{"meta":{"query_hash":"5d4dd5b36749","filters":{"venue":"Information Technology and Management"},"cohort_total":20,"direct_labels_cover":0,"predictions_cover":20,"exported":20,"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/5d4dd5b36749","api":"https://metacan.xera.ac/api/v1/cohort?venue=Information+Technology+and+Management"},"results":[{"id":"W1484738640","doi":"10.1023/a:1013112826330","title":"ASSISTing Management Decisions in the Software Inspection Process","year":2002,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Census and Population Estimation","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Software inspection; Computer science; Process (computing); Software; Component (thermodynamics); Systems engineering; Software development; Software engineering; Engineering; Software quality","score_opus":0.03611539380293943,"score_gpt":0.29841105155497016,"score_spread":0.26229565775203073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1484738640","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49973097,0.000731113,0.45545706,0.0068586585,0.00018560907,0.00078675034,0.0021914984,0.004464223,0.029594166],"genre_scores_gemma":[0.7660981,0.0007647544,0.22761695,0.0001969634,0.00007118333,0.00018128981,0.0013281704,0.00010619412,0.0036365106],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970396,0.001997822,0.0002042891,0.00014406827,0.00047926835,0.00013494368],"domain_scores_gemma":[0.97110903,0.020760572,0.0028687178,0.0010155948,0.003677918,0.0005683046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034898773,0.00042695407,0.00038351747,0.0035673347,0.00087997137,0.002429996,0.00048756102,0.0006770545,0.0042720074],"category_scores_gemma":[0.057020303,0.00037510463,0.00017655178,0.0019766854,0.00021918464,0.0017027728,0.0007531396,0.0008331922,0.0016996452],"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":[0.0003829646,0.0006693964,0.12074343,0.00024080054,0.00004446048,0.00027514057,0.0013890966,0.048286684,0.00516874,0.00989476,0.01954452,0.79336],"study_design_scores_gemma":[0.00012957111,0.0005872806,0.1362386,0.0003024211,0.00012790083,0.0005011772,0.004275949,0.75104827,0.018960569,0.037747554,0.049911417,0.00016936465],"about_ca_topic_score_codex":0.009540465,"about_ca_topic_score_gemma":0.024142433,"teacher_disagreement_score":0.009540465,"about_ca_system_score_codex":0.0010008152,"about_ca_system_score_gemma":0.003325112,"threshold_uncertainty_score":0.018969893},"labels":[],"label_agreement":null},{"id":"W1967734595","doi":"10.1007/s10799-012-0144-7","title":"Effects of strategic alignment on IS success: the mediation role of IS investment in Korea","year":2012,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Information Technology Governance and Strategy","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mediation; Antecedent (behavioral psychology); Scope (computer science); Investment (military); Business; Contingency; Contingency theory; Industrial organization; Organizational structure; Marketing; Management; Economics; Psychology; Political science","score_opus":0.005951828057985189,"score_gpt":0.1956057386655586,"score_spread":0.18965391060757342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967734595","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":[0.9987375,0.000018771625,0.000025156032,0.00009986745,0.000002120538,0.00000278919,0.000018062825,0.0000017129314,0.0010939941],"genre_scores_gemma":[0.9997762,0.000014220438,0.0000144379455,0.000008464068,6.434424e-7,0.0000015207835,0.000020584552,8.7341914e-7,0.00016316686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920386,0.00026543852,0.000043576023,0.000091276954,0.000062149025,0.0003336417],"domain_scores_gemma":[0.9947179,0.0013286577,0.0018367625,0.00022558687,0.00043821082,0.0014529808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083571795,0.00047409377,0.00033993917,0.00056796306,0.0008593157,0.002138945,0.0005640067,0.0005578455,0.006335388],"category_scores_gemma":[0.0031803572,0.00034371015,0.00041955648,0.000971903,0.0008804267,0.0017388304,0.0017900545,0.0013082387,0.0003669621],"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":[0.0017563448,0.0016672383,0.975225,0.000060432852,0.00032159974,0.0009771878,0.0023955181,0.001835102,0.0025366924,0.0046569565,0.00073808443,0.007829817],"study_design_scores_gemma":[0.000072525494,0.0004039315,0.98444587,0.000031655112,0.00024526357,0.000088015775,0.009561771,0.00293242,0.0006509762,0.0009851477,0.0005544744,0.000028002434],"about_ca_topic_score_codex":0.016922574,"about_ca_topic_score_gemma":0.028404485,"teacher_disagreement_score":0.016922574,"about_ca_system_score_codex":0.0015941405,"about_ca_system_score_gemma":0.0033395423,"threshold_uncertainty_score":0.033648133},"labels":[],"label_agreement":null},{"id":"W1972796952","doi":"10.1007/s10799-007-0023-9","title":"Towards an evaluation framework for knowledge management systems","year":2007,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Benchmark (surveying); Knowledge management; Key (lock); Computer science; Portfolio; Process management; Engineering; Business","score_opus":0.03386290162140471,"score_gpt":0.3498349680288944,"score_spread":0.3159720664074897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972796952","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":[0.016820377,0.0009709615,0.9262124,0.0073047895,0.0001571632,0.0028427837,0.00026105676,0.0005605297,0.044870015],"genre_scores_gemma":[0.30859485,0.0003797652,0.68321383,0.00044128086,0.000090224115,0.003453056,0.00035290772,0.0001514864,0.0033226362],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.8626403,0.09181547,0.008927556,0.0035528129,0.030496137,0.0025675779],"domain_scores_gemma":[0.8387034,0.09083086,0.007997828,0.0078669125,0.051073045,0.0035280683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.12527807,0.0016753761,0.0022284205,0.010198301,0.0036699155,0.01822234,0.003920644,0.004336568,0.0064534564],"category_scores_gemma":[0.16614732,0.00080335943,0.0014640362,0.005646102,0.0084521985,0.019305287,0.00699096,0.0034557185,0.0010939367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018910957,0.00041036904,0.002847427,0.00092926977,0.00013005643,0.00008143009,0.0028117278,0.010297308,0.0012714895,0.86864454,0.004437981,0.10794934],"study_design_scores_gemma":[0.00019155841,0.0005524261,0.0032421935,0.0014912055,0.00022768481,0.0001411044,0.0056887646,0.12528476,0.0039478196,0.8316743,0.027426867,0.00013136244],"about_ca_topic_score_codex":0.010039484,"about_ca_topic_score_gemma":0.007847824,"teacher_disagreement_score":0.12527807,"about_ca_system_score_codex":0.013421902,"about_ca_system_score_gemma":0.015781509,"threshold_uncertainty_score":0.6625417},"labels":[],"label_agreement":null},{"id":"W1979586968","doi":"10.1007/s10799-009-0054-5","title":"The strategic knowledge-based dependency diagrams: a tool for analyzing strategic knowledge dependencies for the purposes of understanding and communicating","year":2009,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Knowledge management; Conceptualization; Dependency (UML); Resource (disambiguation); Organizational learning; Computer science; Knowledge value chain; Domain knowledge; Process (computing); Appropriation; Artificial intelligence; Epistemology","score_opus":0.05108975860642415,"score_gpt":0.27024720779188366,"score_spread":0.2191574491854595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979586968","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":[0.007239901,0.00019471569,0.97723025,0.00030720906,0.000055055283,0.00029200586,0.0034915863,0.0050083753,0.006180933],"genre_scores_gemma":[0.124574155,0.0006775555,0.8626995,0.00016570721,0.000039885388,0.00048154456,0.0069032996,0.0008738014,0.0035845179],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99774796,0.0007127268,0.0002790048,0.0002567309,0.0008770975,0.00012651939],"domain_scores_gemma":[0.99113023,0.0056606154,0.0007748212,0.0010463834,0.001136004,0.0002519267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030303146,0.0014987792,0.0006964165,0.007340206,0.0015119014,0.0034057912,0.0014181716,0.0013493232,0.00806119],"category_scores_gemma":[0.015506616,0.0011043572,0.0015467877,0.0051491167,0.00079669687,0.006633027,0.0019631977,0.0017706824,0.001645755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003425704,0.00028405242,0.010163538,0.0014827494,0.00030151944,0.0012599066,0.0050164233,0.05439722,0.008825637,0.4764114,0.026720501,0.41479447],"study_design_scores_gemma":[0.00011670554,0.00016132573,0.0040970743,0.000697214,0.0004321708,0.0016106485,0.0010614377,0.40994433,0.020511542,0.30736727,0.25378564,0.00021463202],"about_ca_topic_score_codex":0.010698864,"about_ca_topic_score_gemma":0.012780293,"teacher_disagreement_score":0.010698864,"about_ca_system_score_codex":0.0012011062,"about_ca_system_score_gemma":0.005178315,"threshold_uncertainty_score":0.026967406},"labels":[],"label_agreement":null},{"id":"W2015738394","doi":"10.1007/s10799-012-0135-8","title":"A comparative analysis of classification algorithms in data mining for accuracy, speed and robustness","year":2012,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Computer science; Robustness (evolution); Data mining; Classifier (UML); Scalability; Principal component analysis; Machine learning; Artificial intelligence; Statistical classification; Execution time; Pattern recognition (psychology); Database","score_opus":0.06475445140591805,"score_gpt":0.3373495764834195,"score_spread":0.27259512507750144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015738394","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":[0.19737893,0.04744679,0.73547405,0.0038030606,0.0007389157,0.0004097198,0.000731896,0.0022934165,0.011723282],"genre_scores_gemma":[0.6519525,0.007841448,0.33515033,0.0005226436,0.00067994784,0.00022816086,0.00095519976,0.00051575276,0.0021539559],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9775138,0.010735298,0.0020487064,0.0016415978,0.0074503417,0.0006101879],"domain_scores_gemma":[0.67654705,0.29408163,0.004241696,0.008532355,0.015989486,0.0006079215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.034753487,0.0012884609,0.0023155326,0.010231493,0.0011697821,0.0048336056,0.0023382795,0.0027308722,0.0019343625],"category_scores_gemma":[0.13877493,0.00068666076,0.0027048434,0.008621292,0.0016111465,0.0075959093,0.0012918107,0.0019776556,0.0006301924],"study_design_candidate":"bench_or_experimental","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":[0.0033627667,0.00042162096,0.030513955,0.0010662627,0.0013906951,0.00016280805,0.00049111666,0.14744876,0.0037871485,0.035079252,0.004572412,0.7717032],"study_design_scores_gemma":[0.00016663446,0.000857389,0.016669918,0.00026602295,0.0007007789,0.0005038427,0.00029170577,0.94325,0.006807321,0.026851052,0.003521549,0.000113787944],"about_ca_topic_score_codex":0.0035798908,"about_ca_topic_score_gemma":0.0019215142,"teacher_disagreement_score":0.034753487,"about_ca_system_score_codex":0.002934617,"about_ca_system_score_gemma":0.0016893286,"threshold_uncertainty_score":0.18379623},"labels":[],"label_agreement":null},{"id":"W2022334480","doi":"10.1023/b:item.0000008081.55563.d4","title":"Understanding Customer Trust in Agent-Mediated Electronic Commerce, Web-Mediated Electronic Commerce, and Traditional Commerce","year":2003,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":349,"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; Memorial University of Newfoundland","funders":"","keywords":"Computational trust; E-commerce; Meaning (existential); Cognition; Context (archaeology); Business; Customer intelligence; Customer to customer; Customer advocacy; Computer science; Knowledge management; Customer retention; Marketing; Psychology; World Wide Web; Reputation; Service (business); Service quality","score_opus":0.08185303778642673,"score_gpt":0.30129929249898224,"score_spread":0.21944625471255552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022334480","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":[0.9688468,0.0016693864,0.007616486,0.0029066885,0.000017286298,0.00002247099,0.0000120102595,0.0000062519416,0.018902574],"genre_scores_gemma":[0.99937785,0.00012712153,0.00025852953,0.000026433789,0.0000055518567,0.0000037343357,0.0000030753506,7.9306545e-7,0.0001968645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.997787,0.0014511953,0.00008549724,0.00010332635,0.00031030958,0.00026256486],"domain_scores_gemma":[0.98473257,0.0108108325,0.0021903652,0.00045567294,0.0012156778,0.00059483916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033671567,0.00022993665,0.0003575132,0.0010517646,0.0011194887,0.0045656674,0.000610122,0.00201083,0.001580049],"category_scores_gemma":[0.015748288,0.00037469828,0.00029690046,0.0009246961,0.0028750026,0.0068950527,0.0013741141,0.0014049361,0.00011424226],"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":[0.0010312743,0.0015588226,0.34723035,0.0004663959,0.00041666892,0.0014672028,0.08875992,0.011483982,0.0018771098,0.4415479,0.0018086927,0.1023517],"study_design_scores_gemma":[0.0001639912,0.000534209,0.31438828,0.00034427078,0.00043566868,0.0012931837,0.06476738,0.12299427,0.0014182607,0.48370078,0.00982006,0.00013953428],"about_ca_topic_score_codex":0.010305479,"about_ca_topic_score_gemma":0.011770995,"teacher_disagreement_score":0.010305479,"about_ca_system_score_codex":0.002460246,"about_ca_system_score_gemma":0.0013934532,"threshold_uncertainty_score":0.020490944},"labels":[],"label_agreement":null},{"id":"W2032444218","doi":"10.1007/s10799-007-0017-7","title":"Extracting knowledge from XML document repository: a semantic Web-based approach","year":2007,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":5,"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":"Computer science; Semantic Web Stack; Semantic Web Rule Language; Social Semantic Web; Information retrieval; World Wide Web; OWL-S; Semantic analytics; Semantic Web; Data Web; Web page","score_opus":0.007772851444681323,"score_gpt":0.23035529675903368,"score_spread":0.22258244531435237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032444218","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":[0.03634636,0.0019616322,0.94412285,0.0010214724,0.00014001428,0.0007540448,0.0039016232,0.0054643815,0.006287654],"genre_scores_gemma":[0.13753691,0.0025593247,0.84300774,0.00019729389,0.00008268324,0.00030603877,0.013441027,0.00028083508,0.0025882267],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774265,0.00029721594,0.0004178474,0.0003682094,0.0010253134,0.00014879256],"domain_scores_gemma":[0.99744534,0.0009603902,0.00023097002,0.00053165806,0.0007365934,0.00009507156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016184039,0.0009829024,0.0018087272,0.014347574,0.0014297869,0.004349705,0.0023545744,0.0018968432,0.0021319096],"category_scores_gemma":[0.006036883,0.0006947704,0.0023197709,0.012761434,0.0008390633,0.006107601,0.0021166326,0.0013431133,0.0018394705],"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":[0.00031941294,0.0006743306,0.0071261358,0.0014311613,0.00033827935,0.0026554982,0.0012181014,0.008266296,0.023408387,0.019309595,0.010104151,0.92514855],"study_design_scores_gemma":[0.000258019,0.00047791007,0.019247662,0.0019285083,0.0027426365,0.009094484,0.0060751163,0.4641144,0.17421725,0.14300708,0.17832641,0.00051056105],"about_ca_topic_score_codex":0.005358671,"about_ca_topic_score_gemma":0.0057589794,"teacher_disagreement_score":0.014347574,"about_ca_system_score_codex":0.00093112123,"about_ca_system_score_gemma":0.0027454763,"threshold_uncertainty_score":0.010654926},"labels":[],"label_agreement":null},{"id":"W2034453623","doi":"10.1007/s10799-012-0118-9","title":"Impact of an ERP system’s capabilities upon the realisation of its business value: a resource-based perspective","year":2012,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Enterprise resource planning; Process management; Knowledge management; Resource-based view; Flexibility (engineering); Resource (disambiguation); Dynamic capabilities; Manufacturing resource planning; Business; Value (mathematics); Transformational leadership; Realisation; Empirical research; Perspective (graphical); Frame (networking); Business process; Computer science; Marketing; Competitive advantage; Management","score_opus":0.014130273311616622,"score_gpt":0.26773280053000276,"score_spread":0.2536025272183861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034453623","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":[0.5542853,0.0023127343,0.015204544,0.008055278,0.0001275619,0.000093248345,0.0003167616,0.000058810547,0.41954568],"genre_scores_gemma":[0.9962059,0.0006340176,0.0010921492,0.00008918679,0.000046333746,0.000014149725,0.00004250842,0.00001395011,0.0018618549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9950878,0.0020164445,0.00021874784,0.00027223505,0.0015246584,0.00088013243],"domain_scores_gemma":[0.9688298,0.022737838,0.0026429116,0.0012497649,0.0031368476,0.001402808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00603545,0.00076381146,0.0004194761,0.0037378448,0.0011921665,0.009619564,0.0013560312,0.001995152,0.010679435],"category_scores_gemma":[0.01850986,0.0005364384,0.0008081075,0.0036661199,0.006282768,0.011934056,0.003323974,0.0028061408,0.00060947455],"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":[0.0011510645,0.0010624737,0.035212245,0.00062181405,0.00032634416,0.0015026283,0.0026788446,0.040819213,0.006900298,0.8205251,0.0019477265,0.08725225],"study_design_scores_gemma":[0.00018769543,0.0020541493,0.19791798,0.0008420329,0.0006185358,0.0013840982,0.01540149,0.053379416,0.021633023,0.6585012,0.04772414,0.0003562306],"about_ca_topic_score_codex":0.0047924984,"about_ca_topic_score_gemma":0.002971003,"teacher_disagreement_score":0.010679435,"about_ca_system_score_codex":0.0037118664,"about_ca_system_score_gemma":0.002720376,"threshold_uncertainty_score":0.03572625},"labels":[],"label_agreement":null},{"id":"W2042058252","doi":"10.1007/s10799-007-0032-8","title":"Exploring new patterns and mechanisms for advanced information technology and systems in the internet-era: introduction to the WITS’05 special issue","year":2007,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Big Data and Business Intelligence","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":"The Internet; Computer science; Data science; World Wide Web","score_opus":0.02965532129854699,"score_gpt":0.2445055689422681,"score_spread":0.21485024764372113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042058252","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050916962,0.08230294,0.54811424,0.11555018,0.0038482756,0.00019971807,0.0008526694,0.0005250872,0.19768995],"genre_scores_gemma":[0.55595165,0.06178461,0.3076948,0.006012967,0.006456837,0.00042080265,0.00096576737,0.0006416003,0.06007099],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990075,0.00032429447,0.00010639175,0.00022688597,0.00024210321,0.000092814415],"domain_scores_gemma":[0.9969285,0.0016826841,0.00028369308,0.000581545,0.00037452846,0.0001491153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020463462,0.0006485114,0.000823529,0.0031735061,0.0020233209,0.011675335,0.0016682746,0.0025582304,0.010425725],"category_scores_gemma":[0.004961419,0.00081997784,0.0013662298,0.007235945,0.012404393,0.03536606,0.003624221,0.0048024403,0.0011481335],"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":[0.0000037098857,0.000011093581,0.00054616993,0.000049721206,0.0000074125046,0.000035388115,0.0005659728,0.00019963333,0.00011188124,0.980974,0.00318961,0.014305423],"study_design_scores_gemma":[0.000002771453,0.0000056179783,0.0006164158,0.00006408158,0.000005653257,0.00011765743,0.00058062683,0.0013798978,0.00012552715,0.9512592,0.045829747,0.000012738329],"about_ca_topic_score_codex":0.0024823546,"about_ca_topic_score_gemma":0.00385872,"teacher_disagreement_score":0.011675335,"about_ca_system_score_codex":0.0025981215,"about_ca_system_score_gemma":0.0014519776,"threshold_uncertainty_score":0.03487748},"labels":[],"label_agreement":null},{"id":"W2043030433","doi":"10.1007/s10799-004-7776-1","title":"Exploiting the Small-Worlds of the Semantic Web to Connect Heterogeneous, Local Ontologies","year":2005,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":11,"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":"Computer science; World Wide Web; Hyperlink; Semantic Web; Ontology components; Ontology; Information retrieval; Semantics (computer science); Linked data; Semantic Web Stack; OWL-S; Web page; Programming language","score_opus":0.010404408290451063,"score_gpt":0.2151533254978153,"score_spread":0.20474891720736424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043030433","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":[0.017385809,0.00060970325,0.95368147,0.0016574946,0.00014746752,0.00013416995,0.00010212087,0.0007682959,0.02551358],"genre_scores_gemma":[0.4296798,0.0015987699,0.5583237,0.00062292744,0.000194167,0.00031517108,0.00059989555,0.00051593344,0.008149695],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965522,0.0019596373,0.00019592764,0.00042867791,0.00069115736,0.00017236143],"domain_scores_gemma":[0.9908212,0.005164485,0.0004517523,0.0025916963,0.0005039656,0.00046687276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004625552,0.0006986058,0.0007121734,0.003041102,0.002678954,0.010036376,0.0017577711,0.0018963062,0.0055401805],"category_scores_gemma":[0.018417554,0.0009945324,0.0013710721,0.0033998357,0.0063979737,0.02721254,0.012906936,0.0036795838,0.0014234018],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073496165,0.00008254181,0.0009247313,0.00013403584,0.0000761771,0.00041847394,0.002843759,0.0060052625,0.0030683684,0.93382233,0.0030746034,0.049476348],"study_design_scores_gemma":[0.000022995324,0.000021871658,0.00022039172,0.00007750043,0.000053679854,0.00019302803,0.00095724675,0.048816454,0.0024740559,0.9054941,0.04163907,0.00002955312],"about_ca_topic_score_codex":0.0032389883,"about_ca_topic_score_gemma":0.004606162,"teacher_disagreement_score":0.010036376,"about_ca_system_score_codex":0.00094289845,"about_ca_system_score_gemma":0.0016901329,"threshold_uncertainty_score":0.02446258},"labels":[],"label_agreement":null},{"id":"W2081805004","doi":"10.1007/s10799-008-0039-9","title":"Relative importance, specific investment and ownership in interorganizational systems","year":2008,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University","funders":"","keywords":"Transaction cost; Investment (military); Industrial organization; Microeconomics; Business; Vendor; Database transaction; Core (optical fiber); Value (mathematics); Relative value; Economics; Finance; Marketing; Computer science; Database","score_opus":0.04043453590908521,"score_gpt":0.27717415913957655,"score_spread":0.23673962323049133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081805004","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":[0.9864659,0.00031276114,0.008369503,0.0002028833,0.0000049565792,0.000009065601,0.000017890314,0.000005380116,0.004611613],"genre_scores_gemma":[0.9991916,0.00005993933,0.0004122119,0.0000051897046,0.000004025347,0.000002780316,0.000008347915,9.543511e-7,0.00031488467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986369,0.0006140286,0.00010662964,0.00014689399,0.0003041045,0.00019149546],"domain_scores_gemma":[0.9750108,0.018208666,0.0035731713,0.0013299144,0.0010166657,0.0008607796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031980583,0.00018796099,0.00043528792,0.0011128283,0.00047019,0.0022917772,0.00051373534,0.00078783033,0.0020682092],"category_scores_gemma":[0.025603503,0.00027048742,0.00022965073,0.0012814831,0.001980891,0.004446505,0.0011234537,0.00061369495,0.000102193386],"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":[0.0008734671,0.00028151734,0.37060684,0.0003834586,0.0003406074,0.00055008533,0.0024715317,0.09500543,0.008761713,0.43829498,0.0006460739,0.08178436],"study_design_scores_gemma":[0.00006836218,0.00042639012,0.36046,0.000067529014,0.00026933948,0.00083694176,0.003334884,0.1223105,0.0028735162,0.50706726,0.0022391155,0.000046174937],"about_ca_topic_score_codex":0.0008829647,"about_ca_topic_score_gemma":0.0019138275,"teacher_disagreement_score":0.0031980583,"about_ca_system_score_codex":0.0012937684,"about_ca_system_score_gemma":0.0004673706,"threshold_uncertainty_score":0.016913176},"labels":[],"label_agreement":null},{"id":"W2088500621","doi":"10.1007/s10799-006-5728-7","title":"Evaluating strategic options using decision-theoretic planning","year":2006,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Heuristics; Product (mathematics); Computer science; Management science; Value (mathematics); Operations research; Risk analysis (engineering); Decision analysis; Strategic planning; Business; Economics; Marketing; Engineering; Mathematics","score_opus":0.046316708808654475,"score_gpt":0.2819348666566401,"score_spread":0.23561815784798562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088500621","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":[0.21983865,0.0015693477,0.7576711,0.0016275583,0.0001037928,0.00040887296,0.0003222481,0.00024849756,0.018209852],"genre_scores_gemma":[0.9005082,0.0007683661,0.09657028,0.00006646633,0.000046844398,0.00023449044,0.00014634541,0.000032176285,0.0016268326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973767,0.0017712835,0.0001082518,0.0001850689,0.00037703142,0.00018173097],"domain_scores_gemma":[0.9824232,0.01588526,0.0005944895,0.00026646053,0.00043898707,0.0003917172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005503629,0.0016522863,0.0017840425,0.0026104653,0.0006230803,0.0038357035,0.0011257404,0.0022658836,0.0038847087],"category_scores_gemma":[0.019840376,0.0013496039,0.0013132247,0.0017949083,0.0018885398,0.0040332363,0.0013003071,0.0015294214,0.00021968762],"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":[0.00008120119,0.00004986399,0.00065400713,0.000047635487,0.000059892165,0.000051085877,0.000033166154,0.957992,0.00011982472,0.033084366,0.00020242832,0.0076245363],"study_design_scores_gemma":[0.000015791478,0.000038111015,0.00008617379,0.0000107402275,0.000020884569,0.000006660375,0.000024389305,0.9600062,0.0001255361,0.03951686,0.00013961825,0.000008955287],"about_ca_topic_score_codex":0.0068694525,"about_ca_topic_score_gemma":0.006998094,"teacher_disagreement_score":0.0068694525,"about_ca_system_score_codex":0.0032884174,"about_ca_system_score_gemma":0.0036557296,"threshold_uncertainty_score":0.029106319},"labels":[],"label_agreement":null},{"id":"W2094386140","doi":"10.1007/s10799-010-0067-0","title":"IT, productivity and organizational practices: large sample, establishment-level evidence","year":2010,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; University of Waterloo","funders":"","keywords":"Productivity; Compensation (psychology); Sample (material); Investment (military); Implementation; Business; Psychology; Marketing; Economics; Social psychology; Engineering; Political science; Economic growth","score_opus":0.07998567115581937,"score_gpt":0.362666920269359,"score_spread":0.28268124911353965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094386140","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":[0.99576616,0.0024631147,0.00035002676,0.00012103785,0.000014621388,0.00003369489,0.0002945499,0.000006852508,0.0009500247],"genre_scores_gemma":[0.9980609,0.00082658144,0.00031675346,0.00013115058,0.000031323474,0.000033995377,0.00037660435,0.0000059202853,0.00021676857],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99119335,0.0045685438,0.0008168225,0.0010423211,0.0018422692,0.0005367412],"domain_scores_gemma":[0.8223226,0.13485898,0.022596154,0.009886224,0.006428848,0.003907267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012675377,0.0005167592,0.0011319601,0.0025639615,0.001516771,0.0020215905,0.0013661465,0.0012402047,0.0042799353],"category_scores_gemma":[0.044227064,0.0008489386,0.0013297917,0.0039066747,0.0026161615,0.0016199057,0.0017822634,0.0013591497,0.0006641342],"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":[0.00063040026,0.0007370802,0.9889262,0.0002557748,0.0013602525,0.000093280076,0.0007597968,0.000056308734,0.00028925372,0.00009490258,0.000191722,0.006605055],"study_design_scores_gemma":[0.00007127818,0.00051528844,0.99738306,0.00006636478,0.0006132635,0.000091443675,0.00077054725,0.000057529705,0.00012228024,0.00005619821,0.00024169155,0.000011013054],"about_ca_topic_score_codex":0.015067496,"about_ca_topic_score_gemma":0.033828583,"teacher_disagreement_score":0.015067496,"about_ca_system_score_codex":0.0009367794,"about_ca_system_score_gemma":0.0016690253,"threshold_uncertainty_score":0.0670346},"labels":[],"label_agreement":null},{"id":"W2622764968","doi":"10.1007/s10799-017-0276-x","title":"IT capabilities for product innovation in SMEs: a configurational approach","year":2017,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Equifinality; Contingency; Product (mathematics); Product innovation; Business; New product development; Industrial organization; Resource (disambiguation); Contingency theory; Dynamic capabilities; Competitive advantage; Innovation management; Globalization; Knowledge management; Computer science; Marketing; Economics; Mathematics","score_opus":0.019884831014865448,"score_gpt":0.24609462739080745,"score_spread":0.22620979637594202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622764968","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":[0.53335977,0.0017215131,0.09818639,0.006162798,0.0000917956,0.0001837216,0.00027927876,0.00017703128,0.3598378],"genre_scores_gemma":[0.9965635,0.00015328823,0.0025582735,0.000030452069,0.000016907623,0.0000254423,0.000021020616,0.000008649391,0.00062249636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9976156,0.0012215505,0.00014380699,0.00022001365,0.0003922639,0.0004069081],"domain_scores_gemma":[0.98876065,0.0074241525,0.0012003998,0.0007418293,0.0009692307,0.0009037153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022944326,0.00091431267,0.00051664346,0.006073937,0.0017999953,0.008995128,0.0020536985,0.0022152364,0.011768657],"category_scores_gemma":[0.01129713,0.0007961645,0.0012703496,0.0048575373,0.0065206173,0.014499723,0.0051537473,0.0015779608,0.0005778141],"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":[0.0001581977,0.00022434519,0.016485246,0.00024360338,0.0001483431,0.0010984936,0.0026353665,0.0450185,0.0012408422,0.8996762,0.0006925535,0.032378413],"study_design_scores_gemma":[0.000036963655,0.00023606628,0.016302412,0.0003507892,0.00013499858,0.0007098748,0.008807615,0.089101814,0.0011205728,0.87968254,0.0034211413,0.00009529375],"about_ca_topic_score_codex":0.0034314003,"about_ca_topic_score_gemma":0.003635296,"teacher_disagreement_score":0.011768657,"about_ca_system_score_codex":0.00404269,"about_ca_system_score_gemma":0.002843337,"threshold_uncertainty_score":0.03937012},"labels":[],"label_agreement":null},{"id":"W4281634305","doi":"10.1007/s10799-022-00367-7","title":"Retailer response to negative online consumer reviews: how can damaged trust be effectively repaired?","year":2022,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Natural Science Foundation of China","keywords":"Reputation; Perception; Service quality; Competence (human resources); Affect (linguistics); Business; Marketing; Quality (philosophy); Service (business); Compensation (psychology); Psychology; Social psychology","score_opus":0.015118441158936381,"score_gpt":0.27077035816248624,"score_spread":0.25565191700354983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281634305","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":[0.7563486,0.005893724,0.016659357,0.13292633,0.0021590784,0.00027026274,0.0002566322,0.0009413344,0.08454466],"genre_scores_gemma":[0.98708504,0.0009615858,0.0032452503,0.0032694712,0.00025146213,0.000040253934,0.000055939418,0.000051085975,0.005039921],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99374676,0.0037957265,0.00025579185,0.00037887174,0.0012394835,0.00058339373],"domain_scores_gemma":[0.96317863,0.014819061,0.0066656754,0.00420052,0.00821144,0.0029246728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009073857,0.00028041782,0.0005390191,0.00054407347,0.0012960827,0.0044848262,0.0012355031,0.002838891,0.0073795156],"category_scores_gemma":[0.0655652,0.00030533204,0.0003927742,0.00039229056,0.001479749,0.0054005263,0.0016910738,0.0018366571,0.0026758702],"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":[0.0023908138,0.0023956099,0.11569191,0.0011966672,0.00040160853,0.0014091273,0.015677387,0.002204121,0.008979508,0.018462183,0.076830424,0.7543606],"study_design_scores_gemma":[0.0007576207,0.0051096673,0.3305304,0.0035900788,0.0015234776,0.00531198,0.1130375,0.058151532,0.023576152,0.15077327,0.30692524,0.00071298174],"about_ca_topic_score_codex":0.004965601,"about_ca_topic_score_gemma":0.0072543425,"teacher_disagreement_score":0.009073857,"about_ca_system_score_codex":0.0014283593,"about_ca_system_score_gemma":0.0030379721,"threshold_uncertainty_score":0.0479877},"labels":[],"label_agreement":null},{"id":"W4318769934","doi":"10.1007/s10799-023-00388-w","title":"The state of lead scoring models and their impact on sales performance","year":2023,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Mitacs","keywords":"Lead (geology); Computer science; Lead time; Predictive modelling; Process (computing); Machine learning; Quality (philosophy); Artificial intelligence; Risk analysis (engineering); Data mining; Operations management; Engineering; Business","score_opus":0.01519373876254896,"score_gpt":0.22883282602854743,"score_spread":0.21363908726599848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318769934","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":[0.8323965,0.012866854,0.12187927,0.006408895,0.0004519583,0.00007963412,0.0010545938,0.0018351603,0.02302704],"genre_scores_gemma":[0.98589724,0.0011649262,0.010079769,0.00013543045,0.00012867352,0.000016663373,0.0003650038,0.00012130152,0.002091056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.98456687,0.009771191,0.0005837839,0.001285102,0.0030373868,0.0007556581],"domain_scores_gemma":[0.820198,0.14529447,0.006881334,0.008241142,0.017326254,0.002058787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027642664,0.0009637273,0.0009947418,0.002927006,0.001279979,0.008679735,0.0018645223,0.0021858083,0.0035040728],"category_scores_gemma":[0.116512276,0.00066455745,0.00074400374,0.004096743,0.0016958211,0.003993177,0.0011897846,0.0027355875,0.0011446615],"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":[0.0019007844,0.000868752,0.09473865,0.00020304232,0.00025131978,0.000046369023,0.00040071778,0.49063113,0.0009114095,0.030596104,0.0066730655,0.37277862],"study_design_scores_gemma":[0.00005938848,0.00045185757,0.011247427,0.000119138225,0.0001151727,0.00005425622,0.00024526208,0.96887815,0.0018962692,0.014930377,0.0019299244,0.00007282892],"about_ca_topic_score_codex":0.011935209,"about_ca_topic_score_gemma":0.014928064,"teacher_disagreement_score":0.027642664,"about_ca_system_score_codex":0.0038431135,"about_ca_system_score_gemma":0.0028564648,"threshold_uncertainty_score":0.14619017},"labels":[],"label_agreement":null},{"id":"W4377096817","doi":"10.1007/s10799-023-00400-3","title":"Knowledge transfer between physicians from different geographical regions in China’s online health communities","year":2023,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Natural Science Foundation of China","keywords":"Tacit knowledge; Knowledge management; Exponential random graph models; Medical knowledge; Knowledge transfer; Explicit knowledge; Business; Quality (philosophy); Medical education; Computer science; Medicine; Graph","score_opus":0.031320171828396984,"score_gpt":0.3060264564318352,"score_spread":0.2747062846034382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377096817","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":[0.99780434,0.000116176394,0.00006907739,0.0004173855,0.000005503998,0.000012957886,0.00002802306,0.0000028573106,0.0015436993],"genre_scores_gemma":[0.99946326,0.000044789642,0.00005359371,0.00007428555,0.000004395549,0.0000059855047,0.000022205873,6.821292e-7,0.00033088628],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978957,0.0008792169,0.00012293912,0.00025129234,0.0003160569,0.0005347596],"domain_scores_gemma":[0.9904308,0.004708232,0.0014836192,0.00035122386,0.0010509214,0.0019752337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002097066,0.00012760541,0.0002352439,0.0016543304,0.0019507637,0.0015761924,0.00062719494,0.0006726483,0.0038505283],"category_scores_gemma":[0.012173655,0.00012142326,0.00026849104,0.0015296763,0.0008679595,0.0018321605,0.002489229,0.0004338701,0.00018286443],"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":[0.00037065483,0.0005354297,0.87119275,0.00015435874,0.00011583439,0.0011301256,0.06127651,0.00046307824,0.0006107505,0.0016109388,0.0020482012,0.060491387],"study_design_scores_gemma":[0.00006262429,0.00021244098,0.8994392,0.00016917818,0.00016287171,0.0003815301,0.08958923,0.004229608,0.0004015842,0.0014456073,0.003869775,0.00003647193],"about_ca_topic_score_codex":0.049681436,"about_ca_topic_score_gemma":0.062063735,"teacher_disagreement_score":0.049681436,"about_ca_system_score_codex":0.0023514982,"about_ca_system_score_gemma":0.005687762,"threshold_uncertainty_score":0.09878451},"labels":[],"label_agreement":null},{"id":"W4388269570","doi":"10.1007/s10799-023-00413-y","title":"Trading volume and open interest from options markets as measures of the effect of IT announcements","year":2023,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Algorithmic trading; Stock market; Business; Stock (firearms); Financial economics; Alternative trading system; Investment decisions; Monetary economics; Economics; Behavioral economics; Finance","score_opus":0.0291429702970446,"score_gpt":0.23331897518680483,"score_spread":0.20417600488976023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388269570","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":[0.9943597,0.00032238485,0.0015956354,0.00016031161,0.000021833224,0.000011794091,0.000473496,0.000037462494,0.0030173385],"genre_scores_gemma":[0.9984707,0.0001226391,0.00027826935,0.000019169005,0.000056219164,0.000006716791,0.0005006805,0.00001060083,0.0005350264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989945,0.0003611411,0.00008570887,0.0000923126,0.0003901524,0.00007614618],"domain_scores_gemma":[0.9329601,0.05217238,0.011012346,0.001209387,0.0011865922,0.0014592139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027552578,0.00038643015,0.00043504316,0.0016275018,0.00018670902,0.0021997928,0.0005196044,0.0010313179,0.0027625074],"category_scores_gemma":[0.033099286,0.00021731202,0.00040174407,0.0014780436,0.00055249024,0.0025339855,0.0006272114,0.0014999985,0.000374318],"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":[0.0071877963,0.0013638493,0.8230891,0.00035342644,0.0010262016,0.00089290814,0.0012056783,0.063248225,0.022064868,0.020130984,0.0020303985,0.05740648],"study_design_scores_gemma":[0.0001229924,0.0008717456,0.8210755,0.000038593837,0.00035042386,0.00043293284,0.00041940645,0.15026468,0.0073648742,0.017473498,0.0014667076,0.00011855596],"about_ca_topic_score_codex":0.0008661357,"about_ca_topic_score_gemma":0.0010370081,"teacher_disagreement_score":0.0027625074,"about_ca_system_score_codex":0.00039058842,"about_ca_system_score_gemma":0.00017777989,"threshold_uncertainty_score":0.014571369},"labels":[],"label_agreement":null},{"id":"W4402266749","doi":"10.1007/s10799-024-00439-w","title":"A unified framework for financial commentary prediction","year":2024,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science","score_opus":0.04150349653960948,"score_gpt":0.36093625238864996,"score_spread":0.31943275584904046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402266749","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":[0.0020306506,0.0002721708,0.98794067,0.0014114428,0.0001072834,0.00010582338,0.00045800663,0.00046826093,0.007205735],"genre_scores_gemma":[0.16163984,0.00082915014,0.82640666,0.00045511257,0.00048755988,0.0005809876,0.0015502003,0.00019871251,0.007851678],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955929,0.0017410876,0.00042486622,0.000704325,0.001204889,0.0003319041],"domain_scores_gemma":[0.98846215,0.006376074,0.0006518563,0.0013028295,0.0028214613,0.0003855899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076038465,0.0009269031,0.0014753719,0.0048643304,0.001842199,0.0077818544,0.0034369424,0.0025475067,0.013041231],"category_scores_gemma":[0.02703709,0.0007240853,0.0020590345,0.0039331014,0.0022029937,0.007827501,0.0036033532,0.002408506,0.0032097525],"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":[0.000035016626,0.00010855857,0.0013592287,0.00007682525,0.000081017664,0.0001051641,0.00026076715,0.051281765,0.0002957763,0.8592451,0.008962607,0.07818812],"study_design_scores_gemma":[0.000015963455,0.000018612014,0.000253537,0.0000635757,0.000028546874,0.000038523416,0.00009747163,0.46485296,0.00023424033,0.52649856,0.007871138,0.00002685042],"about_ca_topic_score_codex":0.01631279,"about_ca_topic_score_gemma":0.0153302485,"teacher_disagreement_score":0.01631279,"about_ca_system_score_codex":0.002104289,"about_ca_system_score_gemma":0.005535553,"threshold_uncertainty_score":0.043627262},"labels":[],"label_agreement":null},{"id":"W4410772565","doi":"10.1007/s10799-025-00455-4","title":"Time series clustering for grouping products based on price and sales patterns","year":2025,"lang":"en","type":"article","venue":"Information Technology and Management","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Series (stratigraphy); Cluster analysis; Computer science; Econometrics; Mathematics; Artificial intelligence; Geology","score_opus":0.004913521361158834,"score_gpt":0.19577075570331254,"score_spread":0.1908572343421537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410772565","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":[0.10997107,0.0006961908,0.8753999,0.0003085924,0.00023026721,0.0004879264,0.004182778,0.005390975,0.0033322212],"genre_scores_gemma":[0.30378145,0.00045240618,0.67631876,0.00009471362,0.00019717135,0.0005052123,0.011942221,0.00041153573,0.006296569],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991817,0.000117270334,0.000090745496,0.00026229722,0.0002472201,0.00010067004],"domain_scores_gemma":[0.9987552,0.00030601505,0.00013968433,0.00022298003,0.000483969,0.000092176146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009276382,0.0008146418,0.0011002304,0.0059547992,0.0011881137,0.0010366604,0.0012447336,0.0008365449,0.0041299067],"category_scores_gemma":[0.0028657536,0.00033308883,0.0019067144,0.0066110105,0.00031978017,0.00091822504,0.0006156693,0.00071625935,0.0025007974],"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":[0.00086779345,0.0007789533,0.01552322,0.00034750142,0.00060319674,0.00020567446,0.00037795896,0.073274225,0.025033316,0.008360453,0.01961438,0.85501343],"study_design_scores_gemma":[0.00006355047,0.00022837047,0.019430947,0.000045978002,0.0002475083,0.00023074402,0.00036736755,0.9519627,0.008168677,0.009767247,0.009400292,0.00008656103],"about_ca_topic_score_codex":0.016356869,"about_ca_topic_score_gemma":0.014447235,"teacher_disagreement_score":0.016356869,"about_ca_system_score_codex":0.0009095619,"about_ca_system_score_gemma":0.0016251124,"threshold_uncertainty_score":0.032523274},"labels":[],"label_agreement":null}]}