_gemma":[0.9970512,0.000021110754,0.0021254069,0.000032206233,0.000035233013,0.00002670667,0.000005690155,0.000007787667,0.00069468684],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99840254,0.000061374616,0.0005142982,0.00028933535,0.0005634937,0.00016898807],"domain_scores_gemma":[0.99834144,0.0006305119,0.00010587599,0.00081393204,0.000023426908,0.0000847836],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008289341,0.00010274705,0.00021834816,0.000096722724,0.00009863212,0.00023452459,0.0007215113,0.000050853694,0.000043904834],"category_scores_gemma":[0.000088533365,0.00006359685,0.000094202136,0.000415049,0.00003953251,0.0002776837,0.00018819413,0.00010252268,0.00083388225],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000374455,0.00065571076,0.0060528573,0.00023789615,0.00036938512,0.000057355235,0.0134198675,0.01382141,0.01948297,0.15514395,0.18406229,0.6066589],"study_design_scores_gemma":[0.00012578412,0.00006574905,0.0012483475,0.0000666122,0.000012239144,0.000021744578,0.0004118077,0.40545774,0.0018378451,0.00028270268,0.5903716,0.00009778756],"about_ca_topic_score_codex":0.00006784046,"about_ca_topic_score_gemma":0.0000037422246,"teacher_disagreement_score":0.97026837,"about_ca_system_score_codex":0.000039241215,"about_ca_system_score_gemma":0.000056945835,"threshold_uncertainty_score":0.9999441},"labels":[],"label_agreement":null},{"id":"W4405635425","doi":"10.1016/j.dss.2024.114389","title":"The implications of account suspensions on online discussion platforms","year":2024,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Chulalongkorn University","keywords":"Computer science","score_opus":0.025527056483968833,"score_gpt":0.2984681075807626,"score_spread":0.27294105109679373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405635425","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15316223,0.0009027329,0.8185124,0.006907465,0.012489741,0.0013166313,0.00010423396,0.0009011857,0.0057033775],"genre_scores_gemma":[0.9957034,0.00010194802,0.0010346532,0.000057580197,0.00013988427,0.000034952933,0.00002043938,0.000015611267,0.0028915205],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982057,0.000026163372,0.00056035485,0.00038806399,0.0005721765,0.00024753282],"domain_scores_gemma":[0.9980863,0.0005082156,0.00011193628,0.001044331,0.00013985431,0.00010936767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000756783,0.00013974072,0.00017825657,0.00019282427,0.00034632802,0.00038153064,0.0007542743,0.00008561555,0.000022316113],"category_scores_gemma":[0.000100737525,0.00006168269,0.00012921807,0.00069705193,0.00003730456,0.00032299242,0.00017226514,0.00018210156,0.00045069386],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037081252,0.00015049952,0.00025500573,0.000033943237,0.000049598257,0.000047116897,0.00046917427,0.00039860388,0.0036712897,0.21319875,0.07965636,0.70203257],"study_design_scores_gemma":[0.0003523415,0.0005551177,0.007218302,0.0007030253,0.000022103639,0.00039359025,0.00057944225,0.056820918,0.002036189,0.022726104,0.90819216,0.00040073937],"about_ca_topic_score_codex":0.000024034229,"about_ca_topic_score_gemma":0.000036177396,"teacher_disagreement_score":0.84254116,"about_ca_system_score_codex":0.00006372145,"about_ca_system_score_gemma":0.00012988306,"threshold_uncertainty_score":0.5792908},"labels":[],"label_agreement":null},{"id":"W4406821531","doi":"10.1016/j.dss.2025.114403","title":"Disclosure of IT-related risk factors in corporate filings","year":2025,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Risk Management in Financial Firms","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"University of North Carolina at Charlotte; McMaster University","keywords":"Business; Accounting","score_opus":0.0228392491163507,"score_gpt":0.2485236504272297,"score_spread":0.22568440131087902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406821531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9600885,0.00011843906,0.002425383,0.0001252818,0.0031266746,0.00078685535,0.000023251107,0.000105483494,0.033200167],"genre_scores_gemma":[0.99518,0.000046670844,0.00004833192,0.00015020788,0.000091598806,0.000024413961,0.00008909284,0.000027731467,0.0043419166],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973225,0.000030247906,0.0013292776,0.0004630524,0.0005253237,0.00032962044],"domain_scores_gemma":[0.9977995,0.00021018878,0.0011879534,0.0005683046,0.00021995291,0.000014089263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014243515,0.0002693791,0.00060063624,0.001106236,0.00011163041,0.0001937473,0.0005247519,0.0001845641,0.00020782785],"category_scores_gemma":[0.00055800384,0.00022482943,0.00015743502,0.002112794,0.00005917993,0.0007374275,0.00031508395,0.00022797918,0.00041706924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007212018,0.000118716955,0.9090345,0.0002649538,0.000048773945,0.00003907417,0.00008126491,0.0018560387,0.0000451864,0.015300271,0.069551185,0.00358794],"study_design_scores_gemma":[0.002228951,0.000036285513,0.5435369,0.0011775444,0.00017233292,9.169264e-7,0.0019087184,0.013876642,0.00007542233,0.02254249,0.41378,0.0006638099],"about_ca_topic_score_codex":0.0021052824,"about_ca_topic_score_gemma":0.00014596141,"teacher_disagreement_score":0.3654976,"about_ca_system_score_codex":0.000051706804,"about_ca_system_score_gemma":0.000040630795,"threshold_uncertainty_score":0.91682786},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Sense (electronics); Computer science; Business; Microeconomics; Economics; Engineering","score_opus":0.01986971340207341,"score_gpt":0.33434959871157927,"score_spread":0.3144798853095059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409235722","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97012347,0.00010783289,0.000009966718,0.00066361687,0.0010950146,0.00039039672,0.000028199132,0.000017568726,0.027563926],"genre_scores_gemma":[0.9988121,0.00006063931,0.0000067575374,0.000085669344,0.00004433124,0.000022189217,0.000008584661,0.000005519055,0.00095422525],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984392,0.0006504439,0.00029062072,0.0001710364,0.00027886743,0.00016983766],"domain_scores_gemma":[0.9928156,0.006839738,0.000106587715,0.00013384121,0.000038714305,0.0000654972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018627737,0.00010084878,0.0002787692,0.00012445249,0.00028139443,0.00012624411,0.000100287456,0.00005502462,0.0000039100014],"category_scores_gemma":[0.0013745673,0.000071418996,0.000043662847,0.00020816125,0.00021000521,0.000060036145,0.00006494509,0.000120052304,0.000003949584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024357249,0.00008507525,0.73753935,0.00009653827,0.000090430236,0.000039120256,0.044008095,0.000009562282,0.00004269244,0.003559689,0.007446614,0.2068393],"study_design_scores_gemma":[0.007059966,0.0015312531,0.48208445,0.007838848,0.00024210998,0.00002057894,0.34556717,0.00046853523,0.00014404887,0.0034476742,0.1506078,0.0009875798],"about_ca_topic_score_codex":0.006320468,"about_ca_topic_score_gemma":0.012984042,"teacher_disagreement_score":0.30155906,"about_ca_system_score_codex":0.00006442334,"about_ca_system_score_gemma":0.000038995924,"threshold_uncertainty_score":0.95546997},"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,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_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","score_opus":0.013893233210944725,"score_gpt":0.26733405558548146,"score_spread":0.25344082237453674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410081179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94280577,0.00011720836,0.011647635,0.0001911404,0.0014609952,0.0012215731,0.000022031,0.00012473676,0.04240889],"genre_scores_gemma":[0.99637437,0.0000071917966,0.000051872867,0.0002505547,0.0003400189,0.0000877979,0.00013400866,0.000020508456,0.0027336918],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99820465,0.000017608478,0.0006087956,0.00044708783,0.00043397152,0.00028785988],"domain_scores_gemma":[0.9991945,0.000114415656,0.00018493694,0.00022970529,0.00026024308,0.000016173799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006295397,0.00020998438,0.0003164416,0.00053680467,0.00016235303,0.00043784667,0.00015595707,0.00008237409,0.00021321735],"category_scores_gemma":[0.000089415225,0.00016701048,0.000058510257,0.00073922426,0.000049370938,0.001330422,0.000026068996,0.0001718918,0.00019425081],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012149259,0.00025316805,0.93258893,0.0004676856,0.00009365482,0.00007061305,0.0008539825,0.0005437804,0.0014254554,0.0014948385,0.01118814,0.049804833],"study_design_scores_gemma":[0.0061688875,0.000088988396,0.93319297,0.0014796634,0.00013717831,0.000027354727,0.0072580427,0.011195515,0.00034820448,0.00037088952,0.039177723,0.0005546072],"about_ca_topic_score_codex":0.0008711715,"about_ca_topic_score_gemma":0.0005170808,"teacher_disagreement_score":0.053568564,"about_ca_system_score_codex":0.000111021116,"about_ca_system_score_gemma":0.00007100664,"threshold_uncertainty_score":0.681049},"labels":[],"label_agreement":null},{"id":"W4411635343","doi":"10.1016/j.dss.2025.114499","title":"Impact of categorization autonomy on effective use and adoption intentions","year":2025,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ted Rogers Centre for Heart Research","funders":"","keywords":"Categorization; Autonomy; Psychology; Computer science; Political science; Artificial intelligence","score_opus":0.07159805148784999,"score_gpt":0.4032096445829803,"score_spread":0.33161159309513033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411635343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85905963,0.00003644737,0.13817799,0.00006438758,0.00089175365,0.0006088999,0.00004656446,0.000087662935,0.0010266863],"genre_scores_gemma":[0.99758506,0.000010062313,0.00031465097,0.000028414206,0.000013731458,0.000058226913,0.000017811271,0.000008908598,0.001963146],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99730295,0.00021612235,0.00097216904,0.0005219277,0.0008051137,0.00018174687],"domain_scores_gemma":[0.9964599,0.0014241345,0.00040409982,0.0007405507,0.0008826981,0.000088635876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017745618,0.00018078787,0.0004355722,0.001439704,0.00015151137,0.0002548858,0.00033186201,0.00024421685,0.00012574422],"category_scores_gemma":[0.002355949,0.00012685792,0.00019680917,0.0012723382,0.000115522555,0.00049401796,0.00012576162,0.00017843461,0.00014162675],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014671715,0.00018504745,0.9156775,0.0000060702173,0.00004915559,0.0000069762295,0.00016337249,0.00046493585,0.0009732563,0.018502671,0.009393476,0.054430827],"study_design_scores_gemma":[0.0006153374,0.00031464524,0.99061334,0.000082271734,0.000026723732,0.000016826236,0.00035994814,0.0014910762,0.00012099294,0.002438154,0.003808453,0.00011225973],"about_ca_topic_score_codex":0.00011049098,"about_ca_topic_score_gemma":0.000013522004,"teacher_disagreement_score":0.13852544,"about_ca_system_score_codex":0.00017646012,"about_ca_system_score_gemma":0.00020365937,"threshold_uncertainty_score":0.51731163},"labels":[],"label_agreement":null}]}