{"meta":{"query_hash":"c0c571d23185","filters":{"venue":"Technological and Economic Development of Economy"},"cohort_total":21,"direct_labels_cover":0,"predictions_cover":21,"exported":21,"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/c0c571d23185","api":"https://metacan.xera.ac/api/v1/cohort?venue=Technological+and+Economic+Development+of+Economy"},"results":[{"id":"W1519032648","doi":"10.3846/13928619.2007.9637780","title":"MANAGERIAL AND ECONOMIC OPTIMISATIONS FOR PREFABRICATED BUILDING SYSTEMS","year":2007,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"BIM and Construction Integration","field":"Engineering","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":"British Columbia Institute of Technology","funders":"","keywords":"Simple (philosophy); Point (geometry); Architectural engineering; Computer science; Risk analysis (engineering); Environmental economics; Business; Economics; Engineering; Mathematics","score_opus":0.01536978068560412,"score_gpt":0.20537390783205434,"score_spread":0.1900041271464502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1519032648","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":[0.067595474,0.0021764992,0.86480147,0.0016428183,0.00018396051,0.00020146773,0.00013345583,0.00013435564,0.06313046],"genre_scores_gemma":[0.8066528,0.001624703,0.17463714,0.00009563382,0.00011340681,0.0003142208,0.00013377456,0.000080172504,0.016348112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963632,0.0016644141,0.0001155808,0.00032614544,0.0011868624,0.00034384115],"domain_scores_gemma":[0.998047,0.0011550356,0.00026405652,0.00021507397,0.00021194886,0.000106943146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003188987,0.0010565575,0.0008919235,0.0009185444,0.0007860684,0.0033195098,0.0010159812,0.0015990052,0.007931057],"category_scores_gemma":[0.00597553,0.0007440779,0.0009304814,0.001034051,0.0018076443,0.0028163253,0.0019549215,0.0018263654,0.00056306215],"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":[0.000053890548,0.000079312704,0.0004128909,0.00015387799,0.000025472751,0.00010124727,0.00013696245,0.799935,0.00190634,0.17020336,0.0006687069,0.026322892],"study_design_scores_gemma":[0.000037175258,0.0001978643,0.0014193828,0.0000901508,0.000028910017,0.00013449017,0.0003062686,0.76763254,0.0014932384,0.2128448,0.015763493,0.000051625044],"about_ca_topic_score_codex":0.0018597657,"about_ca_topic_score_gemma":0.0024739888,"teacher_disagreement_score":0.007931057,"about_ca_system_score_codex":0.0023733003,"about_ca_system_score_gemma":0.0016456195,"threshold_uncertainty_score":0.026531994},"labels":[],"label_agreement":null},{"id":"W1561502092","doi":"10.3846/13928619.2007.9637803","title":"RELEVANT CODES AND REGULATIONS: EFFECTS ON THE DESIGN OF INDUSTRIAL CONSTRUCTION","year":2007,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Function (biology); Field (mathematics); Industrial design; Work (physics); Construction engineering; Computer science; Risk analysis (engineering); Engineering; Business; Mechanical engineering","score_opus":0.13307987757733417,"score_gpt":0.3729843698044275,"score_spread":0.23990449222709334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1561502092","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":[0.39556128,0.0045843953,0.25560546,0.015659614,0.0014704418,0.0009456954,0.0003800813,0.0011379566,0.32465506],"genre_scores_gemma":[0.91993606,0.0013105117,0.058991723,0.0018943766,0.00019800416,0.00057173177,0.00015051042,0.00027763794,0.016669424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9131527,0.042188074,0.005741925,0.0024734498,0.034395453,0.0020484312],"domain_scores_gemma":[0.8606305,0.07679901,0.024777634,0.012780149,0.023614733,0.0013979292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023046346,0.00077329023,0.0003896967,0.0018974743,0.0039730924,0.005478046,0.0015929472,0.002976201,0.003329038],"category_scores_gemma":[0.082554795,0.00080368755,0.000699008,0.0013963191,0.010257733,0.0021906192,0.0034448088,0.0026292994,0.00084901875],"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":[0.00035187678,0.00041622025,0.044761978,0.00090202736,0.000055664455,0.00096281973,0.026801828,0.024528721,0.007315155,0.72200096,0.010040388,0.16186233],"study_design_scores_gemma":[0.00025340344,0.0010930838,0.08148915,0.005244476,0.00031374997,0.0023734213,0.022180505,0.02249406,0.026322525,0.24830763,0.5890942,0.00083368813],"about_ca_topic_score_codex":0.0114874905,"about_ca_topic_score_gemma":0.012030185,"teacher_disagreement_score":0.023046346,"about_ca_system_score_codex":0.004907538,"about_ca_system_score_gemma":0.0091795055,"threshold_uncertainty_score":0.1218822},"labels":[],"label_agreement":null},{"id":"W1590057214","doi":"10.1080/13928619.2004.9637667","title":"The evaluation model of construction companies’ personnel safety and health system","year":2004,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Work (physics); Business; Economics; Operations management; Engineering; Geography","score_opus":0.15705981189287035,"score_gpt":0.4018467398267603,"score_spread":0.24478692793388993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590057214","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":[0.3098156,0.0009431031,0.61782044,0.0043235784,0.00012973933,0.00023766283,0.0013312246,0.0006557114,0.06474283],"genre_scores_gemma":[0.9791574,0.0001744132,0.007302029,0.000039434733,0.000027300252,0.00013279037,0.00022627859,0.00002078669,0.012919565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99891543,0.0004814767,0.000029100656,0.00019714682,0.00015500729,0.00022189946],"domain_scores_gemma":[0.99811745,0.0010024381,0.00016297725,0.00006993398,0.0004836468,0.0001635772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023108448,0.0007173004,0.00058240327,0.0010774318,0.0005692768,0.0019504135,0.0013818771,0.0013066622,0.012998339],"category_scores_gemma":[0.0049346243,0.00032246203,0.0007227906,0.00069000234,0.0009809238,0.0018462103,0.0008893912,0.00087811897,0.0010651327],"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":[0.00017415438,0.000092964314,0.0072757215,0.00006841338,0.00006352876,0.00022272648,0.00028941937,0.8660907,0.0006707437,0.10404524,0.002708423,0.018297983],"study_design_scores_gemma":[0.000009776474,0.000036525933,0.00095709955,0.0000084784415,0.000018754321,0.000024778545,0.00004819865,0.9868788,0.00008510655,0.011398142,0.000526597,0.00000772264],"about_ca_topic_score_codex":0.023099706,"about_ca_topic_score_gemma":0.009498755,"teacher_disagreement_score":0.023099706,"about_ca_system_score_codex":0.003743222,"about_ca_system_score_gemma":0.0017141257,"threshold_uncertainty_score":0.045930505},"labels":[],"label_agreement":null},{"id":"W2016403262","doi":"10.3846/20294913.2014.915245","title":"CRITICALITY ASSESSMENT OF ENERGY INFRASTRUCTURE","year":2014,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Environmental and Industrial Safety","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Lietuvos Mokslo Taryba","keywords":"Critical infrastructure; Criticality; Interdependence; Critical infrastructure protection; Electricity; Ukrainian; Measure (data warehouse); Element (criminal law); Energy sector; Energy security; Unit (ring theory); Business; Computer science; Environmental economics; Risk analysis (engineering); Computer security; Engineering; Economics; Renewable energy","score_opus":0.0104350168575655,"score_gpt":0.20929028519227424,"score_spread":0.19885526833470873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016403262","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":[0.4411719,0.0009907841,0.52606183,0.00017337925,0.00006121646,0.0003202904,0.00042161767,0.00032145964,0.030477464],"genre_scores_gemma":[0.9809343,0.00030325665,0.016898055,0.00001144042,0.000015977415,0.00005073793,0.00016297757,0.000027074788,0.001596052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994313,0.00010184203,0.000023976878,0.00008429572,0.00028238105,0.00007620839],"domain_scores_gemma":[0.9992094,0.00026020268,0.0001321415,0.00004401452,0.00030895649,0.000045258163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053872913,0.00077655376,0.0003379319,0.0039237663,0.0004217206,0.0009368812,0.0004422906,0.0005179837,0.0021756077],"category_scores_gemma":[0.0018426374,0.00029190278,0.00054320943,0.00088752335,0.0005745816,0.0011676685,0.00090874644,0.0003870023,0.00021520903],"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":[0.0002474672,0.00009003893,0.026560178,0.00060019287,0.00011257593,0.00077052956,0.00060683006,0.70312315,0.06970278,0.03347793,0.0014714497,0.16323693],"study_design_scores_gemma":[0.000014196036,0.00026515502,0.013972004,0.0000918862,0.000055471493,0.000543694,0.00056270586,0.9138399,0.038908623,0.024998622,0.0066931406,0.00005459899],"about_ca_topic_score_codex":0.0022305534,"about_ca_topic_score_gemma":0.0018386503,"teacher_disagreement_score":0.0039237663,"about_ca_system_score_codex":0.00087218673,"about_ca_system_score_gemma":0.00073904597,"threshold_uncertainty_score":0.0072780848},"labels":[],"label_agreement":null},{"id":"W2023997099","doi":"10.3846/1392-8619.2009.15.26-38","title":"ASPECTS OF THE NATIONAL URBAN POLICY MANAGEMENT UNDER CONDITIONS OF INTEGRATED PLANNING","year":2009,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Local Economic Development and Planning","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Harmony (color); Autonomy; Architecture; Business; Government (linguistics); Politics; Urban planning; Economic growth; Public administration; Political science; Economic system; Economics; Engineering; Geography","score_opus":0.03537771457070477,"score_gpt":0.28205372907256754,"score_spread":0.24667601450186277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023997099","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":[0.43020704,0.0027483848,0.021581847,0.01265984,0.00020761759,0.00028650134,0.00048882194,0.0001802047,0.53163975],"genre_scores_gemma":[0.9666725,0.0006751898,0.003515958,0.00021168804,0.000027680626,0.00009592886,0.00017646307,0.000027147356,0.028597517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99827504,0.00056861626,0.000085168685,0.00018398034,0.0003424425,0.0005446039],"domain_scores_gemma":[0.99958557,0.00006513874,0.0000715491,0.00005023557,0.00012224702,0.000105268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001580344,0.00019574392,0.00022481171,0.0010203224,0.0022029884,0.006554409,0.0007388072,0.0005744195,0.0063080844],"category_scores_gemma":[0.0014990239,0.00018823234,0.0002743074,0.0016557722,0.0018992606,0.001762305,0.0035133925,0.000675507,0.00034458024],"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":[0.00010813335,0.00011302316,0.020715475,0.0003365123,0.000091447364,0.00088882813,0.010967448,0.034970254,0.00075444515,0.7515853,0.018691124,0.16077809],"study_design_scores_gemma":[0.000037596754,0.00014280839,0.10895204,0.0007218659,0.00010991003,0.00044943448,0.052022632,0.040813267,0.0020050684,0.23946746,0.5552002,0.00007768765],"about_ca_topic_score_codex":0.031245217,"about_ca_topic_score_gemma":0.033863463,"teacher_disagreement_score":0.031245217,"about_ca_system_score_codex":0.0113925375,"about_ca_system_score_gemma":0.0138626,"threshold_uncertainty_score":0.082659006},"labels":[],"label_agreement":null},{"id":"W2092929733","doi":"10.3846/2029-0187.2008.14.11-28","title":"GEOGRAPHIC INFORMATION E‐TRAINING INITIATIVES FOR NATIONAL SPATIAL DATA INFRASTRUCTURES / GEOGRAFINĖS INFORMACIJOS E. MOKYMO INICIATYVOS NACIONALINĖMS ERDVINIŲ DUOMENŲ INFRASTRUKTŪROMS","year":2008,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Geography Education and Pedagogy","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Island University","funders":"","keywords":"Geographic information system; Public participation GIS; Curriculum; Spatial analysis; Geography; GIS and public health; Computer science; Cartography; Political science; Remote sensing","score_opus":0.09169261842783757,"score_gpt":0.32142039858645693,"score_spread":0.22972778015861936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092929733","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":[0.33657348,0.0038264547,0.03504026,0.031984195,0.0009659244,0.0011312062,0.0015913529,0.0025511628,0.586336],"genre_scores_gemma":[0.6253934,0.0030055386,0.0625973,0.0018562918,0.00023512007,0.00071809645,0.0025188825,0.00025467068,0.3034207],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991366,0.00029090967,0.00004070358,0.000115197035,0.00018250466,0.00023411657],"domain_scores_gemma":[0.9981298,0.00023455321,0.00017268992,0.00019640407,0.00036010245,0.0009065104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017698312,0.0002098851,0.00016490262,0.0012202698,0.0013718342,0.0024545009,0.00062950054,0.00084415724,0.022967028],"category_scores_gemma":[0.0019249857,0.00015013701,0.00026334752,0.0010867997,0.0006266002,0.001410685,0.004034911,0.0007528275,0.004090221],"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":[0.00011253407,0.0010360627,0.04155062,0.000543576,0.00001378835,0.00034739362,0.0079098595,0.0018311633,0.0054748156,0.08689881,0.109996796,0.74428463],"study_design_scores_gemma":[0.000017086835,0.00014402102,0.056315415,0.00025297308,0.000008445361,0.00021675277,0.004607881,0.0013839387,0.0019673214,0.0030134541,0.9320574,0.000015338495],"about_ca_topic_score_codex":0.0055424166,"about_ca_topic_score_gemma":0.0061578196,"teacher_disagreement_score":0.022967028,"about_ca_system_score_codex":0.0020020732,"about_ca_system_score_gemma":0.008040293,"threshold_uncertainty_score":0.07683241},"labels":[],"label_agreement":null},{"id":"W2340197128","doi":"10.3846/20294913.2015.1074129","title":"Analysis of project success factors in construction industry","year":2015,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Petro-Canada","funders":"","keywords":"Scope (computer science); Critical success factor; Schedule; Quality (philosophy); Business; Work (physics); Rank (graph theory); Construction industry; Order (exchange); Test (biology); Operations management; Marketing; Computer science; Process management; Engineering; Construction engineering; Finance","score_opus":0.14868826000561033,"score_gpt":0.34193494650788847,"score_spread":0.19324668650227814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340197128","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":[0.99469274,0.00018036512,0.0016441841,0.00006685071,0.0000044477656,0.000091124086,0.00013332945,0.000010769473,0.003176154],"genre_scores_gemma":[0.99886453,0.0000923772,0.0006497388,0.0000036482968,0.0000027246858,0.000040277333,0.00010060612,0.0000032320484,0.0002427503],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997017,0.00072336436,0.00029162524,0.00014837965,0.0013619789,0.00045767915],"domain_scores_gemma":[0.9817894,0.009225942,0.0029845366,0.00033277782,0.00409288,0.0015745764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029942235,0.00041559478,0.00036195063,0.0069093527,0.00065327773,0.0012899799,0.00029031996,0.00029297118,0.002793962],"category_scores_gemma":[0.015504122,0.00020126441,0.0005379556,0.0045883046,0.0005644479,0.000677703,0.0007892686,0.00036093206,0.0003264812],"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":[0.0001935802,0.00021898931,0.93351376,0.00025085086,0.000107231885,0.00041154076,0.0029443065,0.0015818108,0.0012602289,0.0009248177,0.0005783981,0.058014333],"study_design_scores_gemma":[0.000005466185,0.00032152227,0.98618746,0.00008070379,0.0000387887,0.00022773656,0.0072914455,0.0027888233,0.000661523,0.0003367513,0.002035789,0.000023982435],"about_ca_topic_score_codex":0.0035785611,"about_ca_topic_score_gemma":0.0034345002,"teacher_disagreement_score":0.0069093527,"about_ca_system_score_codex":0.0012075492,"about_ca_system_score_gemma":0.002230928,"threshold_uncertainty_score":0.015835166},"labels":[],"label_agreement":null},{"id":"W2805684079","doi":"10.3846/20294913.2017.1280557","title":"TECHNOLOGICAL SOURCES OF ECONOMIC GROWTH IN EUROPE AND THE U.S.","year":2018,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","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":"University of Waterloo","funders":"Junta de Andalucía; Universidad de Málaga","keywords":"Economics; Technological change; Technical change; Investment (military); Growth accounting; Productivity; Technical progress; Human capital; Total factor productivity; General equilibrium theory; Capital accumulation; Capital (architecture); Growth model; Macroeconomics; Economic growth","score_opus":0.024689143060715294,"score_gpt":0.19408590342006415,"score_spread":0.16939676035934886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805684079","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":[0.9727922,0.005988439,0.0006615783,0.0007974126,0.000035771733,0.000008330032,0.0028066793,0.000035459416,0.01687403],"genre_scores_gemma":[0.99273795,0.0033465528,0.00029943167,0.000053347732,0.000028864704,0.0000075414355,0.0024009573,0.000009970714,0.0011153569],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997323,0.000047875445,0.00002261834,0.000042507454,0.00006899267,0.000085583335],"domain_scores_gemma":[0.9989806,0.0002881167,0.00038778325,0.00005314204,0.00020225467,0.00008819318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006588541,0.00029929972,0.00020467954,0.0037422352,0.0002446822,0.0011693347,0.00013544405,0.0002376081,0.000738771],"category_scores_gemma":[0.002183004,0.000085029205,0.00038243935,0.005917287,0.00034493374,0.0007181331,0.0011589471,0.00031168852,0.0002275186],"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":[0.00020609846,0.00006579617,0.87309796,0.000121515084,0.0001669708,0.0006845587,0.0008372547,0.008067815,0.0005480084,0.009933585,0.0043299203,0.101940624],"study_design_scores_gemma":[0.000008743989,0.000029806171,0.98036134,0.000075888114,0.00006257567,0.00024575912,0.0007188815,0.0014787328,0.00052152784,0.0015847189,0.014896963,0.0000151129],"about_ca_topic_score_codex":0.019079912,"about_ca_topic_score_gemma":0.020380793,"teacher_disagreement_score":0.019079912,"about_ca_system_score_codex":0.00084417535,"about_ca_system_score_gemma":0.0007294918,"threshold_uncertainty_score":0.03793776},"labels":[],"label_agreement":null},{"id":"W2886379489","doi":"10.3846/tede.2018.4531","title":"STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION","year":2018,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Innovation Diffusion and Forecasting","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":"York University","funders":"","keywords":"Computer science; Product (mathematics); Process (computing); Industrial organization; Supply and demand; Process management; Game theory; Business; Economics; Microeconomics; Mathematics","score_opus":0.11842309530459443,"score_gpt":0.30189579466942046,"score_spread":0.18347269936482602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886379489","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":[0.34938872,0.00080528023,0.56887275,0.002894333,0.00013491725,0.0004956879,0.00066976313,0.00018472968,0.07655384],"genre_scores_gemma":[0.96522,0.00041612578,0.021404771,0.000103104205,0.000024872865,0.00030896752,0.000095726275,0.000014576141,0.012411967],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924314,0.00039164798,0.00003146423,0.000108236665,0.00009854751,0.0001270902],"domain_scores_gemma":[0.9970169,0.0021641455,0.00035076047,0.00008432345,0.00020523778,0.00017869193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015142015,0.0009402587,0.0012265905,0.0008961969,0.0007246241,0.0024242592,0.0019563856,0.002861236,0.007742162],"category_scores_gemma":[0.004941909,0.00045258284,0.0010893288,0.000999019,0.0015648961,0.002274696,0.0013967083,0.0015904185,0.0006133448],"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":[0.000101311234,0.00012505603,0.0010054685,0.000057541387,0.000027703369,0.0001811894,0.00017481271,0.83977246,0.00072940544,0.15369026,0.00046310754,0.003671714],"study_design_scores_gemma":[0.000025806115,0.00004347643,0.00012219131,0.000008734314,0.0000132367695,0.000019224666,0.000041047013,0.98318243,0.00008037144,0.015992675,0.00045806734,0.000012753274],"about_ca_topic_score_codex":0.009478243,"about_ca_topic_score_gemma":0.0052303053,"teacher_disagreement_score":0.009478243,"about_ca_system_score_codex":0.0021190704,"about_ca_system_score_gemma":0.0016513955,"threshold_uncertainty_score":0.025900126},"labels":[],"label_agreement":null},{"id":"W2901056090","doi":"10.3846/tede.2018.5694","title":"INTERNAL R&amp;amp;D AND EXTERNAL INFORMATION IN KNOWLEDGE-INTENSIVE BUSINESS SERVICE INNOVATION: COMPLEMENTS, SUBSTITUTES OR INDEPENDENT?","year":2018,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; HEC Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Business; Industrial organization; Service (business); Order (exchange); Logistic regression; Marketing; Knowledge management; Computer science; Statistics; Mathematics; Finance","score_opus":0.0891580929911921,"score_gpt":0.2789543875510317,"score_spread":0.1897962945598396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901056090","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":[0.98595667,0.0016536405,0.00089533004,0.00066380034,0.000011794385,0.000034609235,0.0003733943,0.000012992706,0.0103978235],"genre_scores_gemma":[0.99810684,0.00045436114,0.00027114354,0.000062041385,0.00002030908,0.000010264852,0.00018244961,0.000004555013,0.0008879948],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99302167,0.0021634994,0.0005098586,0.0008105149,0.0020615568,0.0014329029],"domain_scores_gemma":[0.9023609,0.061212696,0.023036629,0.0030470947,0.004726815,0.0056158206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0078093135,0.000611692,0.0011185574,0.0046668653,0.00096229644,0.005123984,0.0010223147,0.0013453241,0.004778591],"category_scores_gemma":[0.027401362,0.00046506073,0.0018121671,0.0068769357,0.0030782002,0.0035101138,0.0047513135,0.0014423701,0.00066703215],"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":[0.0001998881,0.00022031141,0.97586006,0.00014336621,0.0005132849,0.00027489857,0.0008804383,0.0013391051,0.00031981868,0.003072059,0.0001961489,0.016980687],"study_design_scores_gemma":[0.000027297916,0.00020558274,0.98963165,0.00019829518,0.0006228229,0.00012784207,0.0026902985,0.0021144154,0.0007390029,0.001524637,0.0020812883,0.00003680616],"about_ca_topic_score_codex":0.124488264,"about_ca_topic_score_gemma":0.1251743,"teacher_disagreement_score":0.124488264,"about_ca_system_score_codex":0.0051782364,"about_ca_system_score_gemma":0.006920633,"threshold_uncertainty_score":0.2475273},"labels":[],"label_agreement":null},{"id":"W2911995299","doi":"10.3846/tede.2019.7686","title":"NETWORK TOPOLOGY OF RENEWABLE ENERGY COMPANIES: MINIMAL SPANNING TREE AND SUB-DOMINANT ULTRAMETRIC FOR THE AMERICAN STOCK","year":2019,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Shiraz University","keywords":"Renewable energy; Ultrametric space; Spanning tree; Wind power; Business; Environmental economics; Solar energy; Economics; Computer science; Econometrics; Mathematics; Engineering; Electrical engineering","score_opus":0.02768446468299792,"score_gpt":0.20647293650472864,"score_spread":0.17878847182173072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911995299","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":[0.9158792,0.0006647709,0.07648731,0.0005826144,0.000024184186,0.000036393852,0.0014587214,0.00013417931,0.0047325916],"genre_scores_gemma":[0.98872095,0.0002730409,0.009337094,0.000024501513,0.000012547825,0.000019158198,0.00088786,0.000008506532,0.0007163397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997335,0.00006955104,0.000019831157,0.0000668148,0.000060389313,0.000049963193],"domain_scores_gemma":[0.9989027,0.00035653278,0.0003337311,0.000068181886,0.00024120741,0.00009757331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042003274,0.00019989489,0.0002466003,0.0028818771,0.0006750189,0.0008477709,0.00042946814,0.00037585775,0.0017128029],"category_scores_gemma":[0.003212214,0.00012859236,0.00033806628,0.002190242,0.0003076973,0.0016463732,0.0004482861,0.00022555114,0.00017268464],"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":[0.0004704168,0.000169586,0.20937966,0.00032786088,0.00023048236,0.0011247982,0.0016955404,0.42276874,0.0073054633,0.14048035,0.012366056,0.203681],"study_design_scores_gemma":[0.000009792655,0.000060958915,0.049494516,0.000040160372,0.000050920302,0.00054374774,0.00079175096,0.888921,0.0010309819,0.054976,0.004051668,0.000028530272],"about_ca_topic_score_codex":0.0062198243,"about_ca_topic_score_gemma":0.0068603596,"teacher_disagreement_score":0.0062198243,"about_ca_system_score_codex":0.00080402766,"about_ca_system_score_gemma":0.00032879453,"threshold_uncertainty_score":0.012367249},"labels":[],"label_agreement":null},{"id":"W2977485423","doi":"10.3846/tede.2019.11094","title":"THE INNOVATION PROCESS IN LOCAL DEVELOPMENT – THE MATERIAL, INSTITUTIONAL, AND INTELLECTUAL INFRASTRUCTURE SHAPING AND SHAPED BY INNOVATION","year":2019,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Business and Economic Development","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Process (computing); Business; Statistical inference; Computer science","score_opus":0.013185733868244263,"score_gpt":0.19907078326090313,"score_spread":0.18588504939265887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977485423","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":[0.8602827,0.0011263089,0.018961534,0.0013824542,0.000027553398,0.000229524,0.00011520749,0.00008216509,0.11779261],"genre_scores_gemma":[0.99634403,0.00015431998,0.0017175708,0.000018966402,0.0000036370886,0.000035336914,0.000018196548,0.0000050812437,0.0017028747],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9977374,0.0012728526,0.00008927773,0.00024908618,0.00028681947,0.00036461654],"domain_scores_gemma":[0.99665534,0.0015292703,0.00053778,0.00042405515,0.00043261197,0.00042093697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024683282,0.00021085049,0.00023988896,0.001736301,0.0021064938,0.0063932226,0.00070313935,0.0007074114,0.004290102],"category_scores_gemma":[0.004396774,0.00022616531,0.0005457381,0.0017348207,0.0061655403,0.0033301013,0.0039466773,0.00056405825,0.00044612968],"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":[0.00025504082,0.0005914856,0.24770166,0.0016844635,0.00021094183,0.004209149,0.18604651,0.0110045355,0.011682213,0.3075594,0.0024739075,0.22658059],"study_design_scores_gemma":[0.00006348017,0.00075842434,0.4159572,0.0012825873,0.00030672818,0.0025652589,0.2716512,0.011356539,0.008192838,0.13595009,0.15173598,0.00017976316],"about_ca_topic_score_codex":0.0031864932,"about_ca_topic_score_gemma":0.004015111,"teacher_disagreement_score":0.0063932226,"about_ca_system_score_codex":0.0030795024,"about_ca_system_score_gemma":0.0041507804,"threshold_uncertainty_score":0.022343457},"labels":[],"label_agreement":null},{"id":"W3088976571","doi":"10.3846/tede.2020.13376","title":"PREDICTORS OF INDUSTRY 4.0 TECHNOLOGIES AFFECTING LOGISTIC ENTERPRISES’ PERFORMANCE: INTERNATIONAL PERSPECTIVE FROM ECONOMIC LENS","year":2020,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Yorkville University","funders":"","keywords":"Perspective (graphical); Business; Industrial organization; Logistic regression; Industry 4.0; Emerging technologies; Industrial Revolution; Marketing; Computer science; Geography","score_opus":0.028282358316952888,"score_gpt":0.2149864680906104,"score_spread":0.1867041097736575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088976571","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":[0.9812114,0.00018661786,0.00036195145,0.00044859678,0.0000069121256,0.000008684651,0.00011912533,0.000005121931,0.017651482],"genre_scores_gemma":[0.9992362,0.00014196144,0.000094000774,0.000010920437,0.0000036860254,0.0000032349783,0.00007544355,0.000001635182,0.00043295854],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879825,0.00034442285,0.00007525847,0.00009394317,0.0003246427,0.00036337978],"domain_scores_gemma":[0.9930392,0.0024757031,0.0025889673,0.00027537422,0.0010056111,0.000615104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015107746,0.00021013098,0.00019788812,0.002052325,0.0006122925,0.0027615945,0.00023522574,0.00025524676,0.0035400235],"category_scores_gemma":[0.0074054883,0.00009167766,0.00024161053,0.0035116184,0.0011473317,0.0015589499,0.001707757,0.0007554661,0.00044457827],"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":[0.000037790396,0.00008885755,0.97682947,0.000030832533,0.000022844153,0.00027338462,0.0016094405,0.0006456761,0.000145309,0.004881758,0.00039014412,0.015044561],"study_design_scores_gemma":[0.0000017963673,0.00007005994,0.9817231,0.000069905305,0.000024444427,0.00012221176,0.012330863,0.0008365768,0.00042286626,0.00084685476,0.0035387692,0.000012455083],"about_ca_topic_score_codex":0.0055726725,"about_ca_topic_score_gemma":0.0050125974,"teacher_disagreement_score":0.0055726725,"about_ca_system_score_codex":0.0009321177,"about_ca_system_score_gemma":0.0012273273,"threshold_uncertainty_score":0.011842489},"labels":[],"label_agreement":null},{"id":"W3108792264","doi":"10.3846/tede.2020.13742","title":"EVALUATION OF THE COORDINATION BETWEEN CHINA’S TECHNOLOGY AND ECONOMY USING A GREY MULTIVARIATE COUPLING MODEL","year":2020,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Interpretability; Computer science; Convergence (economics); Heuristic; China; Process (computing); Fuzzy logic; Multivariate statistics; Coupling (piping); Investment (military); Mathematical optimization; Artificial intelligence; Economics; Mathematics; Machine learning; Engineering; Geography; Economic growth; Political science","score_opus":0.21522110957723395,"score_gpt":0.3533190470349844,"score_spread":0.13809793745775045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108792264","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":[0.5610531,0.0004196012,0.4308494,0.000497984,0.000026561678,0.000071527604,0.00027411786,0.0001444721,0.006663337],"genre_scores_gemma":[0.9898347,0.000085077416,0.009387035,0.000014464381,0.000004755271,0.00002426198,0.000080055725,0.0000066182356,0.0005630776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994205,0.00021473582,0.000030269019,0.00014482839,0.00011165353,0.00007808824],"domain_scores_gemma":[0.99932456,0.00037387776,0.00011049419,0.000039689992,0.000102176484,0.00004915712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015250318,0.0006030354,0.0006238207,0.001606775,0.00034566125,0.0013906155,0.0008078811,0.0007598986,0.0011957615],"category_scores_gemma":[0.0032683532,0.0002067187,0.0008257449,0.0015434662,0.00062322937,0.0013597762,0.0010166309,0.0004539631,0.000073722265],"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":[0.00004996133,0.000027988346,0.011878383,0.00006700846,0.00010604498,0.00011662546,0.00016980607,0.9536703,0.0013570949,0.018523838,0.00042396598,0.013608968],"study_design_scores_gemma":[0.0000032158684,0.000010370858,0.0022112494,0.0000039915517,0.000012727368,0.000008397472,0.000033558605,0.99411064,0.00014342465,0.0033459857,0.000109933106,0.0000064202804],"about_ca_topic_score_codex":0.0154888015,"about_ca_topic_score_gemma":0.0096971495,"teacher_disagreement_score":0.0154888015,"about_ca_system_score_codex":0.0016681754,"about_ca_system_score_gemma":0.0010469346,"threshold_uncertainty_score":0.030797303},"labels":[],"label_agreement":null},{"id":"W3215194498","doi":"10.3846/tede.2021.15704","title":"PARTIAL BACKORDERING INVENTORY MODEL WITH LIMITED STORAGE CAPACITY UNDER ORDER-SIZE DEPENDENT TRADE CREDIT","year":2021,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China; City University of Hong Kong","keywords":"Warehouse; Economic shortage; Renting; Economic order quantity; Profit (economics); Order (exchange); Trade credit; Inventory management; Holding cost; Business; Computer science; Inventory cost; Operations research; Mathematical optimization; Microeconomics; Economics; Operations management; Mathematics; Finance; Marketing; Supply chain","score_opus":0.04021128618228279,"score_gpt":0.19556432568823423,"score_spread":0.15535303950595145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215194498","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":[0.39351282,0.0029323301,0.5667431,0.0022973863,0.0003681159,0.00036702713,0.0032558476,0.0007329042,0.029790552],"genre_scores_gemma":[0.98204595,0.0007725265,0.0057836305,0.00007225451,0.000057302434,0.00013007548,0.00032747816,0.000034739383,0.010776086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915326,0.00019212821,0.0000677181,0.00015852475,0.00019075655,0.00023751562],"domain_scores_gemma":[0.99856454,0.00063530356,0.000344449,0.000091391325,0.00022203273,0.00014231441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012662949,0.0015413675,0.0020624117,0.0010075149,0.0007193578,0.0024992966,0.0030904615,0.0021382407,0.005416047],"category_scores_gemma":[0.0020693846,0.0011338309,0.001435811,0.0016781586,0.001477964,0.0036258348,0.0012985546,0.0016600469,0.0004956807],"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":[0.00009631598,0.00002877163,0.0007063498,0.000092744165,0.000023797102,0.00060131156,0.000046849644,0.98213124,0.00091821415,0.013269757,0.00041989502,0.001664702],"study_design_scores_gemma":[0.000030323277,0.000044106313,0.00027535312,0.000011229195,0.000019127263,0.00007088243,0.000026216097,0.9925684,0.00015964555,0.0064640334,0.00031723946,0.000013463318],"about_ca_topic_score_codex":0.015600385,"about_ca_topic_score_gemma":0.00880772,"teacher_disagreement_score":0.015600385,"about_ca_system_score_codex":0.0021215181,"about_ca_system_score_gemma":0.0022617134,"threshold_uncertainty_score":0.031019151},"labels":[],"label_agreement":null},{"id":"W4200207099","doi":"10.3846/tede.2021.15335","title":"GLOBAL SUPPLY CHAIN RELATIONSHIP, LOCAL MARKET COMPETITION, AND SUPPLIERS’ INNOVATION IN DEVELOPING ECONOMIES","year":2021,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","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":"University of Ottawa","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Supply chain; Industrial organization; Competition (biology); Business; Profit (economics); Market power; Cluster (spacecraft); Horizontal and vertical; Global value chain; Economic geography; Economics; Marketing; International trade; Microeconomics; Comparative advantage; Monopoly; Computer science","score_opus":0.01794564838190061,"score_gpt":0.21260347115055647,"score_spread":0.19465782276865587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200207099","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":[0.9553307,0.0007647292,0.010223775,0.00063035556,0.000005486417,0.000023686398,0.00003617384,0.000009156896,0.032976042],"genre_scores_gemma":[0.9990845,0.00022086124,0.00024065429,0.000009698451,0.0000016699072,0.000003721232,0.0000046219525,7.10324e-7,0.00043367085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9996056,0.00015345776,0.000016654974,0.00005054423,0.00007147783,0.000102266444],"domain_scores_gemma":[0.9980216,0.0011077669,0.00050853915,0.00004447337,0.00015672283,0.00016094741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092843216,0.00016927674,0.00026340678,0.0011622106,0.0006229221,0.0018587152,0.00021246982,0.0003994554,0.0028179968],"category_scores_gemma":[0.002565413,0.00012516636,0.0003212022,0.0015046564,0.0018238765,0.0020361266,0.0011621724,0.0004493771,0.000094484145],"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":[0.00014836692,0.00027964884,0.25255135,0.00032710668,0.00019402232,0.0019446933,0.006093884,0.09708871,0.0033285539,0.59101343,0.00094463705,0.04608559],"study_design_scores_gemma":[0.00011309761,0.00053263846,0.34047195,0.00038218437,0.00045198662,0.0010525011,0.022330891,0.18604007,0.0041018394,0.4216283,0.022723949,0.00017064181],"about_ca_topic_score_codex":0.005098933,"about_ca_topic_score_gemma":0.006436861,"teacher_disagreement_score":0.005098933,"about_ca_system_score_codex":0.0020675724,"about_ca_system_score_gemma":0.0014104787,"threshold_uncertainty_score":0.015001297},"labels":[],"label_agreement":null},{"id":"W4211123160","doi":"10.3846/tede.2022.16321","title":"THE TRADE-OFF BETWEEN CORPORATE SOCIAL RESPONSIBILITY AND COMPETITIVE ADVANTAGE: A BIFORM GAME MODEL","year":2022,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Corporate Social Responsibility Reporting","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Competitive advantage; Industrial organization; Corporate social responsibility; Business; Balance (ability); Context (archaeology); Investment (military); Microeconomics; Economics; Marketing","score_opus":0.04599524790931122,"score_gpt":0.2448183237135078,"score_spread":0.1988230758041966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211123160","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":[0.21443702,0.0004432622,0.5876156,0.0055006198,0.00016468174,0.000505598,0.00067006686,0.00016221164,0.19050096],"genre_scores_gemma":[0.9409688,0.0003858659,0.035021435,0.00034585595,0.000041387797,0.00028584854,0.00011516,0.00001241448,0.02282322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829847,0.0008780343,0.000046628178,0.00017536544,0.00026229664,0.00033921446],"domain_scores_gemma":[0.9978206,0.0012409446,0.00029388498,0.00008406369,0.00021857179,0.00034178628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026458737,0.001021676,0.00091392157,0.0010361099,0.0011417434,0.0030742632,0.0020873633,0.0027396416,0.008218072],"category_scores_gemma":[0.0038729473,0.0003188353,0.0008578676,0.0009539788,0.0024698526,0.0032209957,0.0016882916,0.0018296578,0.000633817],"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":[0.000104912084,0.00014257296,0.0010202143,0.000054215576,0.00003327871,0.00032842247,0.00034770396,0.14030197,0.0011171035,0.84834266,0.0016445493,0.0065623075],"study_design_scores_gemma":[0.000096050506,0.00012834018,0.00047881337,0.00003190852,0.00002051184,0.00010744699,0.0002902115,0.74113876,0.00020786896,0.25289065,0.004569708,0.00003971541],"about_ca_topic_score_codex":0.0133251855,"about_ca_topic_score_gemma":0.01112474,"teacher_disagreement_score":0.0133251855,"about_ca_system_score_codex":0.0038040713,"about_ca_system_score_gemma":0.002146939,"threshold_uncertainty_score":0.027600586},"labels":[],"label_agreement":null},{"id":"W4245935645","doi":"10.3846/13928619.2004.9637667","title":"THE EVALUATION MODEL OF CONSTRUCTION COMPANIES’ PERSONNEL SAFETY AND HEALTH SYSTEM","year":2004,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Risk Management in Financial Firms","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Work (physics); Business; Economics; Economy; Geography; Engineering","score_opus":0.04710408555443135,"score_gpt":0.23220918766779935,"score_spread":0.185105102113368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245935645","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":[0.22985038,0.0012203779,0.708222,0.0039973683,0.00013103454,0.00025969223,0.0012236737,0.00064150046,0.05445407],"genre_scores_gemma":[0.97161037,0.00030793075,0.012712155,0.000048077232,0.000040199233,0.00016030391,0.0002648809,0.00002269518,0.014833361],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887305,0.00044273533,0.000032174514,0.00023714463,0.0001942006,0.00022064043],"domain_scores_gemma":[0.9981704,0.0009306263,0.00017202777,0.00006995731,0.00049123645,0.00016580423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002270206,0.00077121024,0.000592031,0.0011187664,0.00057896954,0.0020885435,0.001500357,0.001309095,0.011303156],"category_scores_gemma":[0.004893665,0.00028678327,0.00065878284,0.0007858175,0.000961609,0.0022273837,0.00091677177,0.0008820805,0.00095727027],"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":[0.00018687084,0.00011790271,0.007972624,0.000095958676,0.00007592708,0.00031794532,0.0004055715,0.79386425,0.00095418125,0.1635147,0.0034450556,0.02904901],"study_design_scores_gemma":[0.000010095169,0.000046999285,0.0010621895,0.000009861465,0.00002164355,0.000042704945,0.00005144558,0.98011476,0.00011589008,0.017714558,0.00080070406,0.000009134343],"about_ca_topic_score_codex":0.017370455,"about_ca_topic_score_gemma":0.008027027,"teacher_disagreement_score":0.017370455,"about_ca_system_score_codex":0.0036182918,"about_ca_system_score_gemma":0.001754111,"threshold_uncertainty_score":0.03781283},"labels":[],"label_agreement":null},{"id":"W4255328108","doi":"10.3846/13928619.2007.9637813","title":"THE USE OF EXPLORATORY TUNNELS AS A TOOL FOR SCHEDULING AND COST ESTIMATION","year":2007,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Duration (music); Scheduling (production processes); Computer science; Excavation; Monte Carlo method; Estimation; Exploratory research; Project management; Track (disk drive); Operations research; Cost estimate; Engineering; Systems engineering; Operations management; Statistics; Geotechnical engineering","score_opus":0.040613951756539174,"score_gpt":0.2246681534651934,"score_spread":0.18405420170865422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255328108","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":[0.23223783,0.00013779322,0.7639471,0.00006567703,0.00001255527,0.0001654929,0.0006982738,0.0005515883,0.0021837065],"genre_scores_gemma":[0.829779,0.00014279028,0.16878556,0.0000057367984,0.000007254926,0.00016492116,0.00054767024,0.000055345132,0.0005117629],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844056,0.0008951989,0.00008085631,0.00015573784,0.00036403237,0.000063666965],"domain_scores_gemma":[0.9892111,0.0078104804,0.0013752568,0.000817339,0.000643488,0.00014234045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002254552,0.0006219794,0.00052680087,0.0019876587,0.00033304756,0.0006804029,0.0005967456,0.0004558066,0.0013071321],"category_scores_gemma":[0.010102287,0.0005793941,0.0005135674,0.0017521383,0.0003063409,0.0009467049,0.00049365865,0.00036323254,0.00022435901],"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":[0.00010545503,0.000053803604,0.016050447,0.000055705186,0.000045072564,0.00007913981,0.00011304904,0.9416103,0.0024408838,0.0036478553,0.00028647526,0.03551188],"study_design_scores_gemma":[0.000009115626,0.00018218685,0.0059382934,0.000019360454,0.000014231408,0.00011189077,0.00006487937,0.9896265,0.0013900538,0.0015041487,0.0011039115,0.000035338682],"about_ca_topic_score_codex":0.0066835503,"about_ca_topic_score_gemma":0.009972243,"teacher_disagreement_score":0.0066835503,"about_ca_system_score_codex":0.0005544849,"about_ca_system_score_gemma":0.001218448,"threshold_uncertainty_score":0.013289332},"labels":[],"label_agreement":null},{"id":"W4366086793","doi":"10.3846/tede.2023.18551","title":"NONPARAMETRIC NUMERICAL APPROACHES TO PROBABILITY WEIGHTING FUNCTION CONSTRUCT FOR MANIFESTATION AND PREDICTION OF RISK PREFERENCES","year":2023,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Social Science Fund of China; National Natural Science Foundation of China; City University of Hong Kong","keywords":"Weighting; Nonparametric statistics; Construct (python library); Function (biology); Econometrics; Computer science; A-weighting; Mathematics; Statistics; Medicine; Biology","score_opus":0.30294977102701076,"score_gpt":0.31691030689014743,"score_spread":0.01396053586313667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366086793","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":[0.0057798475,0.00006141749,0.9922105,0.000078986115,0.000009647802,0.000037871578,0.00004307818,0.00005714616,0.0017215273],"genre_scores_gemma":[0.32130876,0.00044941818,0.67465186,0.00009774331,0.000054863496,0.00081487175,0.00028147455,0.00007354083,0.0022673926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99514836,0.0030881986,0.00025268018,0.0006242519,0.0007303612,0.00015613949],"domain_scores_gemma":[0.98795986,0.008676432,0.0009628778,0.0012076239,0.0010479407,0.00014523105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069674267,0.0010512983,0.00064655347,0.0022757568,0.00055759406,0.002061929,0.0017263794,0.0011012444,0.005093121],"category_scores_gemma":[0.032124255,0.00041975212,0.0012441315,0.0024721492,0.0017648276,0.004013391,0.0017168681,0.0021168897,0.000593194],"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":[0.000086890526,0.00013621752,0.004154773,0.00025775767,0.000081780614,0.00017861063,0.0008711626,0.14493519,0.0030299737,0.7198295,0.0013570931,0.12508115],"study_design_scores_gemma":[0.000011215416,0.000066078486,0.0016162551,0.00005633599,0.000018434946,0.00010256479,0.0001478273,0.64854646,0.0010724948,0.34509256,0.0032209845,0.000048819824],"about_ca_topic_score_codex":0.0017909262,"about_ca_topic_score_gemma":0.0012008946,"teacher_disagreement_score":0.0069674267,"about_ca_system_score_codex":0.0011749498,"about_ca_system_score_gemma":0.0011094449,"threshold_uncertainty_score":0.03684771},"labels":[],"label_agreement":null},{"id":"W4399332524","doi":"10.3846/tede.2024.20821","title":"INVESTIGATING THE EFFECTS OF COVID-19 ON TOURISM IN THE G7 COUNTRIES","year":2024,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Tourism; 2019-20 coronavirus outbreak; Business; Economics; Geography; Virology; Biology; Medicine; Internal medicine; Outbreak; Infectious disease (medical specialty)","score_opus":0.03651939833454417,"score_gpt":0.3063026637330515,"score_spread":0.26978326539850733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399332524","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":[0.9911708,0.00027021606,0.00019730927,0.00057749887,0.000024458299,0.000019978432,0.0004526797,0.0000061826936,0.007280868],"genre_scores_gemma":[0.9988343,0.00025641237,0.00016122786,0.00008252135,0.000006579674,0.0000115930825,0.0003453767,0.0000032485696,0.00029869485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987644,0.0005024442,0.000056252917,0.00006851914,0.00018709281,0.00042145816],"domain_scores_gemma":[0.9978549,0.000660125,0.00052405027,0.00013708849,0.00054100336,0.00028272346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014662294,0.00028747116,0.00028241295,0.0009355355,0.00061161595,0.001794194,0.0002747767,0.0004512005,0.0020882406],"category_scores_gemma":[0.004444821,0.00009655849,0.00058577023,0.0016987361,0.00097645633,0.0009820932,0.0019927023,0.00092538923,0.00022512488],"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":[0.00044793673,0.00027626127,0.90752375,0.00036065723,0.0002918468,0.0023224705,0.0025542655,0.02292301,0.00090445415,0.011169412,0.007199129,0.04402685],"study_design_scores_gemma":[0.000018603561,0.0007962038,0.9253968,0.00027924523,0.000105774154,0.00031314543,0.041462384,0.01555042,0.0010324782,0.002858052,0.012122193,0.00006481137],"about_ca_topic_score_codex":0.029871656,"about_ca_topic_score_gemma":0.042248785,"teacher_disagreement_score":0.029871656,"about_ca_system_score_codex":0.0020829272,"about_ca_system_score_gemma":0.0016392744,"threshold_uncertainty_score":0.05939555},"labels":[],"label_agreement":null}]}