{"meta":{"query_hash":"3b0806920ee2","filters":{"venue":"International Journal of Information Technology and Management"},"cohort_total":11,"direct_labels_cover":0,"predictions_cover":11,"exported":11,"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/3b0806920ee2","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Information+Technology+and+Management"},"results":[{"id":"W1981374061","doi":"10.1504/ijitm.2011.037759","title":"Analysing firm performance in Chinese IT industry: DEA Malmquist productivity measure","year":2010,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":20,"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 Toronto","funders":"","keywords":"Data envelopment analysis; Malmquist index; Productivity; Industrial organization; Measure (data warehouse); China; Maturity (psychological); Index (typography); Convergence (economics); Business; Economics; Econometrics; Total factor productivity; Computer science; Mathematics; Statistics; Economic growth","score_opus":0.017141982584320925,"score_gpt":0.3276121017129896,"score_spread":0.3104701191286687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981374061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97389877,0.000026400705,0.007981507,0.012314448,0.0007033092,0.00008784578,0.0000018104997,0.00001608246,0.004969813],"genre_scores_gemma":[0.9967086,0.000040442945,0.0027960318,0.00025493736,0.00005570044,0.000003224888,0.0000017092066,0.0000023241605,0.0001370466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99755067,0.00003524358,0.0009976788,0.00013429615,0.0011468194,0.0001353101],"domain_scores_gemma":[0.9978849,0.000070418086,0.0008613165,0.0002527636,0.0008919821,0.000038616163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036193859,0.00010957127,0.00021254843,0.004104499,0.00009030565,0.00020937315,0.0009663832,0.00017688036,0.000068263034],"category_scores_gemma":[0.0016363944,0.000080199025,0.00006320193,0.0017439313,0.00015763962,0.001902087,0.00022811185,0.0007420127,0.000027957227],"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":[0.00011169927,0.00014594327,0.55075014,0.000013958708,0.00019858957,0.000036518737,0.0005886156,0.004122271,0.00023025836,0.01669715,0.0008172114,0.42628765],"study_design_scores_gemma":[0.001786605,0.00013468275,0.85249,0.00016005171,0.00006853444,0.0004911214,0.0021494695,0.018945087,0.00090586365,0.02233182,0.10018846,0.00034829753],"about_ca_topic_score_codex":0.0000045532283,"about_ca_topic_score_gemma":0.00006074899,"teacher_disagreement_score":0.42593935,"about_ca_system_score_codex":0.00005701425,"about_ca_system_score_gemma":0.00004083921,"threshold_uncertainty_score":0.36624017},"labels":[],"label_agreement":null},{"id":"W2017758746","doi":"10.1504/ijitm.2007.013998","title":"Electronic service delivery in a multi-channel public sector: an assessment of the government of Canada","year":2007,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Service delivery framework; Government (linguistics); Service (business); Business; Corporate governance; Public sector; Relevance (law); Service design; Order (exchange); Public relations; Public administration; Private sector; Marketing; Political science; Economics; Economic growth; Finance","score_opus":0.009882912910744168,"score_gpt":0.2766849068300585,"score_spread":0.2668019939193143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017758746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96963316,0.000063692256,0.004831266,0.014402277,0.00047967877,0.00020194685,0.000008602718,0.000007252818,0.0103721395],"genre_scores_gemma":[0.9987912,0.0002466695,0.0004306057,0.00047535799,0.000014345219,0.0000021083902,0.0000010790553,0.0000013871522,0.000037227062],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9984374,0.000027343238,0.00043552005,0.00003795839,0.0009228955,0.00013886066],"domain_scores_gemma":[0.99897057,0.000029651364,0.00060067506,0.00006910805,0.00030184773,0.000028169183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011804914,0.00005058813,0.0000857793,0.000247389,0.00005397181,0.000020253232,0.0005421355,0.00005308963,0.000023875462],"category_scores_gemma":[0.0000327197,0.000040418538,0.000021585254,0.0003259179,0.000061676255,0.0006954281,0.00012031126,0.00012089962,7.864637e-8],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000951624,0.0002741159,0.094927296,0.000082215774,0.00033244176,0.00000597118,0.0041371146,0.00046120494,0.00007052927,0.86358553,0.00025991639,0.03576852],"study_design_scores_gemma":[0.004543477,0.00027218027,0.62500066,0.00032517122,0.00006180085,0.000020722331,0.21460384,0.004111877,0.0022779396,0.010269688,0.13818587,0.0003267875],"about_ca_topic_score_codex":0.010953243,"about_ca_topic_score_gemma":0.3530794,"teacher_disagreement_score":0.85331583,"about_ca_system_score_codex":0.000536417,"about_ca_system_score_gemma":0.00028668178,"threshold_uncertainty_score":0.9956329},"labels":[],"label_agreement":null},{"id":"W2082028343","doi":"10.1504/ijitm.2012.044061","title":"Dealing with biometric multi-dimensionality through chaotic neural network methodology","year":2011,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Biometrics; Chaotic; Curse of dimensionality; Dimensionality reduction; Artificial neural network; Computer science; Dimension (graph theory); Fingerprint (computing); Data mining; Linear subspace; Associative property; Artificial intelligence; Pattern recognition (psychology); Content-addressable memory; Machine learning; Mathematics","score_opus":0.06038198197880419,"score_gpt":0.2969288995294264,"score_spread":0.23654691755062224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082028343","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011191258,0.00014862182,0.984709,0.0026756723,0.00036016887,0.00010867224,6.8642873e-7,0.000050822993,0.000755054],"genre_scores_gemma":[0.46626094,0.00025878058,0.53269786,0.00073696394,0.000023975843,0.0000062506424,0.0000011861703,0.0000018082712,0.0000122196325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991989,0.000022147511,0.00038089888,0.00008383677,0.00019036316,0.00012382443],"domain_scores_gemma":[0.9991058,0.000040614435,0.0004225875,0.00013530652,0.00026560578,0.000030046092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034343326,0.000081871665,0.000116313735,0.0006213082,0.00007853531,0.000040964576,0.0006177786,0.00005265984,0.000008601944],"category_scores_gemma":[0.000016127911,0.00006128983,0.000030513274,0.0006254821,0.00007470714,0.0009770197,0.00025549115,0.00013748727,0.0000056924964],"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":[0.000026681775,0.000032255128,0.0007149846,0.0000061785995,0.00013357971,0.000021436743,0.00015457849,0.0010659306,0.0000069191105,0.88532823,0.00016038356,0.11234884],"study_design_scores_gemma":[0.008237954,0.0016812215,0.088815816,0.00040965452,0.0002501038,0.005113587,0.0013647737,0.12120995,0.004294708,0.6555636,0.11183835,0.0012203075],"about_ca_topic_score_codex":0.0000048698575,"about_ca_topic_score_gemma":0.0000014427596,"teacher_disagreement_score":0.4550697,"about_ca_system_score_codex":0.000019715433,"about_ca_system_score_gemma":0.000008327462,"threshold_uncertainty_score":0.24993268},"labels":[],"label_agreement":null},{"id":"W2607456581","doi":"10.1504/ijitm.2017.10004644","title":"Providing custom enterprise resource planning solutions: benefits and challenges","year":2017,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Enterprise resource planning; Flexibility (engineering); Key (lock); Resource (disambiguation); Enterprise system; Knowledge management; Process management; Architecture; Computer science; Enterprise architecture; Business; Computer security; Management; Economics","score_opus":0.042549524018246035,"score_gpt":0.2842843175992056,"score_spread":0.24173479358095956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607456581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50754523,0.016709896,0.028911881,0.2571222,0.0055798036,0.0019353044,0.000027318265,0.00051573646,0.18165264],"genre_scores_gemma":[0.9957487,0.002528925,0.0006144015,0.0008511662,0.00019989519,0.000008559571,0.000004848022,0.000004980857,0.000038522667],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99916524,0.000004151276,0.00040462211,0.00006838954,0.00023323951,0.00012435428],"domain_scores_gemma":[0.9987145,0.000012078114,0.0009328391,0.00012105606,0.00020647279,0.000013025624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048469505,0.000092332295,0.000113320835,0.0011713189,0.00032912934,0.00054176507,0.00037901622,0.000053495376,0.0000126609],"category_scores_gemma":[0.00013596738,0.000082177416,0.000028073611,0.000051546187,0.00007084414,0.003784704,0.00039798798,0.00010196722,0.000013240769],"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":[0.000056287972,0.000019269071,0.00689723,0.00011577818,0.00015869,0.000013177125,0.00028058919,0.000038543458,0.000006878143,0.47888708,0.0021960041,0.5113305],"study_design_scores_gemma":[0.0020635964,0.000042878622,0.053129323,0.0006661319,0.00006124509,0.00013687226,0.0075423853,0.0008207482,0.000046702564,0.006047876,0.9292534,0.00018886101],"about_ca_topic_score_codex":0.000008910996,"about_ca_topic_score_gemma":0.0000036095435,"teacher_disagreement_score":0.9270574,"about_ca_system_score_codex":0.000030048363,"about_ca_system_score_gemma":0.000006097749,"threshold_uncertainty_score":0.5224253},"labels":[],"label_agreement":null},{"id":"W2710937531","doi":"10.1504/ijitm.2017.10005698","title":"Enhancing BRICS integration: a cloud-based green supply chain concept","year":2017,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","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":"Carleton University","funders":"","keywords":"Cloud computing; Supply chain; Industrialisation; Business; Industrial organization; International trade; Economics; Marketing; Political science; Market economy","score_opus":0.008936676141044056,"score_gpt":0.2422978197678667,"score_spread":0.23336114362682264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2710937531","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1808012,0.00018534965,0.44659618,0.3128887,0.005383911,0.00079235155,0.00001987107,0.00045414967,0.05287829],"genre_scores_gemma":[0.9912431,0.000061629355,0.0038406323,0.0043023424,0.00034503275,0.000014812001,0.000028356915,0.000006304371,0.00015775586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989275,0.0000032090327,0.0005762296,0.00008249659,0.00027475986,0.00013582094],"domain_scores_gemma":[0.9978139,0.0000151441245,0.0011878379,0.00024186564,0.0007326019,0.000008655625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037272484,0.00012477407,0.0001548364,0.0019008565,0.0003271902,0.0003869955,0.0008979364,0.00013551433,0.00007633367],"category_scores_gemma":[0.00019339567,0.00011379407,0.000054936936,0.00025099987,0.00027598895,0.0028586797,0.00032008663,0.00025838017,0.000048190286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003468801,0.00003755455,0.0049006306,0.000030687086,0.00012563821,0.000024834568,0.00004589434,0.000019144996,0.00004681494,0.81486243,0.0031853905,0.1766863],"study_design_scores_gemma":[0.006475369,0.0001497778,0.038427692,0.0008433794,0.00022849212,0.00016120615,0.005241754,0.004633457,0.0059034023,0.16285272,0.7743854,0.0006973703],"about_ca_topic_score_codex":0.00006207971,"about_ca_topic_score_gemma":0.000052520747,"teacher_disagreement_score":0.8104419,"about_ca_system_score_codex":0.00004549407,"about_ca_system_score_gemma":0.000018437748,"threshold_uncertainty_score":0.46403873},"labels":[],"label_agreement":null},{"id":"W4231348628","doi":"10.1504/ijitm.2017.083865","title":"Providing custom enterprise resource planning solutions: benefits and challenges","year":2017,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","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":"Carleton University","funders":"","keywords":"Enterprise resource planning; Flexibility (engineering); Key (lock); Resource (disambiguation); Architecture; Computer science; Knowledge management; Process management; Enterprise system; Business; Computer security; Management; Economics","score_opus":0.042549524018246035,"score_gpt":0.2842843175992056,"score_spread":0.24173479358095956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231348628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50754523,0.016709896,0.028911881,0.2571222,0.0055798036,0.0019353044,0.000027318265,0.00051573646,0.18165264],"genre_scores_gemma":[0.9957487,0.002528925,0.0006144015,0.0008511662,0.00019989519,0.000008559571,0.000004848022,0.000004980857,0.000038522667],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99916524,0.000004151276,0.00040462211,0.00006838954,0.00023323951,0.00012435428],"domain_scores_gemma":[0.9987145,0.000012078114,0.0009328391,0.00012105606,0.00020647279,0.000013025624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048469505,0.000092332295,0.000113320835,0.0011713189,0.00032912934,0.00054176507,0.00037901622,0.000053495376,0.0000126609],"category_scores_gemma":[0.00013596738,0.000082177416,0.000028073611,0.000051546187,0.00007084414,0.003784704,0.00039798798,0.00010196722,0.000013240769],"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":[0.000056287972,0.000019269071,0.00689723,0.00011577818,0.00015869,0.000013177125,0.00028058919,0.000038543458,0.000006878143,0.47888708,0.0021960041,0.5113305],"study_design_scores_gemma":[0.0020635964,0.000042878622,0.053129323,0.0006661319,0.00006124509,0.00013687226,0.0075423853,0.0008207482,0.000046702564,0.006047876,0.9292534,0.00018886101],"about_ca_topic_score_codex":0.000008910996,"about_ca_topic_score_gemma":0.0000036095435,"teacher_disagreement_score":0.9270574,"about_ca_system_score_codex":0.000030048363,"about_ca_system_score_gemma":0.000006097749,"threshold_uncertainty_score":0.5224253},"labels":[],"label_agreement":null},{"id":"W4255374636","doi":"10.1504/ijitm.2017.086862","title":"Enhancing BRICS integration: a cloud-based green supply chain concept","year":2017,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","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":"Carleton University","funders":"","keywords":"Cloud computing; Supply chain; Industrialisation; Business; Industrial organization; International trade; Economics; Marketing; Political science; Market economy","score_opus":0.008936676141044056,"score_gpt":0.2422978197678667,"score_spread":0.23336114362682264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255374636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1808012,0.00018534965,0.44659618,0.3128887,0.005383911,0.00079235155,0.00001987107,0.00045414967,0.05287829],"genre_scores_gemma":[0.9912431,0.000061629355,0.0038406323,0.0043023424,0.00034503275,0.000014812001,0.000028356915,0.000006304371,0.00015775586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989275,0.0000032090327,0.0005762296,0.00008249659,0.00027475986,0.00013582094],"domain_scores_gemma":[0.9978139,0.0000151441245,0.0011878379,0.00024186564,0.0007326019,0.000008655625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037272484,0.00012477407,0.0001548364,0.0019008565,0.0003271902,0.0003869955,0.0008979364,0.00013551433,0.00007633367],"category_scores_gemma":[0.00019339567,0.00011379407,0.000054936936,0.00025099987,0.00027598895,0.0028586797,0.00032008663,0.00025838017,0.000048190286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003468801,0.00003755455,0.0049006306,0.000030687086,0.00012563821,0.000024834568,0.00004589434,0.000019144996,0.00004681494,0.81486243,0.0031853905,0.1766863],"study_design_scores_gemma":[0.006475369,0.0001497778,0.038427692,0.0008433794,0.00022849212,0.00016120615,0.005241754,0.004633457,0.0059034023,0.16285272,0.7743854,0.0006973703],"about_ca_topic_score_codex":0.00006207971,"about_ca_topic_score_gemma":0.000052520747,"teacher_disagreement_score":0.8104419,"about_ca_system_score_codex":0.00004549407,"about_ca_system_score_gemma":0.000018437748,"threshold_uncertainty_score":0.46403873},"labels":[],"label_agreement":null},{"id":"W4390920843","doi":"10.1504/ijitm.2024.10061685","title":"Applying machine learning algorithms to determine and predict the reasons and models for employee turnover","year":2024,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":1,"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":"Computer science; Machine learning; Artificial intelligence; Algorithm; Knowledge management; Industrial engineering; Engineering","score_opus":0.012420193256957082,"score_gpt":0.23955139422113503,"score_spread":0.22713120096417794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390920843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18859509,0.0029529487,0.7423853,0.057865933,0.0011851519,0.0016714655,0.000022941538,0.0005832326,0.004737928],"genre_scores_gemma":[0.9920633,0.0008855775,0.0055057914,0.0011411383,0.00015183538,0.00009955827,0.000007919708,0.000007854571,0.00013703539],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99942726,0.0000017628819,0.0002553929,0.00007412126,0.00014795776,0.00009352398],"domain_scores_gemma":[0.9996353,0.00003435687,0.00013613068,0.00005177505,0.0001350413,0.0000074167315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030438107,0.00008663789,0.000092696784,0.0010150914,0.0001161196,0.00033492967,0.0002082322,0.00005677411,0.0000038275743],"category_scores_gemma":[0.00007123427,0.00005937125,0.000024402965,0.00018142581,0.00006371064,0.0014589928,0.00033473477,0.00015394994,0.0000029515982],"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":[0.000039313378,0.0000055364867,0.0010967206,0.000116954696,0.00015038584,0.000008578984,0.00007806732,0.00024329414,0.000014131465,0.3086742,0.0016887619,0.6878841],"study_design_scores_gemma":[0.0007442178,0.00008452157,0.0019326563,0.00029690002,0.00011322004,0.00014736882,0.0013280803,0.12191589,0.000048913735,0.0941122,0.77911484,0.00016118833],"about_ca_topic_score_codex":0.000007752548,"about_ca_topic_score_gemma":0.000005492574,"teacher_disagreement_score":0.8034682,"about_ca_system_score_codex":0.000016459611,"about_ca_system_score_gemma":0.0000039852266,"threshold_uncertainty_score":0.32297346},"labels":[],"label_agreement":null},{"id":"W4391136406","doi":"10.1504/ijitm.2024.136187","title":"Applying machine learning algorithms to determine and predict the reasons and models for employee turnover","year":2024,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":7,"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":"Deutscher Akademischer Austauschdienst","keywords":"Computer science; Machine learning; Artificial intelligence; Algorithm; Knowledge management","score_opus":0.012420193256957082,"score_gpt":0.23955139422113503,"score_spread":0.22713120096417794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391136406","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18859509,0.0029529487,0.7423853,0.057865933,0.0011851519,0.0016714655,0.000022941538,0.0005832326,0.004737928],"genre_scores_gemma":[0.9920633,0.0008855775,0.0055057914,0.0011411383,0.00015183538,0.00009955827,0.000007919708,0.000007854571,0.00013703539],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99942726,0.0000017628819,0.0002553929,0.00007412126,0.00014795776,0.00009352398],"domain_scores_gemma":[0.9996353,0.00003435687,0.00013613068,0.00005177505,0.0001350413,0.0000074167315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030438107,0.00008663789,0.000092696784,0.0010150914,0.0001161196,0.00033492967,0.0002082322,0.00005677411,0.0000038275743],"category_scores_gemma":[0.00007123427,0.00005937125,0.000024402965,0.00018142581,0.00006371064,0.0014589928,0.00033473477,0.00015394994,0.0000029515982],"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":[0.000039313378,0.0000055364867,0.0010967206,0.000116954696,0.00015038584,0.000008578984,0.00007806732,0.00024329414,0.000014131465,0.3086742,0.0016887619,0.6878841],"study_design_scores_gemma":[0.0007442178,0.00008452157,0.0019326563,0.00029690002,0.00011322004,0.00014736882,0.0013280803,0.12191589,0.000048913735,0.0941122,0.77911484,0.00016118833],"about_ca_topic_score_codex":0.000007752548,"about_ca_topic_score_gemma":0.000005492574,"teacher_disagreement_score":0.8034682,"about_ca_system_score_codex":0.000016459611,"about_ca_system_score_gemma":0.0000039852266,"threshold_uncertainty_score":0.32297346},"labels":[],"label_agreement":null},{"id":"W4402171970","doi":"10.29070/3sbta617","title":"Stock Price Prediction Using Artificial Intelligence and Neural Networks","year":2024,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"Stock Market Forecasting Methods","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Artificial neural network; Artificial intelligence; Stock (firearms); Artificial Intelligence System; Computer science; Stock price; Machine learning; Engineering; Series (stratigraphy); Biology","score_opus":0.07297232782300522,"score_gpt":0.3826017305957792,"score_spread":0.30962940277277395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402171970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049440842,0.00028766648,0.9454113,0.0018742166,0.0019759482,0.00009987981,0.0000030140507,0.00003993184,0.0008671609],"genre_scores_gemma":[0.96888566,0.00019364436,0.030644093,0.00012131331,0.00011360869,0.0000028717718,0.0000010163898,0.0000030711062,0.000034740093],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984261,0.000043041477,0.0007827544,0.00009987789,0.0005536418,0.000094583396],"domain_scores_gemma":[0.9989276,0.00024208754,0.0003359235,0.000086483684,0.00037328384,0.000034639383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022126387,0.00007687421,0.00010922289,0.001994473,0.00007088012,0.00038443468,0.00035791763,0.00007716065,0.000029010493],"category_scores_gemma":[0.00065326557,0.000059298232,0.000036821613,0.0005907799,0.00010219489,0.0012812715,0.00024015621,0.00021133506,0.0000031077952],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042623073,0.0000062971917,0.0004123869,0.0000073142874,0.000065054715,0.000015431318,0.00011551497,0.006581505,0.000006649315,0.11795659,0.00021489758,0.87457573],"study_design_scores_gemma":[0.00007469001,0.00008956752,0.0019162444,0.00008669677,0.000024417644,0.0006320746,0.0009067308,0.82514364,0.000087820765,0.16248639,0.0084876735,0.000064073094],"about_ca_topic_score_codex":0.0000010119529,"about_ca_topic_score_gemma":4.6782932e-7,"teacher_disagreement_score":0.9194448,"about_ca_system_score_codex":0.000054322692,"about_ca_system_score_gemma":0.000012648155,"threshold_uncertainty_score":0.37071124},"labels":[],"label_agreement":null},{"id":"W4402200663","doi":"10.29070/8cbrrt74","title":"MEETVERSE: A new way of Interaction on Online Meeting Platforms","year":2024,"lang":"en","type":"article","venue":"International Journal of Information Technology and Management","topic":"Wikis in Education and Collaboration","field":"Social 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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Engineering; Computer science","score_opus":0.010862446349660475,"score_gpt":0.33100781411192726,"score_spread":0.32014536776226676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402200663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5983019,0.0008026218,0.050225455,0.11884754,0.016792161,0.00070086593,0.000025330977,0.0002977881,0.21400633],"genre_scores_gemma":[0.99412847,0.0014718083,0.003242338,0.00032065524,0.00019170342,0.0000023978937,0.000007826646,0.0000022875656,0.00063252234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992029,0.000008505798,0.00036636772,0.000039663308,0.00032463577,0.000057939647],"domain_scores_gemma":[0.9993559,0.000033586988,0.00025816078,0.000040826828,0.00028410385,0.00002743663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036184344,0.000046275847,0.00006503817,0.0011603821,0.00005479415,0.00007893396,0.00018173733,0.000061585815,0.00006931169],"category_scores_gemma":[0.00012799968,0.000039860653,0.000029732983,0.0003527299,0.000056238012,0.0010530157,0.000030659117,0.00011463632,0.000013191903],"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":[0.000038308764,0.000027574577,0.000071319824,0.000013442594,0.000093318115,0.000002177242,0.0033392743,0.00011757579,0.000013598892,0.6632481,0.0053941784,0.32764113],"study_design_scores_gemma":[0.00041624618,0.00011853529,0.00049187697,0.00045659125,0.000027747663,0.000013361027,0.04012997,0.00040007377,0.0007816302,0.032812994,0.92427486,0.00007609102],"about_ca_topic_score_codex":0.000022941833,"about_ca_topic_score_gemma":0.00003323347,"teacher_disagreement_score":0.9188807,"about_ca_system_score_codex":0.00012299976,"about_ca_system_score_gemma":0.00008517994,"threshold_uncertainty_score":0.16254702},"labels":[],"label_agreement":null}]}