{"meta":{"query_hash":"228e5648a632","filters":{"venue":"Applied economics and policy studies"},"cohort_total":26,"direct_labels_cover":0,"predictions_cover":26,"exported":26,"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/228e5648a632","api":"https://metacan.xera.ac/api/v1/cohort?venue=Applied+economics+and+policy+studies"},"results":[{"id":"W4285295173","doi":"10.1007/978-981-19-0564-3_26","title":"Dynamic Capabilities: A Theoretical Review and Reflection","year":2022,"lang":"en","type":"review","venue":"Applied economics and policy studies","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Dynamic capabilities; Connotation; Reflection (computer programming); Computer science; Mechanism (biology); Knowledge management; Management science; Engineering; Epistemology","score_opus":0.05434628441868133,"score_gpt":0.33966735780605617,"score_spread":0.28532107338737484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285295173","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000752671,0.9939202,0.0002471856,0.0046351263,0.00029341114,0.0000059268873,0.000033734737,0.000004229571,0.0007849522],"genre_scores_gemma":[0.0014408673,0.99590474,0.00027473035,0.001887626,0.00031795874,0.000014013512,0.000026952594,0.0000029761634,0.00013015604],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975448,0.0007057698,0.0004829102,0.00038142584,0.00072221656,0.00016285968],"domain_scores_gemma":[0.97229844,0.021498801,0.0016583931,0.00056117825,0.003526546,0.0004565707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008935602,0.0010909998,0.0029195885,0.015067602,0.0006571421,0.005338306,0.0019692848,0.0032988535,0.003985466],"category_scores_gemma":[0.017974094,0.0007405458,0.0011008311,0.015758758,0.0037787473,0.008077679,0.0025805163,0.0046964483,0.0013468985],"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":[0.00010881996,0.00011093672,0.00051487196,0.07256777,0.00031314828,0.00019212437,0.00044341313,0.00071075815,0.0004872049,0.070841916,0.0802857,0.7734233],"study_design_scores_gemma":[0.000025596093,0.00006957189,0.0016057385,0.08196176,0.00055051566,0.00048764612,0.0005094896,0.0002197222,0.00033519807,0.025553312,0.8886357,0.000045714296],"about_ca_topic_score_codex":0.00601364,"about_ca_topic_score_gemma":0.010043134,"teacher_disagreement_score":0.015067602,"about_ca_system_score_codex":0.0060882233,"about_ca_system_score_gemma":0.014268173,"threshold_uncertainty_score":0.04725653},"labels":[],"label_agreement":null},{"id":"W4297129241","doi":"10.1007/978-981-19-5727-7_86","title":"The Detection and Prediction of Financial Frauds","year":2022,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Finance; Actuarial science; Predictive modelling; Flag (linear algebra); Computer science; Business; Accounting; Machine learning; Mathematics","score_opus":0.026470891923053984,"score_gpt":0.24357878913618172,"score_spread":0.21710789721312773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297129241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11574529,0.0602086,0.76716465,0.020769393,0.0019820333,0.00016732013,0.0020992823,0.0012411389,0.030622242],"genre_scores_gemma":[0.79392314,0.023245186,0.15832286,0.0008653882,0.002422846,0.00012848417,0.0017829476,0.00013605582,0.019173086],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981553,0.000636211,0.00010663657,0.00023090023,0.00075456727,0.00011642892],"domain_scores_gemma":[0.9891823,0.008490228,0.000776946,0.00069053174,0.0006938469,0.0001661961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040515144,0.00084482593,0.0010585584,0.0035177928,0.0003493132,0.0027276871,0.0013611277,0.0016420957,0.0017904524],"category_scores_gemma":[0.020593768,0.0005242894,0.0006345175,0.0037200875,0.0013348992,0.0044426396,0.0011845604,0.0021846073,0.0010604782],"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":[0.00016239486,0.000200799,0.019482367,0.0002856335,0.000119256634,0.00017189702,0.00019822261,0.055572398,0.00080772146,0.072414845,0.03721835,0.81336606],"study_design_scores_gemma":[0.00001979994,0.00008292934,0.008924635,0.00022186674,0.000041498915,0.0005224727,0.00014800514,0.6731766,0.0021502494,0.29720995,0.017463583,0.000038373997],"about_ca_topic_score_codex":0.0019193031,"about_ca_topic_score_gemma":0.0012852112,"teacher_disagreement_score":0.0040515144,"about_ca_system_score_codex":0.000879934,"about_ca_system_score_gemma":0.0007658281,"threshold_uncertainty_score":0.021426737},"labels":[],"label_agreement":null},{"id":"W4382239151","doi":"10.1007/978-981-19-7826-5_89","title":"Research on the Market Development Strategy of Sports Apparel Companies Based in Canada","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Educational Research and Science Teaching","field":"Agricultural and Biological Sciences","cited_by":2,"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":"Clothing; Business; Marketing; Product (mathematics); Market development; Advertising; Economics; Political science; Market economy","score_opus":0.21402077020646582,"score_gpt":0.3419715676375056,"score_spread":0.12795079743103976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.753636,0.008322406,0.00033242223,0.0067776632,0.000046011402,0.00010410147,0.0017713503,0.00002812618,0.22898194],"genre_scores_gemma":[0.92886513,0.0038863802,0.00027804033,0.00030872267,0.000008598821,0.000012965854,0.00063867937,0.0000070192245,0.06599433],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99916196,0.00006045837,0.000013978914,0.000054337106,0.0002986464,0.00041077437],"domain_scores_gemma":[0.9977956,0.000412988,0.0001423785,0.000025433408,0.0011219301,0.00050170126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058879115,0.00019539354,0.00019172687,0.0032202457,0.0049748146,0.004131172,0.0009981632,0.00055750506,0.008502105],"category_scores_gemma":[0.0020399147,0.000174026,0.000233484,0.006163452,0.0012561382,0.0011863207,0.00062832213,0.0007879197,0.0003008308],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003891961,0.00044512952,0.33793524,0.0007253465,0.00011195418,0.001909669,0.048017662,0.0043399953,0.0037879047,0.22885983,0.05991451,0.31356367],"study_design_scores_gemma":[0.000023886907,0.000094124895,0.7261794,0.0003377761,0.000056354347,0.00015157786,0.09172657,0.0026360385,0.0013579902,0.0027095268,0.17468281,0.000043911667],"about_ca_topic_score_codex":0.9930756,"about_ca_topic_score_gemma":0.9976484,"teacher_disagreement_score":0.08664875,"about_ca_system_score_codex":0.08664875,"about_ca_system_score_gemma":0.08717923,"threshold_uncertainty_score":0.62868357},"labels":[],"label_agreement":null},{"id":"W4382239294","doi":"10.1007/978-981-19-7826-5_77","title":"Re-examining the Existence of the Environmental Kuznets Curve: Evidence from Six Kinds of Canadian Air Pollutions","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"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":"Kuznets curve; Gross domestic product; Per capita; Air pollution; Panel data; Economics; Econometrics; Pollution; Pollutant; Variance (accounting); Environmental science; Agricultural economics; Macroeconomics; Demography; Ecology","score_opus":0.09153122489321226,"score_gpt":0.23545744304834815,"score_spread":0.1439262181551359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8512467,0.008128743,0.0022437596,0.0061963303,0.00011454349,0.00008815776,0.009377193,0.00008361053,0.122520946],"genre_scores_gemma":[0.9784404,0.003399339,0.00067922135,0.0005106381,0.00005826825,0.000017338454,0.0048212395,0.00005613011,0.012017284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969812,0.00025229814,0.00013431591,0.00034725803,0.0015160529,0.0007689125],"domain_scores_gemma":[0.97210354,0.008109797,0.0026050848,0.002234973,0.013818371,0.001128269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003561573,0.0006477809,0.0007370253,0.006575251,0.0053448807,0.004928323,0.0030028722,0.0013955649,0.009251853],"category_scores_gemma":[0.024764545,0.00027095125,0.0008415061,0.020129915,0.0036271838,0.003368069,0.0026688082,0.0020849046,0.000691051],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052667264,0.00017471025,0.7300574,0.0005877058,0.0004388556,0.0006117331,0.014587006,0.0063670534,0.0008099754,0.10140918,0.03514807,0.10928165],"study_design_scores_gemma":[0.000019820276,0.000024774045,0.9115902,0.00023761146,0.0002790213,0.00008197509,0.019351311,0.002287485,0.00070740416,0.008689996,0.056661297,0.00006904562],"about_ca_topic_score_codex":0.9922259,"about_ca_topic_score_gemma":0.9936289,"teacher_disagreement_score":0.029161353,"about_ca_system_score_codex":0.029161353,"about_ca_system_score_gemma":0.031633742,"threshold_uncertainty_score":0.21158141},"labels":[],"label_agreement":null},{"id":"W4382239447","doi":"10.1007/978-981-19-7826-5_144","title":"Research and Analysis of Business Operation Mode Innovation","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Amazon rainforest; Business model; Reputation; Online business; Business; Marketing; Data science; Industrial organization; Knowledge management; Computer science; The Internet; World Wide Web; Political science","score_opus":0.15464117762688548,"score_gpt":0.40988839410559147,"score_spread":0.25524721647870596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239447","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10689247,0.036098316,0.090001464,0.0118688075,0.00041770595,0.00013763149,0.0004163529,0.00014196314,0.7540254],"genre_scores_gemma":[0.83360916,0.03194138,0.027300386,0.0005179238,0.0004663157,0.00014875917,0.00029568298,0.00007815602,0.10564229],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990368,0.00041168253,0.000026485975,0.000113662085,0.00029737735,0.000114099115],"domain_scores_gemma":[0.99567324,0.0034830775,0.0001425719,0.00026481837,0.00034266515,0.00009357604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016457707,0.00036043403,0.000378048,0.0036087653,0.0006744299,0.004729186,0.0010404171,0.0010489174,0.014058273],"category_scores_gemma":[0.004618203,0.000273416,0.00052765594,0.004753235,0.0037222605,0.0065676146,0.00089132116,0.0013573595,0.001176436],"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":[0.00001556238,0.00005922728,0.0013378162,0.00014995217,0.000009407374,0.000039505274,0.00061954785,0.001850513,0.0003292635,0.9204509,0.0024147306,0.07272345],"study_design_scores_gemma":[0.0000060507846,0.00004904752,0.0068756295,0.0003612188,0.000016779419,0.00013029267,0.0025751041,0.013322345,0.0013368983,0.8809666,0.09434342,0.00001660492],"about_ca_topic_score_codex":0.0045475815,"about_ca_topic_score_gemma":0.0044519245,"teacher_disagreement_score":0.014058273,"about_ca_system_score_codex":0.0038605826,"about_ca_system_score_gemma":0.0033386506,"threshold_uncertainty_score":0.047029555},"labels":[],"label_agreement":null},{"id":"W4382239546","doi":"10.1007/978-981-19-7826-5_36","title":"Covid-19 and Internet Medical Platforms: Opportunities and Challenges","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Post-Communist Economic and Political Transition","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"The Internet; Pandemic; Internet privacy; Coronavirus disease 2019 (COVID-19); Revenue; Enforcement; Value (mathematics); Business; Public relations; Knowledge management; Marketing; Political science; Computer science; Medicine; Law; World Wide Web; Accounting","score_opus":0.2952860866751333,"score_gpt":0.3634957484121442,"score_spread":0.06820966173701093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239546","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035660455,0.026202595,0.0038980856,0.12944989,0.0051283883,0.00005246261,0.00037116275,0.00015161271,0.8311798],"genre_scores_gemma":[0.12882459,0.06433455,0.011786,0.04182542,0.012193126,0.00034595784,0.0013484254,0.00069641136,0.73864555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976688,0.00088076195,0.0000742885,0.00015824333,0.00084644026,0.000371383],"domain_scores_gemma":[0.9917242,0.0050089555,0.00029347182,0.00044157673,0.0011165538,0.0014153478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062775244,0.00062815927,0.0004883603,0.0023110262,0.0028657604,0.02254179,0.002475676,0.005840077,0.049520478],"category_scores_gemma":[0.007961144,0.00038446134,0.00046492025,0.004769429,0.0065217577,0.015885103,0.0050142794,0.0065322765,0.00804286],"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":[0.0000054672337,0.000031980744,0.00013825692,0.00005300877,0.0000020219334,0.000025934214,0.00021736558,0.0000954339,0.00004215862,0.8232522,0.13340907,0.042727195],"study_design_scores_gemma":[0.000006446861,0.0000180655,0.0005631668,0.00040934837,0.0000024514345,0.000092788105,0.0009029913,0.0005971496,0.00013553545,0.1547164,0.8425363,0.000019361465],"about_ca_topic_score_codex":0.009579013,"about_ca_topic_score_gemma":0.015842425,"teacher_disagreement_score":0.049520478,"about_ca_system_score_codex":0.0072001657,"about_ca_system_score_gemma":0.0094686,"threshold_uncertainty_score":0.16566253},"labels":[],"label_agreement":null},{"id":"W4382239615","doi":"10.1007/978-981-19-7826-5_130","title":"Tourism Prediction in Canada and the US Based on a Modified GM (1, 1) Model Considering COVID-19 Effect","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Tourism; Coronavirus disease 2019 (COVID-19); Econometrics; Value (mathematics); Harmony (color); Harmony search; Sample (material); Operations research; Mathematical optimization; Computer science; Economics; Geography; Mathematics; Machine learning","score_opus":0.10714709288407546,"score_gpt":0.3301787518718052,"score_spread":0.2230316589877297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97209597,0.0007961388,0.01155475,0.0017236216,0.00012830477,0.00003383517,0.0028115597,0.00020868606,0.010647131],"genre_scores_gemma":[0.9922645,0.00021051981,0.0015409673,0.000055266286,0.000011204879,0.000008736911,0.0006977754,0.000027520517,0.005183562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997609,0.000055066055,0.000008217437,0.000040867486,0.000030035842,0.00010487419],"domain_scores_gemma":[0.99936074,0.00026239327,0.000039481678,0.000017631117,0.00023621084,0.000083520885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007428217,0.00056682545,0.00082675146,0.00072320364,0.0009112027,0.0017763486,0.0016383225,0.0012116273,0.0019043738],"category_scores_gemma":[0.0016703136,0.00038467473,0.0010172368,0.0013364409,0.00085043156,0.0008520928,0.0005383549,0.0010352712,0.00018058383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007521101,0.000028065682,0.0056994297,0.000021824459,0.000025779262,0.00007910709,0.000022132484,0.98798007,0.000104132065,0.0023622464,0.0015581723,0.0020438025],"study_design_scores_gemma":[0.000005186083,0.0000058088913,0.0021343261,0.000002949541,0.000009152144,0.0000045948473,0.00004315556,0.9971403,0.000042628344,0.0004642389,0.00013850284,0.000009207972],"about_ca_topic_score_codex":0.9583401,"about_ca_topic_score_gemma":0.92836905,"teacher_disagreement_score":0.04165989,"about_ca_system_score_codex":0.011235181,"about_ca_system_score_gemma":0.009391162,"threshold_uncertainty_score":0.08381039},"labels":[],"label_agreement":null},{"id":"W4382239796","doi":"10.1007/978-981-19-7826-5_137","title":"The Relationship Between the Evolution of Buildings and the Environment in China","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sustainability; China; Architectural engineering; Natural resource; Modernism (music); Built environment; Environmental planning; Building industry; Sustainable development; Natural (archaeology); Consumption (sociology); Architectural technology; Business; Engineering; Environmental resource management; Civil engineering; Political science; Geography; Architecture; Ecology; Environmental science; Sociology","score_opus":0.02353537916169356,"score_gpt":0.23851658277661553,"score_spread":0.21498120361492196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95438987,0.0049390537,0.0007024659,0.0016284724,0.00002801609,0.000012428722,0.00024697144,0.000019811723,0.0380329],"genre_scores_gemma":[0.9925484,0.001740393,0.00014288782,0.000048291215,0.000014921976,0.0000032932578,0.0000681038,0.0000032754292,0.005430514],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978644,0.000044223565,0.000011574646,0.000036669895,0.000046976937,0.00007410985],"domain_scores_gemma":[0.9997987,0.000058961734,0.00006071132,0.000013171608,0.000033058834,0.000035432025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027848568,0.00015148646,0.00016568485,0.0010191124,0.00085686235,0.0013564219,0.00039664854,0.00037360308,0.0019975624],"category_scores_gemma":[0.0004875703,0.00015299692,0.0002764208,0.0030077826,0.0013484681,0.0008273748,0.0007162955,0.00037253986,0.00008414291],"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":[0.00014198692,0.00009881025,0.5503455,0.0002558908,0.00015664402,0.0014544007,0.0069940314,0.024712572,0.002831844,0.30728048,0.0047077173,0.101020195],"study_design_scores_gemma":[0.0000065302957,0.00006806574,0.9401687,0.000059936134,0.00005491082,0.00016543391,0.0024721902,0.0115560675,0.00055212626,0.019819787,0.025041973,0.000034190372],"about_ca_topic_score_codex":0.19050817,"about_ca_topic_score_gemma":0.29165673,"teacher_disagreement_score":0.19050817,"about_ca_system_score_codex":0.0058350377,"about_ca_system_score_gemma":0.0036404047,"threshold_uncertainty_score":0.3787986},"labels":[],"label_agreement":null},{"id":"W4382239963","doi":"10.1007/978-981-19-7826-5_18","title":"Analysis of China’s Blind Box Economy—Taking POP MART as an Example","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Strategic Planning and Analysis","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitor analysis; Portfolio; Conformity; China; Marketing; Consumption (sociology); Advertising; Product (mathematics); Marketing strategy; SWOT analysis; The Internet; Business; Economics; Psychology; Sociology; Political science; Computer science; Social science; Mathematics; Financial economics; Social psychology","score_opus":0.09038573003333963,"score_gpt":0.28859862153755017,"score_spread":0.19821289150421054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239963","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7552419,0.0030347018,0.00862655,0.004520136,0.000106691994,0.00009325955,0.0008263012,0.00010323816,0.22744727],"genre_scores_gemma":[0.97581965,0.00073582993,0.00090254616,0.000100782025,0.00002037637,0.00002105798,0.00012658088,0.000013333844,0.022259783],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9998673,0.000026540625,0.0000030972235,0.000013403729,0.000031970416,0.00005773056],"domain_scores_gemma":[0.99989784,0.00002516053,0.000013474604,0.000011694821,0.00003116196,0.000020764182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028738845,0.00032368483,0.00043760194,0.00095486315,0.0010457016,0.0016208428,0.00048289643,0.00063137256,0.0053823693],"category_scores_gemma":[0.00045892008,0.0001253748,0.00058556616,0.0013958154,0.0012194087,0.0011759866,0.0006761331,0.00063949823,0.00017231818],"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":[0.000101267535,0.00007341455,0.0092031425,0.00015408974,0.0000640636,0.00087457645,0.00053588307,0.06906677,0.0010799008,0.8821063,0.008729458,0.028011214],"study_design_scores_gemma":[0.000069797716,0.00018358284,0.07097447,0.0001330105,0.000107180815,0.00016309178,0.0032170746,0.2793486,0.0018249552,0.58204836,0.06185083,0.00007910814],"about_ca_topic_score_codex":0.16914946,"about_ca_topic_score_gemma":0.16919038,"teacher_disagreement_score":0.16914946,"about_ca_system_score_codex":0.0058300444,"about_ca_system_score_gemma":0.005645481,"threshold_uncertainty_score":0.33632982},"labels":[],"label_agreement":null},{"id":"W4382240743","doi":"10.1007/978-981-19-7826-5_6","title":"The Importance of Compensation from Different Aspects: A Study of Akamai Inc.","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Compensation (psychology); Incentive; Agency (philosophy); Shareholder; Executive compensation; Work (physics); Business; Pay for performance; Public relations; Plan (archaeology); Finance; Engineering; Economics; Psychology; Political science; Sociology; Social psychology; Corporate governance; Microeconomics","score_opus":0.051793882386332285,"score_gpt":0.24951759090904727,"score_spread":0.19772370852271498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382240743","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18453376,0.056964982,0.007514566,0.014304247,0.0006667184,0.00004314639,0.0004887511,0.0000865493,0.73539734],"genre_scores_gemma":[0.8672126,0.012690141,0.002154851,0.00058949523,0.00018052432,0.000038003494,0.00016984604,0.000055992135,0.11690862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9994351,0.00012076475,0.000032743137,0.0000823632,0.00017913508,0.0001497682],"domain_scores_gemma":[0.9987043,0.0005964687,0.00015841275,0.0000712898,0.0003350559,0.0001343988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001012288,0.00031289342,0.00046550384,0.0018477521,0.002566309,0.0045824284,0.0006676847,0.0012858215,0.011918638],"category_scores_gemma":[0.00336552,0.00033614473,0.00042656963,0.0032580022,0.0012580162,0.0043311194,0.0010690943,0.0016423654,0.0013639845],"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":[0.00014218572,0.000060742615,0.010334047,0.0001286132,0.0000212416,0.0003426501,0.0024158782,0.0012296673,0.00021554294,0.88313437,0.028084517,0.07389056],"study_design_scores_gemma":[0.00003792453,0.00011404315,0.073142536,0.0006352136,0.00017075863,0.0011238097,0.010238055,0.010085161,0.0011600552,0.45463374,0.4485418,0.0001169289],"about_ca_topic_score_codex":0.016044082,"about_ca_topic_score_gemma":0.021594994,"teacher_disagreement_score":0.016044082,"about_ca_system_score_codex":0.0033492374,"about_ca_system_score_gemma":0.0026863269,"threshold_uncertainty_score":0.039871812},"labels":[],"label_agreement":null},{"id":"W4387427992","doi":"10.1007/978-981-99-6441-3_95","title":"The Relationship between Real E-commerce Platform Reviews and Stocks Price Change Based on Panel Regression Model","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Stock (firearms); Stock price; Econometrics; Economics; Regression analysis; Panel data; Financial economics; Business; Statistics; Mathematics; Engineering","score_opus":0.36161590177285624,"score_gpt":0.3820134608995298,"score_spread":0.02039755912667357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387427992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97456825,0.00084589655,0.009912384,0.00095746975,0.00021106414,0.00004049692,0.008825039,0.00026407762,0.0043752277],"genre_scores_gemma":[0.9822782,0.00028233047,0.0010129791,0.00010895829,0.00010740007,0.000037276954,0.008653132,0.000027686086,0.00749208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985672,0.00067660346,0.000089465386,0.00035748485,0.000117675096,0.00019142844],"domain_scores_gemma":[0.9760621,0.01901748,0.0025436517,0.0009584428,0.0009103904,0.00050790596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029312856,0.0005881865,0.00076286943,0.000941403,0.00035389207,0.0018817057,0.0013883037,0.0015439527,0.009214994],"category_scores_gemma":[0.008729653,0.00055375975,0.0017823906,0.0014621107,0.00040163146,0.0012474844,0.00056037016,0.0025153176,0.003066825],"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":[0.0020486715,0.0008244537,0.883679,0.00019657637,0.0037815387,0.0005688451,0.00024051919,0.06973107,0.0019276798,0.003250039,0.010819545,0.022932163],"study_design_scores_gemma":[0.00010593656,0.000620488,0.5615646,0.00005365553,0.0018179704,0.0002444551,0.0003577247,0.42783707,0.0016672162,0.002597853,0.003007692,0.00012524254],"about_ca_topic_score_codex":0.02608804,"about_ca_topic_score_gemma":0.01832165,"teacher_disagreement_score":0.02608804,"about_ca_system_score_codex":0.0005984725,"about_ca_system_score_gemma":0.0005184307,"threshold_uncertainty_score":0.051872373},"labels":[],"label_agreement":null},{"id":"W4387427999","doi":"10.1007/978-981-99-6441-3_147","title":"Research on the Impact of Macroeconomic Events on the Chinese Stock Market Through the Abnormal Investment Returns","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Volatility (finance); Stock market; Stock (firearms); China; Economics; Monetary economics; Stock market volatility; Financial economics; Investment (military); Event study; Business","score_opus":0.12143636168812469,"score_gpt":0.33967086017711356,"score_spread":0.21823449848898888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387427999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8829553,0.03293891,0.003356607,0.0036750438,0.00026977845,0.000036789006,0.00089363364,0.00006675798,0.07580715],"genre_scores_gemma":[0.96478534,0.026365135,0.00049586047,0.00014477492,0.0002755022,0.000008352693,0.0004417658,0.000009051799,0.0074743005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986255,0.000019911877,0.000012546174,0.000025541523,0.000049678463,0.00002973736],"domain_scores_gemma":[0.9993162,0.00031727625,0.00017138815,0.000027778678,0.00011185875,0.00005546162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051905966,0.00033200264,0.0002443332,0.0013116116,0.0002892593,0.0015038713,0.00037129712,0.00034022576,0.002934667],"category_scores_gemma":[0.0013740787,0.00015363621,0.00035401154,0.0027836596,0.00047542132,0.0016725775,0.00030582384,0.00061190955,0.0001811367],"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":[0.00019556342,0.00020706697,0.55786794,0.0009854384,0.0005340035,0.00153645,0.0015904753,0.015467531,0.0044388394,0.14778599,0.013845503,0.25554517],"study_design_scores_gemma":[0.000013893626,0.00012693803,0.9189896,0.00016290836,0.00044455196,0.00024948103,0.0013929667,0.025505705,0.0017681638,0.029567525,0.02172964,0.000048609967],"about_ca_topic_score_codex":0.02225867,"about_ca_topic_score_gemma":0.022712538,"teacher_disagreement_score":0.02225867,"about_ca_system_score_codex":0.0011835722,"about_ca_system_score_gemma":0.0009925503,"threshold_uncertainty_score":0.044258237},"labels":[],"label_agreement":null},{"id":"W4387428032","doi":"10.1007/978-981-99-6441-3_155","title":"A Cross-National Examination of the Determinants for Covid 19 Vaccination Rates","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Oakville-Trafalgar Memorial Hospital","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Vaccination; Human Development Index; Globe; Normality; Gross domestic product; Regression analysis; Regression; Demography; Geography; Econometrics; Statistics; Medicine; Economic growth; Economics; Human development (humanity); Mathematics; Virology; Sociology; Disease","score_opus":0.09871222514440192,"score_gpt":0.38937098435245004,"score_spread":0.2906587592080481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387428032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9678458,0.0022585203,0.0013157548,0.002464409,0.00006241793,0.000024846186,0.005199865,0.00003492731,0.020793477],"genre_scores_gemma":[0.9852388,0.001020185,0.00057723565,0.00017496203,0.00003080304,0.00002839834,0.0026183068,0.000013833648,0.010297496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990871,0.0004629001,0.00003376486,0.000114607064,0.00009774651,0.00020388332],"domain_scores_gemma":[0.9930795,0.004909814,0.0008055612,0.0002955877,0.0005599125,0.00034959524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018482051,0.00017886945,0.00032389595,0.0010113539,0.00041024425,0.00087746076,0.0005653681,0.00049612415,0.008970032],"category_scores_gemma":[0.0050053066,0.00030273895,0.0010407289,0.0024123657,0.00035690243,0.0009563313,0.0008668888,0.0010743026,0.0007848656],"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":[0.00018038416,0.0001707807,0.950946,0.00008519729,0.00042047902,0.00023639837,0.0007575819,0.004345269,0.00037817264,0.010103391,0.0072441353,0.025132267],"study_design_scores_gemma":[0.000005886085,0.00006617831,0.9887841,0.0000491977,0.00011307342,0.00006478521,0.0016133559,0.004186759,0.0001927217,0.0011078819,0.0038057938,0.0000104386545],"about_ca_topic_score_codex":0.08458115,"about_ca_topic_score_gemma":0.14556968,"teacher_disagreement_score":0.08458115,"about_ca_system_score_codex":0.0010444993,"about_ca_system_score_gemma":0.0012253567,"threshold_uncertainty_score":0.16817766},"labels":[],"label_agreement":null},{"id":"W4387428244","doi":"10.1007/978-981-99-6441-3_24","title":"Innovative Tools for Food Waste Management that Enable Higher Value Circular Economy Outputs","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Food waste; Circular economy; Greenhouse gas; Food security; Production (economics); Business; Food processing; Food industry; Waste recycling; Environmental economics; Natural resource economics; Natural resource; Waste management; Engineering; Economics; Agriculture; Geography","score_opus":0.08462664676484948,"score_gpt":0.2581677527874026,"score_spread":0.17354110602255313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387428244","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0082082255,0.002058984,0.39385632,0.008035045,0.0007837861,0.00021405992,0.00018051562,0.001032484,0.5856306],"genre_scores_gemma":[0.22844428,0.0053985356,0.42540905,0.0018670526,0.00041126786,0.0006355266,0.00034706912,0.00093338615,0.33655384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99936587,0.00019401072,0.000022992466,0.00006309102,0.00029729234,0.000056861227],"domain_scores_gemma":[0.99914086,0.0004605206,0.000056586578,0.00016163828,0.00012874801,0.000051618666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014007504,0.00059519993,0.0002722574,0.0011897106,0.00088227214,0.0058357934,0.0010069966,0.0015740372,0.026214821],"category_scores_gemma":[0.0027749385,0.0003702122,0.0005762615,0.0015873271,0.0025956563,0.0061832075,0.002768903,0.0019988061,0.003957433],"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":[0.000010738151,0.000056179124,0.00006797557,0.000107250264,0.0000057093234,0.000041719122,0.0002557213,0.0024768596,0.0015548099,0.9085276,0.011358912,0.07553659],"study_design_scores_gemma":[0.000013836235,0.00002765064,0.000164163,0.00016090844,0.0000074605805,0.00008287526,0.00046665626,0.0059960573,0.0047030863,0.737919,0.2504392,0.000019183897],"about_ca_topic_score_codex":0.000777163,"about_ca_topic_score_gemma":0.0018889038,"teacher_disagreement_score":0.026214821,"about_ca_system_score_codex":0.0018764971,"about_ca_system_score_gemma":0.0017307979,"threshold_uncertainty_score":0.08769727},"labels":[],"label_agreement":null},{"id":"W4387430339","doi":"10.1007/978-981-99-6441-3_2","title":"Research on Business Management Based on New Retail Model: The Case of Yonghui Supermarket","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Investment (military); Scarcity; Rivalry; Control (management); China; Competitive advantage; Industrial organization; Marketing; Supply chain; Process (computing); Commerce; Economics; Market economy","score_opus":0.15831245400908706,"score_gpt":0.32921657913955654,"score_spread":0.1709041251304695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387430339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5607239,0.002538463,0.006653834,0.0060673007,0.00005623475,0.00006343879,0.0000671078,0.00003557318,0.42379418],"genre_scores_gemma":[0.9680913,0.0012718069,0.001216007,0.00011807803,0.000014184418,0.000015598336,0.000027097383,0.000011228826,0.029234616],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99980694,0.00007668504,0.0000045726383,0.000033610468,0.000023573855,0.000054641605],"domain_scores_gemma":[0.9997179,0.0001628326,0.000029438323,0.000018771962,0.000026482632,0.00004461779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003855485,0.00023113083,0.00027637178,0.00047577088,0.002290526,0.0034937966,0.00091047055,0.001159205,0.009828343],"category_scores_gemma":[0.0005946743,0.0002295715,0.00037647077,0.0014383374,0.0026755447,0.0050790543,0.00077546603,0.0013321362,0.00030350938],"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":[0.00003330192,0.00011359495,0.004005912,0.00006990844,0.0000133166195,0.0014955053,0.0057526897,0.008257528,0.00040954893,0.9629837,0.003955685,0.012909299],"study_design_scores_gemma":[0.00005346147,0.00020025342,0.02238509,0.00025111708,0.0000885953,0.0009595907,0.07920732,0.13659982,0.0011515485,0.6103665,0.14864467,0.00009209088],"about_ca_topic_score_codex":0.031311266,"about_ca_topic_score_gemma":0.056536827,"teacher_disagreement_score":0.031311266,"about_ca_system_score_codex":0.0039199367,"about_ca_system_score_gemma":0.0018157328,"threshold_uncertainty_score":0.062258065},"labels":[],"label_agreement":null},{"id":"W4387430400","doi":"10.1007/978-981-99-6441-3_75","title":"Value Investment: A Case Study for Technology Companies (Meta vs Microsoft)","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Innovation Diffusion and Forecasting","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 Toronto","funders":"","keywords":"Profitability index; Business; Valuation (finance); Shareholder; Investment (military); Investment value; Finance; Industrial organization; Accounting; Cash","score_opus":0.27627129241212756,"score_gpt":0.40062962376629657,"score_spread":0.12435833135416902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387430400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9204628,0.0015371161,0.0026705188,0.0015779866,0.000027333295,0.000049538357,0.00013742976,0.00004153957,0.07349582],"genre_scores_gemma":[0.9729287,0.0010469967,0.0028787043,0.00011169477,0.000012814352,0.000019802203,0.00007770101,0.000018138142,0.022905488],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997737,0.00008018679,0.000008070482,0.000023749713,0.000055882803,0.000058433678],"domain_scores_gemma":[0.99925286,0.0005124873,0.000070005466,0.000029731842,0.0000452496,0.000089610534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005584437,0.000263157,0.00018426254,0.00094174116,0.0012441333,0.0028007233,0.00046657358,0.0016411985,0.0044214353],"category_scores_gemma":[0.0017166351,0.000120167184,0.00027466123,0.0014717262,0.000571225,0.0014885758,0.00070224307,0.0007305573,0.0005360898],"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":[0.0010091773,0.0029992354,0.12281558,0.0005898797,0.00011098891,0.046679687,0.0373343,0.0102023175,0.017601833,0.28554225,0.026149906,0.44896474],"study_design_scores_gemma":[0.00026382174,0.0034872845,0.21159957,0.0014109482,0.00042076057,0.04012539,0.17553517,0.060368065,0.046414934,0.097716995,0.36245087,0.00020612736],"about_ca_topic_score_codex":0.0076545947,"about_ca_topic_score_gemma":0.014894933,"teacher_disagreement_score":0.0076545947,"about_ca_system_score_codex":0.0015884738,"about_ca_system_score_gemma":0.0006038869,"threshold_uncertainty_score":0.015220106},"labels":[],"label_agreement":null},{"id":"W4387430419","doi":"10.1007/978-981-99-6441-3_1","title":"Crew Scheduling Problem: Integer Optimization Using Set-Covering Model","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Crew scheduling; Crew; Integer programming; Operations research; Scheduling (production processes); Mathematical optimization; Computer science; MATLAB; Linear programming; Job shop scheduling; Branch and price; Engineering; Schedule; Mathematics; Aeronautics; Operating system","score_opus":0.08088362128537244,"score_gpt":0.30145352918369095,"score_spread":0.2205699078983185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387430419","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01972217,0.0021863477,0.9402712,0.00075952156,0.00020586724,0.0001054012,0.0007107973,0.00023025846,0.035808526],"genre_scores_gemma":[0.6210555,0.007425224,0.3063461,0.0004548388,0.00039655934,0.0006592486,0.0015081388,0.00053369,0.061620705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994943,0.00019322426,0.000012942675,0.00008820353,0.0001293862,0.00008185361],"domain_scores_gemma":[0.9996425,0.00023090378,0.000036428588,0.000032033076,0.000032442553,0.000025665544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065356947,0.0012743974,0.0015318312,0.0007240463,0.00042271978,0.0020559055,0.0018058677,0.0018646128,0.005474044],"category_scores_gemma":[0.001627605,0.00071344717,0.0011261388,0.0025848795,0.00063215673,0.0020590238,0.0010465727,0.001418512,0.0006992182],"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":[0.000033225064,0.0000355639,0.00013966575,0.000116003815,0.00003665218,0.000050540904,0.00003365466,0.9387856,0.000786934,0.033017166,0.0052657197,0.021699332],"study_design_scores_gemma":[0.000007692387,0.000019626683,0.00013510534,0.000017895316,0.000010331159,0.00003630961,0.000021826161,0.9760088,0.00027292134,0.019528836,0.0039319117,0.000008852617],"about_ca_topic_score_codex":0.008249195,"about_ca_topic_score_gemma":0.0045518875,"teacher_disagreement_score":0.008249195,"about_ca_system_score_codex":0.0015279243,"about_ca_system_score_gemma":0.0012672064,"threshold_uncertainty_score":0.018312454},"labels":[],"label_agreement":null},{"id":"W4387430424","doi":"10.1007/978-981-99-6441-3_51","title":"The Research of Three Parties’ Game Influenced by IWOM in Evolutionary Game Theory-Taking “Ice Cream Assassin” as an Example","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Ice cream; Profit (economics); Business; Evolutionarily stable strategy; Point (geometry); Microeconomics; Marketing; Game theory; Industrial organization; Economics; Mathematics","score_opus":0.1428122524259561,"score_gpt":0.32528361698620156,"score_spread":0.18247136456024546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387430424","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1407335,0.0042778384,0.39437768,0.005173152,0.00073527836,0.00009342201,0.00005886582,0.000038503957,0.4545117],"genre_scores_gemma":[0.9422042,0.0016012916,0.026992455,0.0003436737,0.00010744516,0.00007834699,0.000021404845,0.00003288657,0.028618194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993117,0.00044525103,0.0000150106225,0.000068189765,0.000077148085,0.000082643266],"domain_scores_gemma":[0.99909246,0.0006883731,0.000051505136,0.000046377107,0.00006286334,0.000058465692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011313182,0.0004315891,0.00039410684,0.00036850234,0.0010699149,0.0018764104,0.0007686192,0.0011606318,0.0037178209],"category_scores_gemma":[0.0025440883,0.0002234952,0.00076607626,0.0006008544,0.0029463447,0.0031020138,0.0010083517,0.0019367307,0.00021440208],"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":[0.000006274589,0.000010093693,0.00012267834,0.000024828434,0.0000052662976,0.000035150042,0.00029214297,0.0051112925,0.00017705502,0.99073106,0.00050345523,0.0029807312],"study_design_scores_gemma":[0.00000822698,0.000031793043,0.00040092386,0.000045577104,0.000012506587,0.000064782085,0.00049275573,0.04959145,0.00027198507,0.9353333,0.013734014,0.000012620628],"about_ca_topic_score_codex":0.0029194106,"about_ca_topic_score_gemma":0.0026323777,"teacher_disagreement_score":0.0037178209,"about_ca_system_score_codex":0.0019092562,"about_ca_system_score_gemma":0.0010021777,"threshold_uncertainty_score":0.0138527155},"labels":[],"label_agreement":null},{"id":"W4392173240","doi":"10.1007/978-981-97-0523-8_130","title":"Valuation and Analysis of the Canadian Banking Sector During the COVID-19 Pandemic","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Valuation (finance); Pandemic; Business; 2019-20 coronavirus outbreak; Economics; Actuarial science; Accounting; Virology; Medicine; Infectious disease (medical specialty); Internal medicine; Disease","score_opus":0.11945581687062944,"score_gpt":0.3010516276270522,"score_spread":0.18159581075642273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392173240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.808641,0.005714067,0.0033364296,0.0049272943,0.00009234404,0.00012404464,0.0071956892,0.0000625191,0.16990659],"genre_scores_gemma":[0.9795797,0.0022111142,0.001395675,0.00010401101,0.00002720879,0.00001611311,0.0021854758,0.000012156739,0.014468559],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996306,0.00003684027,0.000007956606,0.000026124035,0.00018411089,0.00011430484],"domain_scores_gemma":[0.9992495,0.00013967365,0.00007294521,0.000017090802,0.00044315148,0.00007771392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000573437,0.00026479494,0.00019611813,0.0018129859,0.0012123891,0.0023488733,0.0006210367,0.00038012545,0.0026326429],"category_scores_gemma":[0.002619999,0.00012212509,0.00025634276,0.003099505,0.0005843154,0.0005785851,0.00044868884,0.00044904507,0.0001701277],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033743962,0.00011842759,0.41373536,0.0003164138,0.00009898497,0.0016415354,0.0048700213,0.10709858,0.0036087323,0.18633468,0.07975191,0.20208788],"study_design_scores_gemma":[0.000010669277,0.00004368321,0.72350377,0.0001857513,0.000056524124,0.00020896693,0.011300827,0.1839901,0.00081486005,0.016652677,0.063132755,0.0000993403],"about_ca_topic_score_codex":0.97297996,"about_ca_topic_score_gemma":0.97295195,"teacher_disagreement_score":0.030903602,"about_ca_system_score_codex":0.030903602,"about_ca_system_score_gemma":0.013047647,"threshold_uncertainty_score":0.22422236},"labels":[],"label_agreement":null},{"id":"W4392173853","doi":"10.1007/978-981-97-0523-8_114","title":"InstaCart Analysis: Use PCA with K-Means to Segment Grocery Customers","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Grocery store; Business; Grocery shopping; Marketing","score_opus":0.040486402772903655,"score_gpt":0.2548725476785104,"score_spread":0.21438614490560676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392173853","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021091107,0.0003320409,0.9284647,0.0002669067,0.00028762504,0.000269286,0.0031812394,0.035674628,0.010432444],"genre_scores_gemma":[0.07272213,0.00028451413,0.89589137,0.00010465412,0.0001263326,0.00038949598,0.0059684003,0.0048106615,0.01970238],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991373,0.0001400529,0.00004533347,0.00022712328,0.0003336704,0.000116474126],"domain_scores_gemma":[0.99907506,0.00027402482,0.00004540017,0.00014746033,0.000423487,0.000034577584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009783068,0.0018547138,0.0011763127,0.0026073349,0.00119611,0.0022647122,0.0017425151,0.00073941576,0.023411417],"category_scores_gemma":[0.003310896,0.0008165883,0.0021605634,0.003226455,0.0004060047,0.0016393579,0.0016504736,0.0013857768,0.011529883],"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":[0.00021467685,0.00021227477,0.0030376716,0.00015596373,0.00022293693,0.00007911126,0.00028405013,0.015347707,0.0064549623,0.0044614314,0.050617173,0.918912],"study_design_scores_gemma":[0.000075883305,0.00014188283,0.013852747,0.000045250108,0.00017972176,0.00020707361,0.00037198997,0.8974318,0.019645747,0.0108334,0.05705527,0.00015925958],"about_ca_topic_score_codex":0.023442348,"about_ca_topic_score_gemma":0.034672823,"teacher_disagreement_score":0.023442348,"about_ca_system_score_codex":0.0006582626,"about_ca_system_score_gemma":0.0015094292,"threshold_uncertainty_score":0.07831901},"labels":[],"label_agreement":null},{"id":"W4392173928","doi":"10.1007/978-981-97-0523-8_86","title":"Research on Financial Competitiveness of a Listed Company Based on DuPont Analysis Method","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Business; Accounting; Finance","score_opus":0.08582130046626284,"score_gpt":0.3577469879223092,"score_spread":0.27192568745604634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392173928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80035025,0.0052031646,0.042431477,0.0007464022,0.000100211546,0.00017738974,0.0010668068,0.00012781973,0.14979655],"genre_scores_gemma":[0.9661414,0.001629897,0.017484074,0.00006547233,0.00006145795,0.00012063309,0.000586193,0.000018017621,0.013892759],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988663,0.000380816,0.000046814213,0.00019581016,0.00037907602,0.00013120785],"domain_scores_gemma":[0.9984555,0.0008405616,0.00015211622,0.000055339704,0.00042889433,0.0000675858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011863965,0.0005056565,0.00044992665,0.0076890956,0.0009925134,0.00189816,0.0006819753,0.00044282255,0.0047056805],"category_scores_gemma":[0.001764374,0.00013905013,0.0006277014,0.0067905816,0.0005554087,0.0020498226,0.000511947,0.00040202087,0.00041148707],"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":[0.0006034628,0.00033234849,0.2525863,0.00097645726,0.00037357715,0.0010814309,0.004313472,0.014992426,0.019638127,0.18313341,0.0074057463,0.51456326],"study_design_scores_gemma":[0.000084311585,0.0013223542,0.64891136,0.00053862465,0.0009874424,0.0017495416,0.02057151,0.16096653,0.032622214,0.058178987,0.073805,0.00026214545],"about_ca_topic_score_codex":0.017250843,"about_ca_topic_score_gemma":0.018840166,"teacher_disagreement_score":0.017250843,"about_ca_system_score_codex":0.0022427025,"about_ca_system_score_gemma":0.0016279636,"threshold_uncertainty_score":0.034300864},"labels":[],"label_agreement":null},{"id":"W4392174233","doi":"10.1007/978-981-97-0523-8_54","title":"Analysis and Forecast of USD/EUR Exchange Rate Based on ARIMA and GARCH Models","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Autoregressive integrated moving average; Autoregressive conditional heteroskedasticity; Econometrics; Exchange rate; Economics; Statistics; Mathematics; Time series; Volatility (finance); Finance","score_opus":0.08509245611221859,"score_gpt":0.2644115267625414,"score_spread":0.17931907065032282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392174233","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4811691,0.0045586834,0.4927282,0.0007906418,0.00045011382,0.000042942753,0.0012216329,0.0015163184,0.01752232],"genre_scores_gemma":[0.9472734,0.0016867873,0.042605806,0.00004890241,0.0001338532,0.000017647564,0.0014114875,0.0000922774,0.006729875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987876,0.000026397372,0.000009235146,0.000025649708,0.000046217185,0.000013710301],"domain_scores_gemma":[0.9998462,0.00007863764,0.000013257553,0.000011273537,0.000045963996,0.000004594776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040485297,0.0003137947,0.0002965225,0.0005035748,0.00012643334,0.00057277665,0.00027003596,0.00031785225,0.0011669097],"category_scores_gemma":[0.00089473283,0.00019683993,0.0005504319,0.0004084903,0.00008866177,0.0007138732,0.00012376471,0.0004879922,0.00030519758],"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":[0.00020131929,0.000065951186,0.009059917,0.000117889,0.00015595206,0.00023648994,0.00007723744,0.77826536,0.01233559,0.016880866,0.00565909,0.17694427],"study_design_scores_gemma":[0.000003991446,0.000014124224,0.002933859,0.0000046561913,0.000017892311,0.00002559262,0.000009946582,0.99226296,0.001446135,0.0025056112,0.00076629635,0.000008963812],"about_ca_topic_score_codex":0.010191256,"about_ca_topic_score_gemma":0.005646739,"teacher_disagreement_score":0.010191256,"about_ca_system_score_codex":0.0002489632,"about_ca_system_score_gemma":0.00032868734,"threshold_uncertainty_score":0.02026391},"labels":[],"label_agreement":null},{"id":"W4392174247","doi":"10.1007/978-981-97-0523-8_166","title":"Addressing Credit Fraud Threat: Detected Through Supervised Machine Learning Model","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Machine learning; Computer science; Artificial intelligence; Business","score_opus":0.10920659951861404,"score_gpt":0.31604332168910093,"score_spread":0.20683672217048688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392174247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30509344,0.0025848122,0.649512,0.008287704,0.00094534206,0.00030026364,0.0010417036,0.0034674197,0.028767291],"genre_scores_gemma":[0.93757695,0.0005955771,0.053968266,0.000491563,0.00039222956,0.000052952175,0.0007789399,0.000059213256,0.00608445],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999035,0.00027348622,0.00004599714,0.00014588087,0.00039653547,0.00010309697],"domain_scores_gemma":[0.9963541,0.0016281746,0.0005175327,0.00046074102,0.0008884904,0.00015105106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018233313,0.00066163565,0.00067378423,0.001180787,0.00056885206,0.0018481999,0.0010248369,0.0015472965,0.0019311743],"category_scores_gemma":[0.008365804,0.00022182359,0.00042781758,0.0007743746,0.0005403524,0.0024472068,0.0009282951,0.0021026896,0.0008826618],"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":[0.00054109714,0.0012468394,0.05342992,0.00020362013,0.00013521533,0.000557845,0.00023989228,0.12291723,0.008274137,0.023705568,0.067395724,0.7213529],"study_design_scores_gemma":[0.00000979751,0.00006059242,0.003303261,0.000025799738,0.000018243181,0.00018403397,0.000070863236,0.9734883,0.0033554765,0.01659976,0.0028707017,0.000013200057],"about_ca_topic_score_codex":0.0019356884,"about_ca_topic_score_gemma":0.0018455039,"teacher_disagreement_score":0.0019356884,"about_ca_system_score_codex":0.000751711,"about_ca_system_score_gemma":0.0012373498,"threshold_uncertainty_score":0.009642839},"labels":[],"label_agreement":null},{"id":"W4392174322","doi":"10.1007/978-981-97-0523-8_99","title":"The Impact of Capital Globalization on Green Innovation: A Cross-Country Empirical Analysis","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Globalization; Economic geography; Capital (architecture); Cross country; Economics; Business; Demographic economics; Geography; Market economy","score_opus":0.04007864590801262,"score_gpt":0.3039023306168213,"score_spread":0.2638236847088087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392174322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822911,0.0029917408,0.0011945533,0.00071945455,0.00004833426,0.000019192572,0.0010691815,0.000039527455,0.011626932],"genre_scores_gemma":[0.99280906,0.0016478077,0.00025636848,0.00010646551,0.000041165953,0.000014872156,0.0009696514,0.000016444528,0.0041381754],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920005,0.0003400655,0.000029269679,0.00010225528,0.000070833674,0.00025749742],"domain_scores_gemma":[0.988724,0.00751382,0.0020315766,0.00041253754,0.000576528,0.0007416981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019672557,0.00054440234,0.0006650745,0.0018649617,0.0007132571,0.0030181059,0.0005685019,0.00086681364,0.0060329014],"category_scores_gemma":[0.0050556287,0.00027053745,0.0018507369,0.0034289637,0.0015819089,0.0027800733,0.0018914883,0.0017147085,0.000908671],"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":[0.0010436241,0.000818295,0.84695727,0.00037744988,0.0018087754,0.0019474068,0.0015237401,0.052849386,0.0006342959,0.03527328,0.014459325,0.04230711],"study_design_scores_gemma":[0.000097414086,0.000600891,0.92621094,0.00041382058,0.0018316786,0.0005558786,0.010775988,0.02876104,0.0015756277,0.014425085,0.014624383,0.0001273031],"about_ca_topic_score_codex":0.026369559,"about_ca_topic_score_gemma":0.02968878,"teacher_disagreement_score":0.026369559,"about_ca_system_score_codex":0.0012831313,"about_ca_system_score_gemma":0.0011118938,"threshold_uncertainty_score":0.05243218},"labels":[],"label_agreement":null},{"id":"W4392174383","doi":"10.1007/978-981-97-0523-8_174","title":"Analysis of Influencing Factors of Housing Affordability Crisis in Vancouver","year":2024,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"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":"Business","score_opus":0.040035046512694496,"score_gpt":0.25267248474341136,"score_spread":0.21263743823071687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392174383","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933581,0.00020163447,0.000043665437,0.0005028771,0.0000050735534,0.000011369873,0.0005291029,0.0000031800942,0.0053450596],"genre_scores_gemma":[0.99694926,0.00024099459,0.000022755314,0.000031328716,0.0000035771538,0.000004666396,0.00028692,0.0000034464792,0.0024570304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997323,0.000029596247,0.000012328354,0.000024770205,0.000050678213,0.00015034946],"domain_scores_gemma":[0.9990953,0.0001195245,0.00011899619,0.000019046654,0.00033670454,0.0003104161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020616283,0.00012146229,0.00022145566,0.0008997863,0.0014367105,0.0022444874,0.0005628526,0.00042624446,0.0043318127],"category_scores_gemma":[0.0014895408,0.00017388469,0.00023627612,0.0027928439,0.00056924013,0.00044166786,0.00094193366,0.0009686042,0.00028741665],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092891125,0.00007532014,0.98174,0.000030672523,0.00004583195,0.0004962383,0.00260599,0.0010440081,0.00036353673,0.002800122,0.0029870786,0.0077182935],"study_design_scores_gemma":[0.0000020557777,0.0000109243665,0.9827892,0.000016902975,0.000014417937,0.000039432332,0.013369959,0.0009772602,0.00008251671,0.0001975946,0.0024937694,0.0000059830686],"about_ca_topic_score_codex":0.90579253,"about_ca_topic_score_gemma":0.9605223,"teacher_disagreement_score":0.094207466,"about_ca_system_score_codex":0.010673739,"about_ca_system_score_gemma":0.008243373,"threshold_uncertainty_score":0.18952447},"labels":[],"label_agreement":null},{"id":"W4409177773","doi":"10.1007/978-981-96-3236-7_51","title":"Harnessing Twitter Sentiments for Short-Term Stock Predictions in the Digital Age","year":2025,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Term (time); Stock (firearms); Computer science; Business; Financial economics; Economics; History; Physics; Astronomy","score_opus":0.19196037181038209,"score_gpt":0.4170126909578481,"score_spread":0.225052319147466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409177773","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35994202,0.0116481455,0.47252303,0.00945627,0.0026659167,0.00024563348,0.015218407,0.004316977,0.12398365],"genre_scores_gemma":[0.8693718,0.0058885976,0.09269188,0.00063874875,0.0015802364,0.0001233754,0.00445266,0.00027086024,0.02498189],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998204,0.000047245732,0.0000129601285,0.000036563237,0.000063619926,0.000019169818],"domain_scores_gemma":[0.9989686,0.0006882664,0.00009991732,0.00008325706,0.00011933907,0.000040669926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007778951,0.0005881775,0.0002943262,0.0010670974,0.00020956715,0.0018154996,0.0003338547,0.0005605545,0.006229989],"category_scores_gemma":[0.004138358,0.0001902587,0.0003443676,0.0011635625,0.00019069893,0.0028071455,0.0006634276,0.0006929289,0.0038788128],"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":[0.00020873541,0.00019819294,0.03744608,0.00035898134,0.00017640358,0.00016515292,0.0003949228,0.0272875,0.011217793,0.018100604,0.037785955,0.8666597],"study_design_scores_gemma":[0.000024459136,0.00016215425,0.026685694,0.00022401521,0.00015331621,0.00019215385,0.00073619053,0.82271147,0.0122856265,0.09516304,0.041579984,0.00008183479],"about_ca_topic_score_codex":0.001757777,"about_ca_topic_score_gemma":0.0037332312,"teacher_disagreement_score":0.006229989,"about_ca_system_score_codex":0.0002612531,"about_ca_system_score_gemma":0.00022713518,"threshold_uncertainty_score":0.02084142},"labels":[],"label_agreement":null}]}