{"meta":{"query_hash":"6668d808bb10","filters":{"venue":"Journal of Ubiquitous Systems and Pervasive Networks"},"cohort_total":101,"direct_labels_cover":0,"predictions_cover":101,"exported":101,"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/6668d808bb10","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Ubiquitous+Systems+and+Pervasive+Networks"},"results":[{"id":"W1971196735","doi":"10.5383/juspn.03.01.005","title":"An Efficient Channel Estimator for Frequency Hopping System via Propagator Method","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Estimator; Propagator; Channel (broadcasting); Frequency-hopping spread spectrum; Statistical physics; Computer science; Mathematics; Physics; Statistics; Telecommunications; Mathematical physics","score_opus":0.026621968057328613,"score_gpt":0.27527702314951175,"score_spread":0.24865505509218314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971196735","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007335852,0.0012039171,0.98840034,0.000024943904,0.0020094477,0.0006942766,0.0000043306695,0.00012131248,0.00020560261],"genre_scores_gemma":[0.76695776,0.000018591823,0.2325157,0.000017262044,0.0004166496,0.000047246067,5.9759026e-7,0.000020276248,0.00000590989],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977822,0.00026747663,0.0010144871,0.00029074596,0.000345861,0.00029927003],"domain_scores_gemma":[0.99666137,0.00021100065,0.0013953126,0.00036997904,0.0011180791,0.00024426167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020047342,0.00022356355,0.0006214305,0.0002628635,0.00017924722,0.0001409357,0.0006353782,0.00016492032,0.0000012106392],"category_scores_gemma":[0.00007393176,0.00017820897,0.00016687003,0.0002753564,0.00004606953,0.0005255366,0.00006267896,0.00019584985,5.0454395e-7],"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":[0.00073955156,0.0021078568,0.0032950472,0.010676247,0.0016894782,0.0005221024,0.031194722,0.392341,0.029973844,0.38235274,0.0035880785,0.14151934],"study_design_scores_gemma":[0.0003655198,0.0011566821,0.00025162552,0.0011205549,0.00005755471,0.0011823142,0.00038890023,0.9914394,0.0032598933,0.0004983218,0.00005094426,0.00022829628],"about_ca_topic_score_codex":0.00016494544,"about_ca_topic_score_gemma":0.0000032273044,"teacher_disagreement_score":0.7596219,"about_ca_system_score_codex":0.00010704342,"about_ca_system_score_gemma":0.00013468931,"threshold_uncertainty_score":0.7267151},"labels":[],"label_agreement":null},{"id":"W1993197252","doi":"10.5383/juspn.01.01.001","title":"Ambient Things on the Web","year":2010,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"World Wide Web; Computer science","score_opus":0.01652226279357138,"score_gpt":0.22656795924155548,"score_spread":0.2100456964479841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993197252","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":[0.8717399,0.00212369,0.09432039,0.008697192,0.018876212,0.00077952293,0.000005187086,0.000093128445,0.0033647653],"genre_scores_gemma":[0.996596,0.00013328558,0.00012332268,0.00091144774,0.0020007286,0.000010738605,2.3368261e-7,0.000013426306,0.000210831],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981162,0.00027772595,0.00058239035,0.00022788493,0.00051263376,0.00028319823],"domain_scores_gemma":[0.997174,0.00093521905,0.00075778284,0.00043510192,0.000514167,0.00018369616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018578464,0.0001918638,0.00038635536,0.0001227553,0.00027803928,0.0006158457,0.0007614825,0.00015479558,0.000013492925],"category_scores_gemma":[0.00012809274,0.00011467605,0.00016848928,0.00021867499,0.00006677889,0.00060194684,0.00013533227,0.00095597655,0.000013746395],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049792964,0.001374183,0.016928539,0.0005114808,0.0019192181,0.0017872086,0.027368786,0.0074157603,0.06503183,0.2109147,0.33876243,0.32748795],"study_design_scores_gemma":[0.0034864054,0.0031287284,0.008283186,0.002690288,0.00015144213,0.01934295,0.0039049694,0.44393247,0.0012773017,0.0014958475,0.5107303,0.001576075],"about_ca_topic_score_codex":0.000069820795,"about_ca_topic_score_gemma":0.000054299417,"teacher_disagreement_score":0.4365167,"about_ca_system_score_codex":0.000034064316,"about_ca_system_score_gemma":0.00011271054,"threshold_uncertainty_score":0.59386146},"labels":[],"label_agreement":null},{"id":"W2005207744","doi":"10.5383/juspn.04.01.001","title":"Ambient Intelligence on Personal Mobility Assistants for Sustainable Travel Choices","year":2012,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Personal mobility; Ambient intelligence; Psychology; Computer science; Business; Human–computer interaction; Telecommunications","score_opus":0.022044239403083362,"score_gpt":0.25788802991445725,"score_spread":0.23584379051137389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005207744","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":[0.846204,0.0051471717,0.14524253,0.000060678933,0.0020631044,0.00061202206,0.000030080299,0.00003536972,0.00060507463],"genre_scores_gemma":[0.9985439,0.00021723198,0.00010080836,0.000046673515,0.000824887,0.000030018035,0.000005515867,0.00001685213,0.00021408987],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9988587,0.000026161144,0.0005197123,0.00008864699,0.0001763234,0.00033048686],"domain_scores_gemma":[0.9990137,0.00017204469,0.00015542816,0.00008510471,0.000421804,0.00015187643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068297045,0.00013966713,0.0002696213,0.000091937116,0.0001232585,0.0000643652,0.00008167152,0.00010323567,0.00001276978],"category_scores_gemma":[0.000033362332,0.00011640071,0.000100833604,0.00013986944,0.00003593234,0.00026801278,0.000004197687,0.00021952669,6.40064e-7],"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":[0.0008657977,0.0015663484,0.07076891,0.004830638,0.0013123151,0.00006107648,0.020571502,0.7954227,0.002556262,0.06614954,0.016741106,0.019153804],"study_design_scores_gemma":[0.0029304423,0.002502446,0.5794283,0.0014523643,0.00050932367,0.00048194994,0.07219575,0.23674278,0.0019396247,0.00041031078,0.09985133,0.001555363],"about_ca_topic_score_codex":0.000028379172,"about_ca_topic_score_gemma":0.00002035838,"teacher_disagreement_score":0.55867994,"about_ca_system_score_codex":0.000101031605,"about_ca_system_score_gemma":0.000031376403,"threshold_uncertainty_score":0.47466832},"labels":[],"label_agreement":null},{"id":"W2031868952","doi":"10.5383/juspn.02.01.005","title":"Energy-Efficient and Scalable Group Key Management for Hierarchical Sensor Network","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Scalability; Key (lock); Computer science; Wireless sensor network; Group (periodic table); Distributed computing; Computer network; Computer security; Database; Chemistry","score_opus":0.0174278056212629,"score_gpt":0.21335146201369226,"score_spread":0.19592365639242937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031868952","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":[0.03471237,0.015170922,0.9439994,0.00022310132,0.003970397,0.0005339297,0.0000032331238,0.000059950664,0.0013267153],"genre_scores_gemma":[0.96343666,0.0028381452,0.030301271,0.00036407265,0.0028244448,0.000032222346,0.0000019300435,0.0000389776,0.0001622774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972471,0.0002513277,0.0008797366,0.0004622673,0.00042333346,0.00073624577],"domain_scores_gemma":[0.9978265,0.00043689625,0.00061351893,0.00040775357,0.0003151424,0.00040015805],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011492806,0.00033036686,0.0006725224,0.00016101987,0.00034997353,0.00032123455,0.0006236033,0.00024789327,0.0000034151076],"category_scores_gemma":[0.000013981208,0.0002721738,0.00018393001,0.00030310167,0.00013495621,0.0002381323,0.00032179127,0.0003899422,7.200475e-7],"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":[0.00076975586,0.0006246919,0.0028624374,0.0006863329,0.0012126543,0.0010873483,0.005748129,0.27857423,0.000054404038,0.56494623,0.024160787,0.119273014],"study_design_scores_gemma":[0.0015196808,0.0010520599,0.0014541134,0.00074006984,0.00012930746,0.0017905007,0.0004699781,0.9692816,0.0000109789735,0.0028220185,0.020224838,0.00050483824],"about_ca_topic_score_codex":0.00005849016,"about_ca_topic_score_gemma":0.000021102649,"teacher_disagreement_score":0.9287243,"about_ca_system_score_codex":0.000059302693,"about_ca_system_score_gemma":0.000029303912,"threshold_uncertainty_score":0.99997306},"labels":[],"label_agreement":null},{"id":"W2072139326","doi":"10.5383/juspn.03.02.006","title":"Configuring Snort as a Firewall on Windows 7 Environment","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Operating system; Firewall (physics); Computer science; Context-based access control; Windows Vista; Embedded system; Microsoft Windows; Application firewall; Computer security; Physics; Stateful firewall; Software; Astronomy","score_opus":0.02065673674838837,"score_gpt":0.20542210615519504,"score_spread":0.18476536940680668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072139326","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":[0.8418134,0.010992233,0.12684345,0.0003634424,0.00813155,0.0007243667,0.000002012675,0.00008835816,0.011041209],"genre_scores_gemma":[0.9961535,0.0017672082,0.00029591835,0.0002994927,0.0012861185,0.0000063437633,2.80926e-7,0.000012109782,0.0001790258],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983867,0.00015479153,0.00056075933,0.0002411984,0.00036716048,0.00028940488],"domain_scores_gemma":[0.9987554,0.00010406269,0.000539827,0.00028306755,0.0001008869,0.00021678045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006298836,0.00018875691,0.00035115163,0.00011717923,0.00020251182,0.00014376512,0.0004169952,0.0001537241,0.000050027666],"category_scores_gemma":[0.000015005973,0.00014976748,0.00013113745,0.00010647806,0.000045379573,0.0003587163,0.000106851956,0.00043072706,0.000019559484],"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":[0.0033086543,0.0029129474,0.014481743,0.0007513701,0.002479506,0.007184941,0.09657696,0.16854794,0.0031891463,0.12663196,0.04374413,0.5301907],"study_design_scores_gemma":[0.006691593,0.022401836,0.025184024,0.004250837,0.00029241852,0.018504415,0.0018984878,0.5967007,0.0037047088,0.006255215,0.3115134,0.0026023577],"about_ca_topic_score_codex":0.00015173739,"about_ca_topic_score_gemma":0.000009013665,"teacher_disagreement_score":0.52758837,"about_ca_system_score_codex":0.0000617176,"about_ca_system_score_gemma":0.000038742677,"threshold_uncertainty_score":0.6107341},"labels":[],"label_agreement":null},{"id":"W2075448825","doi":"10.5383/juspn.03.02.001","title":"PISC: A Portable Interactive Surface Computer","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer graphics (images); Surface (topology); Human–computer interaction; Computer science; Multimedia; Mathematics","score_opus":0.02377696663755122,"score_gpt":0.23114398334925812,"score_spread":0.2073670167117069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075448825","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":[0.01935424,0.0020907833,0.97518116,0.0002022374,0.0013885542,0.00022007996,0.0000025305794,0.000030203379,0.0015302221],"genre_scores_gemma":[0.9890948,0.00041780373,0.009374279,0.00019054106,0.00070224126,0.0000051192023,9.4550654e-7,0.000013302962,0.00020097861],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998546,0.00014083167,0.00058968196,0.00021946896,0.00024189362,0.00026210852],"domain_scores_gemma":[0.9981473,0.00015157132,0.00074920635,0.0003233686,0.0004347406,0.00019378976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056224474,0.00016039443,0.000368009,0.00007599589,0.00014074983,0.00016866528,0.0005753248,0.00010505379,0.000010496886],"category_scores_gemma":[0.000008633656,0.00012616164,0.00010468553,0.00021287013,0.00005302704,0.0005850593,0.00017816851,0.00034840102,0.0000055877704],"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":[0.00055999064,0.0026700036,0.028837213,0.000809793,0.0037582235,0.002143449,0.069840126,0.42450172,0.0014204212,0.15594426,0.21273014,0.096784666],"study_design_scores_gemma":[0.0014719791,0.0014703234,0.008297055,0.00084689836,0.00012515452,0.005715756,0.0016904615,0.94979644,0.0002178119,0.0012766832,0.028409008,0.0006824038],"about_ca_topic_score_codex":0.00026468525,"about_ca_topic_score_gemma":0.000022172297,"teacher_disagreement_score":0.96974057,"about_ca_system_score_codex":0.000059294358,"about_ca_system_score_gemma":0.00007947524,"threshold_uncertainty_score":0.51447225},"labels":[],"label_agreement":null},{"id":"W2075560215","doi":"10.5383/juspn.02.01.003","title":"Context-based Integrated Suites for News Delivery System","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Delivery system; Computer science; World Wide Web; Biology; Engineering; Biomedical engineering","score_opus":0.05764427042650719,"score_gpt":0.28216628992635234,"score_spread":0.22452201949984515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075560215","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":[0.7732567,0.071359135,0.11558693,0.0035185986,0.013766123,0.0044857464,0.000072580246,0.00054583064,0.017408341],"genre_scores_gemma":[0.99735457,0.00079972163,0.0009086807,0.00015033153,0.0005923072,0.000027054357,0.0000031690054,0.000014614393,0.00014956534],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99846673,0.00037166593,0.0005821638,0.00012133474,0.00018364411,0.00027448978],"domain_scores_gemma":[0.99727035,0.00080033153,0.0006724531,0.0001919497,0.00089126977,0.00017367577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011666937,0.00013117846,0.00041680012,0.00015201242,0.00036877504,0.00007771727,0.00041110415,0.00028227965,0.000023670318],"category_scores_gemma":[0.00026956908,0.00010325239,0.00014148543,0.00016624932,0.00022359475,0.00013280498,0.000027319096,0.0002711113,0.0000019502559],"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":[0.0025635876,0.0009275297,0.12783603,0.0011373431,0.0014960566,0.00023298588,0.07377665,0.0013409061,0.00076138123,0.36586583,0.07322688,0.35083482],"study_design_scores_gemma":[0.0054694894,0.0019492212,0.0027806344,0.0026153896,0.00039653483,0.00025881044,0.29661354,0.05871098,0.00022816744,0.00027909278,0.62979275,0.00090536725],"about_ca_topic_score_codex":0.0048695523,"about_ca_topic_score_gemma":0.0035723848,"teacher_disagreement_score":0.5565659,"about_ca_system_score_codex":0.00011583743,"about_ca_system_score_gemma":0.00025826588,"threshold_uncertainty_score":0.7361339},"labels":[],"label_agreement":null},{"id":"W2097186897","doi":"10.5383/juspn.04.01.004","title":"A Multimodal Transport Network Model for Advanced Traveler Information System","year":2012,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Technische Universiteit Eindhoven","keywords":"Multimodal transport; Computer science; Transport engineering; Engineering","score_opus":0.01756176611234764,"score_gpt":0.26212820871469816,"score_spread":0.24456644260235053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097186897","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":[0.08246007,0.0021473723,0.91138023,0.00009574357,0.002462995,0.00061194063,0.00002485454,0.000043216813,0.00077357603],"genre_scores_gemma":[0.9940139,0.00028158998,0.0034011942,0.00006247305,0.0020407552,0.000023646548,0.000023035442,0.000012469013,0.00014095704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847674,0.000085903965,0.00067145407,0.000072774244,0.00030322516,0.00038987724],"domain_scores_gemma":[0.9984351,0.00012934518,0.00062721205,0.00006233695,0.0005115889,0.00023445106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001412452,0.00012850907,0.0003186273,0.000074496566,0.0004442908,0.000067656976,0.00010202506,0.00019404692,0.000002304513],"category_scores_gemma":[0.000026517397,0.000111327405,0.000119778575,0.0001384762,0.000044263044,0.0011199582,0.000002266047,0.00015659997,5.5514397e-7],"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":[0.00015529564,0.000014353517,0.007281205,0.000103851,0.00004080919,9.934402e-7,0.020548668,0.96507436,0.0000018934912,0.0048000515,0.0007262873,0.0012522585],"study_design_scores_gemma":[0.0017837604,0.00015928892,0.009340804,0.0006270452,0.00018487919,0.0000469664,0.021111535,0.95166963,0.0000012612634,0.00002014751,0.014750607,0.00030405878],"about_ca_topic_score_codex":0.00010489262,"about_ca_topic_score_gemma":0.00011132349,"teacher_disagreement_score":0.9115538,"about_ca_system_score_codex":0.000079853824,"about_ca_system_score_gemma":0.00012696399,"threshold_uncertainty_score":0.45397997},"labels":[],"label_agreement":null},{"id":"W2104632301","doi":"10.5383/juspn.03.02.004","title":"Recommendations for Australia’s Implementation of the National Emergency Warning System Using Location-Based Services","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and GPS-based Vehicle Safety Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Warning system; Business; Early warning system; Computer science; Medical emergency; Computer security; Process management; Telecommunications; Medicine","score_opus":0.06869583214843028,"score_gpt":0.30355333961034386,"score_spread":0.23485750746191358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104632301","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":[0.85637915,0.0029198178,0.1290032,0.00013506754,0.009884087,0.0013218434,0.000104955536,0.000054524204,0.00019735249],"genre_scores_gemma":[0.9985454,0.000033924487,0.00042133476,0.0000109513085,0.0009186169,0.00001843219,0.000009039427,0.000022909093,0.000019411342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984838,0.00009562626,0.00092025206,0.00009140784,0.00022734284,0.00018157827],"domain_scores_gemma":[0.9981698,0.000077305885,0.0007091441,0.00008857518,0.00089452276,0.000060675648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006906691,0.00014346822,0.00027489758,0.000108133536,0.00017366822,0.000025134073,0.00016040051,0.00010011657,0.000015083482],"category_scores_gemma":[0.000006891286,0.00011034796,0.0001328308,0.00020326198,0.000016797894,0.00018403548,0.000011211555,0.00013584473,3.496673e-7],"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":[0.0000642086,0.00003865235,0.042119335,0.0037880216,0.00042380727,0.0000015165887,0.0039381306,0.9431948,0.0017461806,0.0008496876,0.0028387257,0.0009969468],"study_design_scores_gemma":[0.0013369931,0.00022445696,0.015500423,0.0022753107,0.00024953295,0.00012578275,0.011968092,0.9649369,0.0011185042,0.000030076573,0.0019178971,0.0003160442],"about_ca_topic_score_codex":0.00052767986,"about_ca_topic_score_gemma":0.00014468124,"teacher_disagreement_score":0.14216623,"about_ca_system_score_codex":0.00013951186,"about_ca_system_score_gemma":0.00007819112,"threshold_uncertainty_score":0.44998592},"labels":[],"label_agreement":null},{"id":"W2137776299","doi":"10.5383/juspn.01.01.002","title":"Stenog-Shell Framework for Anonymous File Exchange","year":2010,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Shell (structure); Computer science; Operating system; Materials science; Composite material","score_opus":0.016046377316010996,"score_gpt":0.2576752301299648,"score_spread":0.2416288528139538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137776299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005497526,0.0057820445,0.98311406,0.00044893412,0.0044729915,0.00037547853,0.000086488,0.00010703785,0.000115454706],"genre_scores_gemma":[0.62682843,0.0012341744,0.36636358,0.00036654779,0.004669192,0.000081508086,0.00001377865,0.000054024382,0.00038878113],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99841297,0.000048480237,0.00054576993,0.00029899945,0.00026927792,0.00042447908],"domain_scores_gemma":[0.997097,0.0009246974,0.000752998,0.0006134157,0.00044865956,0.00016323947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056254806,0.00022496015,0.00048896344,0.00015728634,0.00021249859,0.00028392827,0.0010890461,0.00036399183,0.000029509265],"category_scores_gemma":[0.0004097263,0.00017642917,0.00013247674,0.00024059473,0.00010466587,0.0006728197,0.00029132882,0.0008276802,0.0000029493629],"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":[0.00025119618,0.0003690978,0.0009082303,0.0008643286,0.00045982836,0.0009819164,0.0033200076,0.012035563,0.004216889,0.28641543,0.34244353,0.34773397],"study_design_scores_gemma":[0.0028627831,0.004518877,0.0014746974,0.0017359584,0.00015292475,0.008091152,0.0023960066,0.18846981,0.00074828294,0.05262289,0.73508054,0.0018460839],"about_ca_topic_score_codex":0.000016422235,"about_ca_topic_score_gemma":0.000027559643,"teacher_disagreement_score":0.6213309,"about_ca_system_score_codex":0.000034944875,"about_ca_system_score_gemma":0.000067205205,"threshold_uncertainty_score":0.71945727},"labels":[],"label_agreement":null},{"id":"W2187400216","doi":"10.5383/juspn.05.02.002","title":"Simulation of Carpooling Agents with the Janus Platform","year":2014,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Information and Communication Technologies","keywords":"Carpool; Computer science; Negotiation; Plan (archaeology); Process (computing); NetLogo; Work (physics); Function (biology); Agent-based model; Traffic congestion; Matching (statistics); Transport engineering; Engineering; Artificial intelligence","score_opus":0.014588978511134037,"score_gpt":0.2217148646401877,"score_spread":0.20712588612905367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187400216","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":[0.803059,0.0006297139,0.19529487,0.00004078704,0.00046242663,0.00013566206,0.000003109234,0.000013469455,0.00036098165],"genre_scores_gemma":[0.99946094,0.00006310235,0.000059589598,0.000028628912,0.0003555441,0.0000023796308,0.0000025502857,0.0000109029,0.000016347896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993255,0.000017479024,0.00036626984,0.000044103414,0.00015060163,0.00009605134],"domain_scores_gemma":[0.99923545,0.00017859174,0.00019768992,0.00008434072,0.00026433702,0.000039615254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003027311,0.00008061668,0.00018813804,0.000052960473,0.000060999555,0.000026224481,0.000064702646,0.000056127374,0.0000038957346],"category_scores_gemma":[0.000011342448,0.000049700393,0.00004019875,0.000118633645,0.00002754587,0.0001055904,0.0000027020349,0.00015644482,1.905347e-7],"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":[0.000015392216,0.0000060815496,0.001920011,0.00006289914,0.00006721269,0.000001516322,0.0007876501,0.9953702,0.000068740585,0.00026377157,0.00018898843,0.0012475032],"study_design_scores_gemma":[0.000460111,0.000149273,0.017382845,0.00019826964,0.00006800184,0.000036101694,0.000892712,0.97541696,0.000030917858,0.0000146923585,0.005266326,0.00008380224],"about_ca_topic_score_codex":0.000020562145,"about_ca_topic_score_gemma":0.00005980874,"teacher_disagreement_score":0.19640198,"about_ca_system_score_codex":0.000016335292,"about_ca_system_score_gemma":0.000012753437,"threshold_uncertainty_score":0.20267232},"labels":[],"label_agreement":null},{"id":"W2395696481","doi":"10.5383/juspn.05.01.004","title":"Feedback Provision on Running Technique with a Smartphone","year":2013,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Winter Sports Injuries and Performance","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Smartphone application; Internet privacy; Human–computer interaction; Multimedia","score_opus":0.006704591064691164,"score_gpt":0.21985681409114216,"score_spread":0.213152223026451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395696481","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":[0.9836409,0.004770748,0.00651908,0.0008427266,0.00087603653,0.0010774042,0.0000015475802,0.00002711375,0.0022444609],"genre_scores_gemma":[0.99553096,0.00051135366,0.0008696455,0.00035220527,0.0017655217,0.000030088295,0.0000020169407,0.000029233199,0.0009089612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874824,0.000023151193,0.00054155214,0.00015571473,0.00027767787,0.00025363718],"domain_scores_gemma":[0.9986441,0.000039980907,0.00050951965,0.00019059586,0.00040207367,0.00021374058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003605911,0.00019003561,0.000536188,0.00012236902,0.00010714284,0.000092503215,0.000083319384,0.00013861958,0.00005465129],"category_scores_gemma":[0.000010242957,0.00011287815,0.00008834162,0.00012338505,0.00006269732,0.00019829623,0.00002587855,0.0005089399,0.000005693058],"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":[0.012206826,0.0015493939,0.5923059,0.0058097146,0.002141248,0.003693295,0.0095973965,0.017454624,0.011526052,0.0011524385,0.24681014,0.09575301],"study_design_scores_gemma":[0.018168598,0.07720945,0.45562217,0.06455301,0.000977148,0.078750916,0.010902939,0.03563883,0.0044197277,0.00021401428,0.25100753,0.0025356472],"about_ca_topic_score_codex":0.00013213567,"about_ca_topic_score_gemma":0.0000046516857,"teacher_disagreement_score":0.13668369,"about_ca_system_score_codex":0.000051480405,"about_ca_system_score_gemma":0.00006816759,"threshold_uncertainty_score":0.46030372},"labels":[],"label_agreement":null},{"id":"W2399221722","doi":"10.5383/juspn.05.02.003","title":"A Micro Simulated and Demand Driven Supply Chain Model To Estimate Regional Production and Consumption Relations","year":2014,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Supply chain; Production (economics); Consumption (sociology); Process (computing); Economic order quantity; Finished good; Industrial organization; Economics; Microeconomics; Point (geometry); Microsimulation; Order (exchange); Business; Computer science; Transport engineering; Marketing; Engineering","score_opus":0.022553741498156418,"score_gpt":0.22879296387264403,"score_spread":0.2062392223744876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399221722","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":[0.7927676,0.005073888,0.20127895,0.00016070087,0.00042737552,0.00021860476,0.0000067091582,0.0000307243,0.000035484234],"genre_scores_gemma":[0.9967517,0.0012510176,0.0013755736,0.00002843387,0.0004678186,0.0000026324346,0.00000589766,0.000021179014,0.00009571516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991907,0.00003622155,0.00037089814,0.00013205793,0.000108361826,0.0001617801],"domain_scores_gemma":[0.9994368,0.00007794598,0.000108592314,0.00007732835,0.0001341779,0.00016517258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027497276,0.00014364246,0.00027739326,0.000101523765,0.00011339071,0.00006190047,0.00003905825,0.00012655414,0.0000014485415],"category_scores_gemma":[0.000025533836,0.00012486894,0.000029564964,0.000059036538,0.000056637844,0.000117990014,0.000009216802,0.00021091741,5.714575e-7],"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":[0.000034564142,0.0000087992275,0.017637571,0.00012040894,0.00005583786,0.0000071365394,0.00055001955,0.9782226,0.0010463991,0.0003407026,0.001713875,0.00026205333],"study_design_scores_gemma":[0.00036897793,0.000116664996,0.012673258,0.00040436763,0.00008948649,0.00040529668,0.00003592591,0.98491675,0.000013814833,0.0001017466,0.000726135,0.00014757135],"about_ca_topic_score_codex":0.000010705677,"about_ca_topic_score_gemma":0.00005165746,"teacher_disagreement_score":0.20398417,"about_ca_system_score_codex":0.000029038694,"about_ca_system_score_gemma":0.00001119825,"threshold_uncertainty_score":0.50920075},"labels":[],"label_agreement":null},{"id":"W2402349153","doi":"10.5383/juspn.05.01.001","title":"Detecting Primary User Emulation Attacks in Cognitive Radio Networks via Physical Layer Network Coding","year":2013,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Foundation","keywords":"Emulation; Computer science; Cognitive radio; RSS; Physical layer; Computer network; Coding (social sciences); Linear network coding; Wireless; Real-time computing; Telecommunications","score_opus":0.012106734892490338,"score_gpt":0.23403224836084421,"score_spread":0.22192551346835387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402349153","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":[0.29143244,0.0061112167,0.6996873,0.0000096828035,0.0017426228,0.0006485862,0.000001190641,0.000063059466,0.0003038793],"genre_scores_gemma":[0.9936752,0.00063588074,0.00058643566,0.00003817461,0.004879937,0.000040904422,0.000008399049,0.000086652784,0.000048422964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977878,0.00019277808,0.0009843088,0.00023296887,0.00023922505,0.0005629522],"domain_scores_gemma":[0.9981541,0.0005832033,0.0005404927,0.00014256545,0.00039576384,0.0001838886],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005433482,0.00034306446,0.00079356035,0.00015971475,0.00014830372,0.0001735842,0.0001333824,0.00028114393,0.000009347404],"category_scores_gemma":[0.000043428023,0.00031657983,0.00013036576,0.0003899106,0.000039280174,0.00083158474,0.000044829754,0.0007741406,0.0000029370592],"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":[0.000035342822,0.000016612194,0.01045247,0.00011545815,0.000106188825,0.00003000869,0.00052183407,0.9820239,0.00037567943,0.000015237413,0.00060698355,0.005700315],"study_design_scores_gemma":[0.00095948006,0.00012965416,0.008349843,0.0014542555,0.00006136831,0.0003340361,0.000439518,0.9877859,0.000020503381,0.00003127943,0.0000977498,0.0003364502],"about_ca_topic_score_codex":0.00006390642,"about_ca_topic_score_gemma":0.000036672405,"teacher_disagreement_score":0.70224273,"about_ca_system_score_codex":0.00025442778,"about_ca_system_score_gemma":0.000022704537,"threshold_uncertainty_score":0.99992865},"labels":[],"label_agreement":null},{"id":"W2404433927","doi":"10.5383/juspn.05.02.004","title":"Privacy Management Solution in Ubiquitous Environments Using Percontrol","year":2014,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Bluetooth; Computer science; Identifier; Ubiquitous computing; Radio-frequency identification; Wireless; Wireless sensor network; Identification (biology); Computer network; Computer security; Human–computer interaction; Telecommunications","score_opus":0.010725482818747375,"score_gpt":0.215526953735342,"score_spread":0.20480147091659462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404433927","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":[0.19130327,0.003122099,0.80283153,0.0001381312,0.0020342793,0.00027746375,3.7540403e-7,0.000016816271,0.00027606002],"genre_scores_gemma":[0.99240625,0.0008376926,0.0053231483,0.00014935923,0.0011536265,0.0000066778916,8.3635496e-7,0.00002559359,0.00009679949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970746,0.00044761755,0.0009466991,0.00039002384,0.0005526142,0.0005884476],"domain_scores_gemma":[0.9983112,0.00019224205,0.00075290684,0.00044964472,0.00008470961,0.0002092675],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011306803,0.00028786005,0.00059499685,0.0003027002,0.00018420152,0.0002522032,0.0007255974,0.00020185331,0.0000019710837],"category_scores_gemma":[0.000022340584,0.00025167837,0.00013877153,0.00028673693,0.000062931314,0.0004997685,0.0002833046,0.00043375124,0.0000019995791],"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":[0.000033511824,0.00010415488,0.0016463745,0.000051209852,0.00007225531,0.00014669208,0.0004589554,0.9842973,0.00077517267,0.0027488903,0.00020559486,0.009459934],"study_design_scores_gemma":[0.0013656226,0.00026481925,0.003399999,0.0005147152,0.000040992374,0.00057102693,0.0001404119,0.98853904,0.00002746373,0.00006815048,0.0047922214,0.0002755392],"about_ca_topic_score_codex":0.00007945851,"about_ca_topic_score_gemma":0.000017027402,"teacher_disagreement_score":0.801103,"about_ca_system_score_codex":0.00023627793,"about_ca_system_score_gemma":0.000026012785,"threshold_uncertainty_score":0.99999356},"labels":[],"label_agreement":null},{"id":"W2408096433","doi":"10.5383/juspn.05.01.002","title":"Electromagnetic Energy and Data Transfer for a Neural Implant","year":2013,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Wireless power transfer; Baseband; Subthreshold conduction; Wireless; Computer science; Energy consumption; Electronic engineering; Telecommunications link; Energy (signal processing); Power (physics); Maximum power transfer theorem; Electrical engineering; Engineering; Telecommunications; CMOS; Transistor; Voltage; Physics","score_opus":0.01464472500685321,"score_gpt":0.21386916335287448,"score_spread":0.19922443834602127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2408096433","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":[0.81614983,0.071478404,0.108302034,0.00018406172,0.0031069666,0.0004598754,0.000033996945,0.00010154218,0.0001832928],"genre_scores_gemma":[0.9933422,0.0038726504,0.00043187704,0.00007595824,0.002098967,0.000027742328,0.000016707125,0.00005675909,0.00007713822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986242,0.00006156365,0.00056432036,0.00019651072,0.00014561068,0.0004077688],"domain_scores_gemma":[0.9989253,0.00035840843,0.000097185504,0.00025308933,0.00015809636,0.00020787015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028913328,0.00023172855,0.00046417137,0.000079408666,0.0000940673,0.00020721728,0.0002896238,0.00017557149,0.000005136679],"category_scores_gemma":[0.00001856281,0.00018847412,0.00005765531,0.000085377236,0.000045913355,0.00033016002,0.00004369975,0.00024408608,1.6436164e-7],"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":[0.00006780277,0.000037362726,0.0007336289,0.00056895457,0.0004924604,0.0000972311,0.0003283672,0.8617941,0.0053054458,0.0011654226,0.06990162,0.059507582],"study_design_scores_gemma":[0.0006842322,0.00051741675,0.00062835217,0.0002800393,0.00009330105,0.0025486685,0.00009094965,0.9847469,0.000031971744,0.00005677,0.010068953,0.0002524531],"about_ca_topic_score_codex":0.00014082863,"about_ca_topic_score_gemma":0.000104782244,"teacher_disagreement_score":0.17719238,"about_ca_system_score_codex":0.000024282414,"about_ca_system_score_gemma":0.000019553543,"threshold_uncertainty_score":0.7685752},"labels":[],"label_agreement":null},{"id":"W2735666015","doi":"10.5383/juspn.09.01.002","title":"The AREA Framework for Location-Based Smart Mobile Augmented Reality Applications","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Augmented reality; Computer science; Mobile device; Mobile computing; Mobile Web; Human–computer interaction; Mobile technology; Mixed reality; World Wide Web; Telecommunications","score_opus":0.031288957106261665,"score_gpt":0.3071268888842211,"score_spread":0.27583793177795946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735666015","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042313358,0.0027929966,0.9909517,0.0036539033,0.0007070905,0.0012764146,0.000014466011,0.000027747892,0.00015254717],"genre_scores_gemma":[0.99187875,0.00055995176,0.0052755764,0.00018822608,0.0010118699,0.0009527756,0.000006918236,0.000016711447,0.000109222005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998351,0.00011191175,0.00067549304,0.0002650696,0.00030313447,0.00029341297],"domain_scores_gemma":[0.9946572,0.0012446409,0.0015691281,0.0013036127,0.0010438347,0.00018156394],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0013964,0.0001656858,0.0003057961,0.000048977694,0.0022600542,0.0009601223,0.0014729695,0.00015940034,9.436338e-7],"category_scores_gemma":[0.00017647939,0.000115142924,0.00014031968,0.00014657795,0.00019011118,0.0002777565,0.00012592984,0.0003136684,0.0000013807403],"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":[0.00016944269,0.00052149745,0.004162645,0.00039776598,0.00063245307,0.000010914876,0.0008443043,0.3158967,0.00011739409,0.5290808,0.031550456,0.11661566],"study_design_scores_gemma":[0.000909213,0.0003854753,0.0048940443,0.0004988925,0.000110721885,0.00011105786,0.00049313233,0.8077888,0.000056899004,0.012099473,0.1723275,0.00032478545],"about_ca_topic_score_codex":0.00010918731,"about_ca_topic_score_gemma":0.00007697474,"teacher_disagreement_score":0.9914556,"about_ca_system_score_codex":0.00009652259,"about_ca_system_score_gemma":0.00022115579,"threshold_uncertainty_score":0.9990389},"labels":[],"label_agreement":null},{"id":"W2792417284","doi":"10.5383/juspn.10.01.003","title":"An Architectural Model for Fog Computing","year":2018,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski; Université du Québec à Chicoutimi","funders":"Université du Québec à Chicoutimi; Université du Québec à Rimouski","keywords":"Computer science; Geology; Environmental science; Computer graphics (images)","score_opus":0.023625956121370584,"score_gpt":0.27971137644653743,"score_spread":0.25608542032516685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792417284","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":[0.20473698,0.00096010725,0.78502464,0.0001170182,0.00890173,0.0001592352,2.769887e-7,0.000031350908,0.00006866603],"genre_scores_gemma":[0.9538896,0.000011673471,0.024288356,0.00020539125,0.02154286,0.000001507909,7.253561e-7,0.000016994989,0.00004290367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983372,0.00010575824,0.00060777407,0.0002594139,0.0002356271,0.000454205],"domain_scores_gemma":[0.9980828,0.00023905882,0.00054627896,0.00026020533,0.00064816343,0.00022345132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010558149,0.00019185084,0.00041150904,0.00012925723,0.00043877377,0.00043350627,0.0006632305,0.00011355036,2.1308148e-7],"category_scores_gemma":[0.00003108884,0.00014975473,0.00013872342,0.00015235264,0.00007013122,0.00038164257,0.00013129174,0.00026195913,6.875407e-7],"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":[0.00021362919,0.00015167467,0.0026703854,0.00026493135,0.0002599141,0.00007442439,0.021924669,0.6279551,0.001123575,0.0043233098,0.020247187,0.3207912],"study_design_scores_gemma":[0.0004711634,0.0008415485,0.00032823207,0.0002132442,0.000017464972,0.001129433,0.000082682185,0.99510324,0.000026620852,0.0005405718,0.0010583326,0.00018743944],"about_ca_topic_score_codex":0.000023226887,"about_ca_topic_score_gemma":0.0000059599674,"teacher_disagreement_score":0.7607363,"about_ca_system_score_codex":0.000038756385,"about_ca_system_score_gemma":0.00009743181,"threshold_uncertainty_score":0.6106821},"labels":[],"label_agreement":null},{"id":"W2895427262","doi":"10.5383/juspn.10.01.005","title":"Agent–based Modeling of Social Behavioral Challenges in Transportation","year":2018,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Psychology; Transport engineering; Engineering","score_opus":0.07532753955216039,"score_gpt":0.32332228394025325,"score_spread":0.24799474438809288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895427262","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":[0.97645193,0.002849298,0.018902745,0.00031233422,0.0008131327,0.00015151188,0.000007864192,0.000010771258,0.0005003949],"genre_scores_gemma":[0.9981867,0.00078327383,0.0001972089,0.000012808792,0.00078743533,0.0000021374747,0.0000063602474,0.0000074868212,0.000016608576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988724,0.00013558952,0.00049324724,0.00008687299,0.0002667042,0.00014520588],"domain_scores_gemma":[0.9990525,0.000045502828,0.0003772587,0.00003348953,0.0004336921,0.00005753467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007254293,0.000072798684,0.00023409587,0.000118946075,0.00016521857,0.00002558713,0.00007481557,0.00014079438,0.000009563977],"category_scores_gemma":[0.00000970318,0.00006868694,0.0000626821,0.0001359523,0.00008601834,0.00016486905,9.346767e-7,0.00012152605,1.5325232e-7],"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":[0.0002780737,0.00016911654,0.027008334,0.00012211277,0.000037866892,0.000034041375,0.130509,0.8331239,0.000053793206,0.0035755902,0.00017027195,0.004917857],"study_design_scores_gemma":[0.0051191514,0.0020087876,0.11749568,0.0022113572,0.0003997849,0.000017443534,0.17102095,0.6942845,0.000037617934,0.00027608805,0.0063374364,0.00079123146],"about_ca_topic_score_codex":0.0007614215,"about_ca_topic_score_gemma":0.0039762435,"teacher_disagreement_score":0.13883945,"about_ca_system_score_codex":0.00003145756,"about_ca_system_score_gemma":0.00010407407,"threshold_uncertainty_score":0.28009722},"labels":[],"label_agreement":null},{"id":"W2946439011","doi":"10.5383/juspn.11.01.003","title":"Practical Defense-in-depth Solution for Microservice Systems","year":2019,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Computer security","score_opus":0.021572261823583877,"score_gpt":0.2678738866598278,"score_spread":0.24630162483624393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946439011","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":[0.15188465,0.011431935,0.82173973,0.0008754292,0.012445077,0.0011296297,0.0000028783934,0.000041559146,0.00044912891],"genre_scores_gemma":[0.9950672,0.00075780344,0.0021407139,0.00016894101,0.0016973431,0.000015887405,0.0000011963112,0.000016371447,0.00013459042],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796927,0.00025097645,0.0007896688,0.0002856441,0.00031055268,0.0003938673],"domain_scores_gemma":[0.997861,0.00048839283,0.00073575985,0.0002637545,0.0005012844,0.0001497798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015115058,0.00018470024,0.0005047398,0.00016932594,0.00013969335,0.00038557703,0.0003178885,0.00025203673,0.0000025470843],"category_scores_gemma":[0.00004437312,0.00015422312,0.00013918665,0.000280814,0.000023550485,0.00079239224,0.000097762284,0.00043933437,0.0000063935204],"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":[0.0034296124,0.0015300509,0.028380848,0.00547109,0.0011150135,0.0008592841,0.010559839,0.5425688,0.013888844,0.21589506,0.11878688,0.05751469],"study_design_scores_gemma":[0.0013323711,0.0010350584,0.000935382,0.0007419872,0.000028692177,0.0025784757,0.00038516233,0.96117777,0.000031632604,0.00019001876,0.031308066,0.00025535922],"about_ca_topic_score_codex":0.00017276756,"about_ca_topic_score_gemma":0.00009700322,"teacher_disagreement_score":0.8431825,"about_ca_system_score_codex":0.00011049619,"about_ca_system_score_gemma":0.000111081696,"threshold_uncertainty_score":0.6289036},"labels":[],"label_agreement":null},{"id":"W2949485457","doi":"10.5383/juspn.11.02.003","title":"Optimizing Web Service Composition with Graphplan and Fuzzy Control","year":2019,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Composition (language); Service composition; Computer science; Control (management); Web service; Service (business); Fuzzy logic; World Wide Web; Artificial intelligence; Business; Marketing; Linguistics; Philosophy","score_opus":0.004276138728244515,"score_gpt":0.18561427200756667,"score_spread":0.18133813327932216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949485457","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":[0.91986835,0.009390695,0.06708731,0.0012570781,0.0012422088,0.00044067585,0.00000530417,0.000044853143,0.0006635064],"genre_scores_gemma":[0.9958054,0.00034174605,0.00174307,0.0015388903,0.0005399668,0.000003858526,0.0000021164828,0.000015121259,0.000009861347],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985133,0.0001559316,0.00042995313,0.00027194148,0.0003280596,0.00030086088],"domain_scores_gemma":[0.9983563,0.00022483716,0.000535418,0.00025465354,0.0004217827,0.00020703445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040208804,0.00022679238,0.00048978673,0.00016926673,0.00016317499,0.00035953018,0.00039924608,0.00011568021,0.0000020021216],"category_scores_gemma":[9.0628936e-7,0.00015562907,0.00006022512,0.0003210228,0.00002427837,0.0005390411,0.00008772088,0.0003311911,0.0000018437255],"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":[0.00237513,0.00042614946,0.122049674,0.0030890857,0.0023915302,0.0010443592,0.032162778,0.77230644,0.021864988,0.027068574,0.0010344541,0.014186857],"study_design_scores_gemma":[0.012290247,0.004720536,0.017609546,0.0047259447,0.00039911715,0.014387702,0.005231137,0.9299784,0.00016096895,0.00041910526,0.0087117925,0.0013655355],"about_ca_topic_score_codex":0.00013868051,"about_ca_topic_score_gemma":0.0001373512,"teacher_disagreement_score":0.15767196,"about_ca_system_score_codex":0.000017831984,"about_ca_system_score_gemma":0.00005843801,"threshold_uncertainty_score":0.63463694},"labels":[],"label_agreement":null},{"id":"W2950437283","doi":"10.5383/juspn.11.02.004","title":"The Multi-Agent System Solutions for Big Multi-sensor Data Management","year":2019,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data science; Distributed computing; Data mining","score_opus":0.05929860227270915,"score_gpt":0.2647331762428013,"score_spread":0.20543457397009213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950437283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049572256,0.01530459,0.963954,0.00033409326,0.014167916,0.001069947,0.000015694439,0.00006428611,0.00013227724],"genre_scores_gemma":[0.967221,0.0027480414,0.024774224,0.00011989045,0.0029056075,0.00004611186,0.000011678996,0.000055739292,0.0021176888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968763,0.00029737072,0.0010070271,0.00052862195,0.0004998106,0.0007908846],"domain_scores_gemma":[0.9961804,0.0006946968,0.0009722615,0.001418851,0.00050684955,0.00022691373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023859104,0.00029794784,0.00053789077,0.00013422495,0.0007751718,0.00065317185,0.0021565491,0.000169659,4.7010138e-7],"category_scores_gemma":[0.00003207424,0.0001968366,0.00018977567,0.00028806436,0.00007251024,0.0003166407,0.0008889744,0.00035555504,0.0000076119322],"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":[0.000059972033,0.00014490723,0.00053876225,0.00034851482,0.00049442536,0.000093075,0.00029874351,0.96003765,0.00006626979,0.016884208,0.007215906,0.013817583],"study_design_scores_gemma":[0.0014287035,0.00018165373,0.00041651234,0.0006201787,0.00007727155,0.000405311,0.001414636,0.9462311,0.000003177553,0.000002548964,0.04898459,0.00023427518],"about_ca_topic_score_codex":0.00004363389,"about_ca_topic_score_gemma":0.000059301485,"teacher_disagreement_score":0.96226376,"about_ca_system_score_codex":0.00015284352,"about_ca_system_score_gemma":0.000066170476,"threshold_uncertainty_score":0.8026764},"labels":[],"label_agreement":null},{"id":"W2952473555","doi":"10.5383/juspn.11.02.002","title":"Green Service Level Agreement Compliance for Optical WDM Networks","year":2019,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Service-level agreement; Wavelength-division multiplexing; Compliance (psychology); Service (business); Business; Telecommunications; Computer network; Computer science; Optoelectronics; Physics; Psychology; Quality of service; Marketing; Wavelength; Social psychology","score_opus":0.03619027904992409,"score_gpt":0.2523298703857852,"score_spread":0.2161395913358611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952473555","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":[0.1744927,0.02530505,0.7921463,0.000549262,0.0050132275,0.0013594177,0.000020970985,0.00021235684,0.0009006727],"genre_scores_gemma":[0.98582244,0.0017301452,0.009806918,0.00019681598,0.0020841185,0.000033693694,0.000006482525,0.00007527478,0.00024412258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803877,0.000025988205,0.00081205973,0.00023649432,0.0002709339,0.0006157633],"domain_scores_gemma":[0.99837124,0.00040091434,0.0002721175,0.0003063013,0.00045160414,0.000197843],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040573502,0.00033082097,0.0007650559,0.000086773834,0.00009476005,0.00009386401,0.00039308434,0.00034908715,0.000010976692],"category_scores_gemma":[0.00002679537,0.00027810314,0.00015369094,0.0002414665,0.000060542767,0.00023829435,0.00009809788,0.0006300113,0.000008176927],"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":[0.00008460751,0.000021577567,0.0010043369,0.00041310093,0.00019163665,0.000022298898,0.00006438572,0.98231524,0.00014821009,0.0015303888,0.0024554995,0.011748719],"study_design_scores_gemma":[0.001068366,0.00048588097,0.001158815,0.0009235202,0.0000761033,0.0003094589,0.0004618246,0.9849748,0.00001467987,0.0002630762,0.00987507,0.0003884144],"about_ca_topic_score_codex":0.000016136577,"about_ca_topic_score_gemma":0.000048593534,"teacher_disagreement_score":0.8113297,"about_ca_system_score_codex":0.00012133852,"about_ca_system_score_gemma":0.000020762225,"threshold_uncertainty_score":0.9999671},"labels":[],"label_agreement":null},{"id":"W3011864134","doi":"10.5383/juspn.12.02.003","title":"A Scalable Digital Infrastructure for Sustainable Energy Grid Enabled by Distributed Ledger Technology","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Distributed ledger; Scalability; Sustainable energy; Grid; Computer science; Ledger; Blockchain; Distributed computing; Environmental economics; Business; Database; Electrical engineering; Computer security; Engineering; Renewable energy; Finance; Geology; Economics","score_opus":0.003801615058983421,"score_gpt":0.17203958219049942,"score_spread":0.168237967131516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011864134","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":[0.08128444,0.030725868,0.8801372,0.0018863434,0.0034691873,0.00073248334,0.00015487052,0.0003450527,0.001264576],"genre_scores_gemma":[0.9961044,0.0007578235,0.00008463399,0.00012550005,0.0024582045,0.00003643064,0.000050888622,0.000058445898,0.00032366463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.998536,0.000018057064,0.000565969,0.00018908804,0.00017569201,0.000515177],"domain_scores_gemma":[0.9989605,0.00008074234,0.00021494536,0.00014055215,0.00037709414,0.00022616854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014097034,0.00026186407,0.00056207774,0.00012515788,0.00011857973,0.0002729794,0.0002537163,0.0003231376,0.000008655736],"category_scores_gemma":[0.000073129675,0.0002250601,0.00011395448,0.0003914071,0.000046231267,0.00036337995,0.00009413643,0.00035197553,5.663187e-7],"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":[0.00005096562,0.000010968317,0.00052088173,0.00024595644,0.00024731294,0.00007175744,0.000054036514,0.6197464,0.00020849172,0.0009519793,0.37713498,0.00075626094],"study_design_scores_gemma":[0.0010755766,0.00035854036,0.000060030587,0.00010635225,0.00007877886,0.00015902158,0.0014373548,0.1986809,0.00022736183,0.00014502292,0.7973834,0.0002876647],"about_ca_topic_score_codex":0.00001323004,"about_ca_topic_score_gemma":0.0000020202333,"teacher_disagreement_score":0.91481996,"about_ca_system_score_codex":0.00013517955,"about_ca_system_score_gemma":0.00003608429,"threshold_uncertainty_score":0.9177685},"labels":[],"label_agreement":null},{"id":"W3012985095","doi":"10.5383/juspn.07.01.005","title":"Multi-hop Wireless Network: A Comparative Study for Routing Protocols Using OMNET++ Simulator","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Computer network; Routing protocol; Ad hoc On-Demand Distance Vector Routing; Optimized Link State Routing Protocol; Link-state routing protocol; Destination-Sequenced Distance Vector routing; Wireless Routing Protocol; Dynamic Source Routing; Network simulation; Wireless ad hoc network; Distance-vector routing protocol; Interior gateway protocol; Network packet; Distributed computing; Wireless; Telecommunications","score_opus":0.07593900346058716,"score_gpt":0.3400410546709598,"score_spread":0.26410205121037267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012985095","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":[0.14637491,0.0010150771,0.8394855,0.000049644153,0.0015105064,0.011501049,0.000004021981,0.000046785768,0.000012464156],"genre_scores_gemma":[0.9866852,0.00003219502,0.008180783,0.00006719874,0.003959869,0.0009511492,3.982752e-7,0.000043220167,0.00007994332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99587864,0.0006025002,0.0015287088,0.00057679584,0.0005265352,0.00088682346],"domain_scores_gemma":[0.99487215,0.0012030014,0.0018818979,0.0005668225,0.0011150294,0.00036109262],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024068416,0.00044994793,0.0012540882,0.0001182282,0.00050271524,0.0005119226,0.000978225,0.00023057983,0.0000027315702],"category_scores_gemma":[0.000060014812,0.00029364225,0.00025951164,0.000383858,0.00008962243,0.0008505242,0.0003307566,0.00039047317,0.0000011595132],"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":[0.00045817555,0.00065056107,0.028308349,0.00014665931,0.00074207963,0.00015468948,0.004262175,0.94206786,0.0009706158,0.0016610151,0.0026664794,0.017911317],"study_design_scores_gemma":[0.0043162005,0.0017180819,0.0013992513,0.0018085771,0.000076502154,0.00034290354,0.0008123269,0.98764175,0.000021316315,0.00004649863,0.0013809602,0.0004356067],"about_ca_topic_score_codex":0.00004654774,"about_ca_topic_score_gemma":0.00006338591,"teacher_disagreement_score":0.84031034,"about_ca_system_score_codex":0.00019597326,"about_ca_system_score_gemma":0.00021470604,"threshold_uncertainty_score":0.99995154},"labels":[],"label_agreement":null},{"id":"W3013032741","doi":"10.5383/juspn.08.02.004","title":"Complex system modeling and platform implementation for financial risk management in energy markets","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Risk management; Nash equilibrium; Computer science; Government (linguistics); Game theory; System dynamics; General partnership; Financial modeling; Risk analysis (engineering); Finance; Business; Economics; Microeconomics","score_opus":0.01937903527095109,"score_gpt":0.24399595943327987,"score_spread":0.22461692416232878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013032741","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":[0.6478743,0.0061365473,0.34009188,0.00003322828,0.0037038974,0.0006339409,0.000022386515,0.000042968928,0.0014608334],"genre_scores_gemma":[0.99460995,0.0035416258,0.0006690666,0.000012954404,0.0010689826,0.000045418954,0.0000054547736,0.000028933493,0.00001759478],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987531,0.000031556105,0.0006159172,0.00014692133,0.000167457,0.00028508087],"domain_scores_gemma":[0.99922955,0.000052648662,0.0003598587,0.00018578288,0.000083348146,0.00008879804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006849949,0.00018434749,0.00037944515,0.00015616525,0.00027455852,0.00022645961,0.00017606918,0.00008670624,0.0000014906761],"category_scores_gemma":[0.000008879398,0.00017034955,0.00006722322,0.000036250032,0.00001828302,0.0002688503,0.00007762932,0.00012638565,1.05714854e-7],"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":[0.00007508556,0.000007502497,0.0018245876,0.00045259853,0.00015664313,0.000046486726,0.00013463496,0.9654076,0.0000073761075,0.003237944,0.0018451157,0.026804393],"study_design_scores_gemma":[0.0015686653,0.000083855586,0.0108906785,0.00038288106,0.000091669885,0.00006983739,0.0012915957,0.9807168,0.000003612239,0.000078172525,0.004647121,0.00017509267],"about_ca_topic_score_codex":0.00028372402,"about_ca_topic_score_gemma":0.0004263855,"teacher_disagreement_score":0.34673566,"about_ca_system_score_codex":0.00014662175,"about_ca_system_score_gemma":0.00000937196,"threshold_uncertainty_score":0.6946653},"labels":[],"label_agreement":null},{"id":"W3013134268","doi":"10.5383/juspn.07.01.001","title":"Performance Evaluation of Routing Protocols for Video Conference over MPLS VPN Network","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multiprotocol Label Switching; Computer network; Computer science; Routing protocol; Open Shortest Path First; Interior gateway protocol; Scalability; Border Gateway Protocol; Enhanced Interior Gateway Routing Protocol; Default gateway; Routing (electronic design automation); Link-state routing protocol; Quality of service; Operating system","score_opus":0.05362127779179093,"score_gpt":0.30082954484232693,"score_spread":0.247208267050536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013134268","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":[0.16600631,0.0027490403,0.8219433,0.00022165487,0.002168082,0.0065860837,0.000005955556,0.00003925604,0.00028033645],"genre_scores_gemma":[0.99430096,0.00022374303,0.0024145693,0.00008602035,0.0022980918,0.0006096916,6.3724536e-7,0.000019884255,0.00004640299],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997152,0.00027839004,0.0010747662,0.000299107,0.00071900396,0.00047674222],"domain_scores_gemma":[0.9951585,0.000829283,0.001616219,0.00036808595,0.0018708272,0.00015709527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004168634,0.00023571834,0.0006314546,0.000086492844,0.00019673756,0.00018012493,0.0005751022,0.0001616088,0.000008710772],"category_scores_gemma":[0.00019831475,0.00014979334,0.00017337046,0.0002505335,0.00006674762,0.0006980622,0.00012546907,0.00018324741,7.0580444e-7],"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":[0.00066230516,0.00018853875,0.10028484,0.0005704478,0.0005120414,0.000019316925,0.0013958266,0.32602036,0.00093650277,0.018237287,0.0244027,0.5267698],"study_design_scores_gemma":[0.0034747696,0.0015069642,0.018021764,0.0053466903,0.00011931358,0.00027688887,0.0000635912,0.965175,0.00010436686,0.0010781945,0.0044518295,0.0003806732],"about_ca_topic_score_codex":0.000015140873,"about_ca_topic_score_gemma":0.000011717064,"teacher_disagreement_score":0.82829463,"about_ca_system_score_codex":0.00009256003,"about_ca_system_score_gemma":0.00030128902,"threshold_uncertainty_score":0.6108395},"labels":[],"label_agreement":null},{"id":"W3013229757","doi":"10.5383/juspn.06.01.005","title":"End-to-End Safety Solution for Children Enabled by a Wearable Sensor Vest","year":2015,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Tekes","keywords":"VEST; Wearable computer; Computer science; Cloud computing; Human–computer interaction; Multimedia; Computer security; Embedded system; Operating system","score_opus":0.011413794159475658,"score_gpt":0.21404964253396577,"score_spread":0.2026358483744901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013229757","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":[0.1458681,0.028066969,0.8197441,0.00043397694,0.0036546506,0.0011304052,0.00010460733,0.00026693448,0.0007302215],"genre_scores_gemma":[0.9967748,0.0010440995,0.0006821701,0.00006313802,0.0010967908,0.000016675618,0.000014290458,0.00004000843,0.0002680231],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987461,0.000043879754,0.00052754674,0.00012932738,0.00020806277,0.0003451036],"domain_scores_gemma":[0.9990764,0.00008689118,0.00017242336,0.00013382606,0.0003318151,0.00019861363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005581321,0.00018575613,0.00041536422,0.00012585969,0.0001246923,0.000106316125,0.00015096305,0.00022645903,0.0000051648826],"category_scores_gemma":[0.00008403477,0.00015606402,0.00008631366,0.00016905762,0.000033302127,0.00016928706,0.000027810225,0.00023479747,0.0000028265322],"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":[0.00022874329,0.00003802351,0.002151033,0.00015798243,0.0003074586,0.00001528251,0.00084969454,0.8058409,0.0016528992,0.0003137923,0.17853028,0.009913882],"study_design_scores_gemma":[0.007678682,0.0027044802,0.0025055378,0.0015358495,0.00038722408,0.0021780217,0.00439079,0.7678886,0.0035754193,0.0002811122,0.2053951,0.001479153],"about_ca_topic_score_codex":0.00007539581,"about_ca_topic_score_gemma":0.000019323028,"teacher_disagreement_score":0.8509067,"about_ca_system_score_codex":0.00013909799,"about_ca_system_score_gemma":0.00004417807,"threshold_uncertainty_score":0.63641065},"labels":[],"label_agreement":null},{"id":"W3013262564","doi":"10.5383/juspn.06.01.004","title":"LOS/NLOS Identification Based on Stable Distribution Feature Extraction and SVM Classifier for UWB On-Body Communications","year":2015,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Non-line-of-sight propagation; Support vector machine; Computer science; Classifier (UML); Wireless; Feature extraction; Context (archaeology); Artificial intelligence; Identification (biology); Pattern recognition (psychology); Machine learning; Telecommunications; Geography","score_opus":0.029044277565832877,"score_gpt":0.26839277918578497,"score_spread":0.23934850161995208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013262564","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":[0.20946756,0.019183801,0.7571745,0.0019349612,0.007689916,0.0022733482,0.00042199052,0.00021598721,0.0016379482],"genre_scores_gemma":[0.9973203,0.00076063146,0.00020916536,0.000043189128,0.0012932017,0.000047640286,0.00014718935,0.000038865423,0.00013983305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987109,0.00012829757,0.0004907988,0.00016087976,0.0002636939,0.0002454616],"domain_scores_gemma":[0.9981586,0.00043571662,0.00036329398,0.00036935267,0.00046457862,0.00020846352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008009436,0.00020612625,0.00034396356,0.00010103966,0.00021098938,0.00021175221,0.00017938606,0.00027885893,0.0000013999472],"category_scores_gemma":[0.00007362891,0.00018235561,0.00008053762,0.00014787122,0.000055502842,0.00027144916,0.000020075553,0.00053314253,0.0000010849454],"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":[0.0003036088,0.00010428301,0.0010129391,0.00021064386,0.00013348398,0.000010160007,0.00022295765,0.8941996,0.0007032047,0.0013769722,0.09723244,0.0044897287],"study_design_scores_gemma":[0.00096413045,0.00036605942,0.003518701,0.0005898303,0.000094318086,0.000094315044,0.00035747595,0.97009814,0.00008254698,0.00008039518,0.023549244,0.00020485099],"about_ca_topic_score_codex":0.000013774241,"about_ca_topic_score_gemma":0.000027551028,"teacher_disagreement_score":0.7878527,"about_ca_system_score_codex":0.00024412274,"about_ca_system_score_gemma":0.00004939008,"threshold_uncertainty_score":0.7436246},"labels":[],"label_agreement":null},{"id":"W3013321416","doi":"10.5383/juspn.08.01.004","title":"Experimental Derivation of the Thermal Coefficients and Performance Observations of Heated Platforms in 3D Printing","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"3D printing; Rapid prototyping; Thermal; Product (mathematics); Fiber; Mechanical engineering; Process engineering; Manufacturing engineering; Range (aeronautics); Computer science; Materials science; Engineering; Composite material; Mathematics; Physics","score_opus":0.017463517587500865,"score_gpt":0.20567636481457333,"score_spread":0.18821284722707246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013321416","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":[0.99702233,0.00080856524,0.0017595063,0.000016422506,0.0002496878,0.00010331524,0.0000023166365,0.000013893542,0.000023990704],"genre_scores_gemma":[0.9996204,0.00017819036,0.00012079852,0.0000026116825,0.000059708807,0.000002789609,2.8545273e-7,0.0000087786575,0.0000064716346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993126,0.000015156749,0.00039391383,0.000057302786,0.000106444146,0.00011458068],"domain_scores_gemma":[0.99948174,0.00009572806,0.00024528382,0.000084871775,0.00007511265,0.00001729071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021775943,0.000085816886,0.00020098528,0.00006718665,0.000045750883,0.00001010527,0.00010365929,0.000073962336,0.0000015368228],"category_scores_gemma":[0.000034410168,0.00004706664,0.000029802675,0.00008698775,0.00007559454,0.00011555364,0.000055858047,0.00012545838,4.0684338e-8],"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":[0.00007060861,0.00006011472,0.63649344,0.0003648876,0.00011899967,0.000003390312,0.0019592862,0.20643874,0.12479034,0.00021341574,0.0000610651,0.029425733],"study_design_scores_gemma":[0.0007711094,0.00021444439,0.8002814,0.0021510788,0.000014661188,0.00004494851,0.0011032283,0.04074134,0.15446308,0.000012146362,0.00007021152,0.00013237367],"about_ca_topic_score_codex":0.000014694352,"about_ca_topic_score_gemma":0.0000033318736,"teacher_disagreement_score":0.1656974,"about_ca_system_score_codex":0.000028812225,"about_ca_system_score_gemma":0.000009238139,"threshold_uncertainty_score":0.19193217},"labels":[],"label_agreement":null},{"id":"W3013331711","doi":"10.5383/juspn.08.01.002","title":"Ambient Technology in Vehicles: The Risks and Benefits","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Emerging technologies; Work (physics); Computer security; Computer science; Internet privacy; Engineering; Artificial intelligence","score_opus":0.023710852751873786,"score_gpt":0.24105069331347093,"score_spread":0.21733984056159714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013331711","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":[0.94008875,0.057262905,0.0005225451,0.00050076144,0.0012077832,0.00022853057,0.000002609394,0.000024286393,0.00016184224],"genre_scores_gemma":[0.98960996,0.009328374,0.000038129787,0.00003130911,0.0009302206,0.000009844087,4.1627715e-7,0.000030321311,0.000021429008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874544,0.00005808483,0.00050175784,0.00014244753,0.00018255852,0.0003696851],"domain_scores_gemma":[0.9989686,0.00010816777,0.00033074652,0.00035937538,0.00011541919,0.0001176826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072775467,0.00019682664,0.00044160185,0.0001313432,0.00028712567,0.00026684717,0.0003727214,0.00026218183,0.0000016242436],"category_scores_gemma":[0.00004730512,0.00013659729,0.00006303691,0.00009222773,0.00014849797,0.00018659377,0.000110612425,0.0007257001,0.0000010051099],"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":[0.00001749991,0.000011557771,0.0279055,0.000059299313,0.00009212935,0.00013673861,0.00026998372,0.9570212,0.00011005238,0.00041423587,0.0010313276,0.0129304705],"study_design_scores_gemma":[0.0015256852,0.00031564088,0.118816,0.001605598,0.0001002978,0.002824758,0.0012334718,0.86399776,0.000073204814,0.0003192252,0.008785112,0.00040324242],"about_ca_topic_score_codex":0.00011811855,"about_ca_topic_score_gemma":0.0002707654,"teacher_disagreement_score":0.09302344,"about_ca_system_score_codex":0.00005859555,"about_ca_system_score_gemma":0.00001874956,"threshold_uncertainty_score":0.5570276},"labels":[],"label_agreement":null},{"id":"W3013432555","doi":"10.5383/juspn.07.02.001","title":"Cyber-Physical Spatial Decision Support System for Road Traffic Management","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Scope (computer science); Computer science; Traffic congestion; Population; Autonomy; Control (management); Architecture; Transport engineering; Computer security; Business; Engineering; Geography","score_opus":0.0071745359267153365,"score_gpt":0.2167653856212889,"score_spread":0.20959084969457356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013432555","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":[0.08033046,0.00081522705,0.91261846,0.000043287364,0.0037955092,0.0006527675,0.0000144400265,0.0006008295,0.00112903],"genre_scores_gemma":[0.9967172,0.00075324246,0.0005162278,0.00001775338,0.0018111723,0.000045211942,0.0000016447459,0.000037690454,0.00009982121],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986946,0.000032936034,0.0005709662,0.000157144,0.00026602508,0.0002783513],"domain_scores_gemma":[0.9992616,0.000112448804,0.00019079148,0.00015979294,0.00012584637,0.00014951499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004210853,0.00020188319,0.00041767638,0.00016283822,0.000078657766,0.00007602813,0.00017723397,0.00011242208,0.0000029591977],"category_scores_gemma":[0.0000067327287,0.00013280631,0.00018034823,0.00007494457,0.00002695382,0.0001742651,0.000034057033,0.00011586712,0.0000032861312],"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":[0.00019506557,0.00006447535,0.000058053407,0.00064242305,0.00043978728,0.00011913497,0.00021783315,0.07565878,0.00021966711,0.0017000095,0.101277955,0.8194068],"study_design_scores_gemma":[0.005819112,0.0018937426,0.0022163736,0.004301346,0.0005995842,0.0008849988,0.0014794808,0.78964573,0.00017825716,0.00004817315,0.19210193,0.00083125266],"about_ca_topic_score_codex":0.0000048509824,"about_ca_topic_score_gemma":0.000008187604,"teacher_disagreement_score":0.9163868,"about_ca_system_score_codex":0.00013186585,"about_ca_system_score_gemma":0.000010032288,"threshold_uncertainty_score":0.54156846},"labels":[],"label_agreement":null},{"id":"W3013471690","doi":"10.5383/juspn.09.01.001","title":"Safety-Critical Mobile Systems – The RESCUER Interaction Evaluation Approach","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministério da Ciência, Tecnologia e Inovação; Conselho Nacional de Desenvolvimento Científico e Tecnológico; European Commission","keywords":"Usability; Computer science; Crowdsourcing; Event (particle physics); Process (computing); System usability scale; Scale (ratio); Mobile apps; Human–computer interaction; Heuristic evaluation; World Wide Web","score_opus":0.13417380359720815,"score_gpt":0.422296033054589,"score_spread":0.28812222945738086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013471690","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":[0.8893719,0.020274531,0.05888585,0.0029880889,0.022054767,0.0016623585,0.000018610224,0.000049072154,0.004694851],"genre_scores_gemma":[0.9973208,0.00036588556,0.00006698612,0.000049676608,0.0016284687,0.000041099658,0.000001375154,0.0000136793615,0.0005120308],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99588364,0.0008957609,0.0012470516,0.0003036637,0.0014018087,0.00026804794],"domain_scores_gemma":[0.99449676,0.0010360625,0.0015372186,0.00086730596,0.0019195582,0.00014311851],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0104882475,0.00018045004,0.0005175378,0.00019343445,0.0012165856,0.0015477008,0.0010223105,0.00030649483,0.000035528145],"category_scores_gemma":[0.002166637,0.000098835495,0.00018232112,0.00013576458,0.0003068781,0.00075281283,0.0001626024,0.000746574,0.000012307135],"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":[0.0015712312,0.0008577542,0.17453893,0.00016931359,0.00067254825,0.00026325416,0.006542448,0.42661977,0.00052603433,0.033399496,0.13968569,0.21515355],"study_design_scores_gemma":[0.0025517186,0.0010702766,0.14367144,0.0007719865,0.0005190893,0.007240434,0.04674576,0.6742736,0.00001189962,0.0012384384,0.121328205,0.0005771673],"about_ca_topic_score_codex":0.00010451156,"about_ca_topic_score_gemma":0.000021333279,"teacher_disagreement_score":0.24765381,"about_ca_system_score_codex":0.00009838415,"about_ca_system_score_gemma":0.000095363124,"threshold_uncertainty_score":0.9994888},"labels":[],"label_agreement":null},{"id":"W3013485901","doi":"10.5383/juspn.08.02.003","title":"From Relational Database to Big Data: Converting Relational to graph database, MOOC database as example","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Graph database; Computer science; Relational database; Database; Database design; Database schema; Database model; View; Graph; Relational database management system; Semi-structured model; Wait-for graph; Relational model; Information retrieval; Theoretical computer science","score_opus":0.09163477766572739,"score_gpt":0.29044669702098885,"score_spread":0.19881191935526146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013485901","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":[0.07553454,0.0021715467,0.9129477,0.0012011286,0.0065264697,0.00040153813,0.00096104434,0.000032917076,0.00022312831],"genre_scores_gemma":[0.9459405,0.00034087262,0.042011663,0.0011667786,0.009526536,0.000018389503,0.00067619147,0.000045625056,0.00027342624],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99661076,0.00030381628,0.0009933076,0.0007889088,0.0008279257,0.00047530467],"domain_scores_gemma":[0.99449,0.0008699629,0.0010845775,0.0023402278,0.000513866,0.0007013409],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002714664,0.00032243007,0.00055205286,0.00028842557,0.0011346037,0.00079313596,0.002476904,0.00013201084,0.000022940689],"category_scores_gemma":[0.0006658866,0.0002799619,0.0001078088,0.0002849946,0.00010022914,0.0030389514,0.0019688853,0.00060751976,0.000030596293],"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":[0.0020906045,0.00097253296,0.058847558,0.00047762445,0.0028581389,0.0054821367,0.012682837,0.081705555,0.015925493,0.4435967,0.26477283,0.110588],"study_design_scores_gemma":[0.010164084,0.0024537558,0.057285126,0.0110324025,0.00076443853,0.0055006924,0.0036637296,0.62460357,0.0008259021,0.017535796,0.2615869,0.0045836265],"about_ca_topic_score_codex":0.0017753706,"about_ca_topic_score_gemma":0.00016421029,"teacher_disagreement_score":0.87093604,"about_ca_system_score_codex":0.000044381333,"about_ca_system_score_gemma":0.00022647799,"threshold_uncertainty_score":0.99996525},"labels":[],"label_agreement":null},{"id":"W3013519205","doi":"10.5383/juspn.08.01.003","title":"A Model transformation from computing independent model to platform independent model in model driven architecture","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Class diagram; Unified Modeling Language; Computer science; Transformation (genetics); Activity diagram; Set (abstract data type); Dimension (graph theory); Model transformation; Class (philosophy); Software engineering; Programming language; Artificial intelligence; Software; Mathematics; Consistency (knowledge bases)","score_opus":0.027363461669739974,"score_gpt":0.26124207400418814,"score_spread":0.23387861233444818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013519205","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":[0.3814839,0.00038422376,0.6165954,0.00053394405,0.00034475164,0.00035262314,0.000017922846,0.00002450314,0.00026269897],"genre_scores_gemma":[0.9751392,0.00014732452,0.023336494,0.000812708,0.00048333092,0.000013261384,0.0000067622054,0.000034495086,0.000026421949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965361,0.000078810976,0.0012203074,0.00055740564,0.00094071607,0.00066670595],"domain_scores_gemma":[0.99714947,0.00010581543,0.0010748496,0.00080003456,0.0004156023,0.00045424455],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000811001,0.0004645611,0.00083675125,0.0004217111,0.0005896837,0.0009042831,0.0020730842,0.00037188674,6.2442666e-7],"category_scores_gemma":[0.000011896605,0.00038041317,0.00022179722,0.00016775451,0.000037735674,0.0013584377,0.0005556622,0.0011227011,0.0000013191318],"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":[0.00012987014,0.00006794863,0.0003422382,0.00007638794,0.0000725825,0.000033584805,0.031025339,0.9594419,0.00046330463,0.0021480198,0.000046103843,0.006152732],"study_design_scores_gemma":[0.0014148384,0.000147048,0.00038052586,0.0007866355,0.000041974647,0.00013892335,0.0005762501,0.9890072,0.000044051743,0.0070419884,0.000014087412,0.00040652696],"about_ca_topic_score_codex":0.00077207776,"about_ca_topic_score_gemma":0.0027956602,"teacher_disagreement_score":0.5936553,"about_ca_system_score_codex":0.0001769747,"about_ca_system_score_gemma":0.00032640327,"threshold_uncertainty_score":0.99986476},"labels":[],"label_agreement":null},{"id":"W3013524315","doi":"10.5383/juspn.08.01.001","title":"Software Quality Assessment Algorithm Based on Fuzzy Logic","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Software quality; Fuzzy logic; Data mining; Verification and validation; Software metric; Software; Quality (philosophy); Software quality control; Metric (unit); Software measurement; Algorithm; Software development; Software engineering; Artificial intelligence; Programming language; Mathematics; Statistics; Engineering","score_opus":0.04507118796917641,"score_gpt":0.3327389602104978,"score_spread":0.2876677722413214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013524315","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008867372,0.0012641273,0.9857931,0.00061013066,0.0030006564,0.00020572527,0.000004784119,0.00005558715,0.00019851697],"genre_scores_gemma":[0.96257687,0.00016267947,0.035408124,0.00017670577,0.0015380845,0.000011193715,0.0000010498163,0.000020606796,0.00010468148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976599,0.00024332947,0.0005634039,0.00029961014,0.0008272963,0.00040645196],"domain_scores_gemma":[0.9961765,0.0013195956,0.0007451091,0.0009168568,0.00055721164,0.00028475455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023962308,0.00021421131,0.0005015685,0.00014815816,0.00048945507,0.0010293814,0.0013270533,0.00016263913,0.000003874756],"category_scores_gemma":[0.00069893495,0.00016374861,0.00015829482,0.00009682256,0.00007303377,0.0004288632,0.00023251875,0.0006607194,0.0000026358011],"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":[0.00010240542,0.00048959476,0.14058848,0.00055829936,0.00037464764,0.0019743878,0.0005161719,0.43796355,0.00009036768,0.007907034,0.012655866,0.3967792],"study_design_scores_gemma":[0.0017018499,0.0015979559,0.30719775,0.00094664283,0.000025316862,0.00044847917,0.000081723854,0.68356985,0.000017510853,0.0005910496,0.0033128778,0.00050897914],"about_ca_topic_score_codex":0.000101324425,"about_ca_topic_score_gemma":0.0000042403335,"teacher_disagreement_score":0.9537095,"about_ca_system_score_codex":0.00015015058,"about_ca_system_score_gemma":0.00021366165,"threshold_uncertainty_score":0.9926349},"labels":[],"label_agreement":null},{"id":"W3013547980","doi":"10.5383/juspn.07.01.004","title":"Content-based Filter Publish Subscribe Model for Real-time WSN applications","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"King Fahd University of Petroleum and Minerals","keywords":"Computer science; Computer network; Quality of service; Publication; Distributed computing; Wireless sensor network; Middleware (distributed applications); Network packet; Energy consumption; Porting; Efficient energy use; Decoupling (probability); Throughput; Real-time computing; Wireless; Telecommunications; Operating system; Engineering","score_opus":0.039103999484897456,"score_gpt":0.24683318232309143,"score_spread":0.20772918283819397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013547980","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006374945,0.0010698279,0.9857053,0.005127089,0.0006177714,0.00078991026,0.00003731491,0.00014602367,0.0001317802],"genre_scores_gemma":[0.93204546,0.00041239292,0.062396035,0.0007537278,0.001697841,0.00037107436,0.0000044047038,0.000051715517,0.0022673793],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997848,0.000079309844,0.00077061635,0.00038700862,0.0003742477,0.00054082496],"domain_scores_gemma":[0.9966692,0.00061395107,0.0006402963,0.00063472684,0.0011604222,0.00028142493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009875515,0.00025304305,0.00055451086,0.00025015813,0.00019462612,0.0004329725,0.0012781799,0.00023617741,0.0000030127628],"category_scores_gemma":[0.00012236921,0.00016592487,0.00019593579,0.00032003172,0.00008160381,0.0006765928,0.00019584408,0.00019197984,0.0000053909653],"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":[0.00042805483,0.0003791009,0.0030444078,0.0002887161,0.0006166052,0.000096776304,0.0008382532,0.20322715,0.022993611,0.05109483,0.5045138,0.21247867],"study_design_scores_gemma":[0.0017853872,0.0007080939,0.00044865228,0.00063726655,0.00006865971,0.00024707025,0.00011572975,0.97265345,0.00032194055,0.001452688,0.021047726,0.0005133666],"about_ca_topic_score_codex":0.00002179148,"about_ca_topic_score_gemma":0.00002006934,"teacher_disagreement_score":0.9256705,"about_ca_system_score_codex":0.00012223814,"about_ca_system_score_gemma":0.00016498289,"threshold_uncertainty_score":0.676622},"labels":[],"label_agreement":null},{"id":"W3013630590","doi":"10.5383/juspn.06.01.002","title":"Support Vector Machines Regression for Channel Estimation in MIMO LTE systems","year":2015,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fading; MIMO; Multipath propagation; Orthogonal frequency-division multiplexing; Computer science; MIMO-OFDM; Algorithm; Channel (broadcasting); Minimum mean square error; Additive white Gaussian noise; Electronic engineering; Estimator; Mathematics; Decoding methods; Telecommunications; Engineering; Statistics","score_opus":0.02029150891796313,"score_gpt":0.2581720741123905,"score_spread":0.23788056519442738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013630590","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":[0.040198725,0.025150383,0.9230822,0.000059896567,0.009862229,0.0012629606,0.000024670944,0.0000912774,0.00026769025],"genre_scores_gemma":[0.99651736,0.00046120922,0.0011147388,0.000009080371,0.0015856136,0.000059613983,0.000020578316,0.00006300347,0.00016881383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828625,0.00009434486,0.0009393398,0.00015597219,0.0002224989,0.00030157279],"domain_scores_gemma":[0.9985684,0.0001453486,0.00049052085,0.00014865412,0.00044299115,0.00020407872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088262063,0.0002470723,0.0006220599,0.00022951174,0.000059119335,0.00010760523,0.00012884231,0.00021996521,9.3598214e-7],"category_scores_gemma":[0.00009474747,0.00019816132,0.00007825798,0.00018306744,0.000018839371,0.00045338983,0.00001912033,0.00023459489,0.0000011562158],"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":[0.00007824641,0.000015400941,0.00040948048,0.0004505914,0.000042695225,0.000027385811,0.0008234321,0.99289954,0.00010789523,0.00007423812,0.0043381327,0.0007329837],"study_design_scores_gemma":[0.001281563,0.00030051224,0.000104376384,0.0012814094,0.000034084136,0.00055356545,0.00077464693,0.99396956,0.00001888794,0.000032048076,0.0014382923,0.00021104624],"about_ca_topic_score_codex":0.000064352265,"about_ca_topic_score_gemma":0.000031785254,"teacher_disagreement_score":0.9563186,"about_ca_system_score_codex":0.00021257906,"about_ca_system_score_gemma":0.00005312047,"threshold_uncertainty_score":0.8080784},"labels":[],"label_agreement":null},{"id":"W3013687893","doi":"10.5383/juspn.08.02.001","title":"Bankruptcy prediction and risk scoring using Hybrid Discriminant Neural Networks","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Linear discriminant analysis; Artificial neural network; Bankruptcy; Discriminant; Portfolio; Reliability (semiconductor); Multiple discriminant analysis; Computer science; Artificial intelligence; Machine learning; Bankruptcy prediction; Econometrics; Data mining; Actuarial science; Business; Finance; Economics","score_opus":0.02281904233818544,"score_gpt":0.2311638341336785,"score_spread":0.20834479179549306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013687893","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":[0.96956366,0.0054696733,0.018698022,0.00006981306,0.005680522,0.00023495943,0.000011992619,0.000025859561,0.0002455159],"genre_scores_gemma":[0.984171,0.0022479668,0.000023409735,0.00004596841,0.0134425005,0.0000043117243,0.000006542534,0.000032483575,0.000025835367],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99835783,0.000037390022,0.0006758944,0.00027107316,0.0002828887,0.00037491324],"domain_scores_gemma":[0.99743867,0.000040816103,0.0018582128,0.0002660783,0.00034179885,0.000054414562],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00075286726,0.00026772823,0.00049673714,0.00014868041,0.0014569507,0.0015094394,0.00024234965,0.00013601201,0.000004917992],"category_scores_gemma":[0.0001257202,0.00021198316,0.00013437997,0.00006965154,0.00013724079,0.0020110325,0.00021369536,0.00046969025,4.985813e-7],"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":[0.0003453179,0.0000814968,0.80189425,0.0004623235,0.00019869575,0.00024560207,0.00011799291,0.15487471,0.00010200573,0.0009772292,0.002236684,0.038463704],"study_design_scores_gemma":[0.00067541795,0.00007906432,0.21668385,0.00067840016,0.00034332898,0.00029715354,0.00024449095,0.7794804,0.0000014022701,0.00008937236,0.0012347961,0.00019234033],"about_ca_topic_score_codex":0.002860945,"about_ca_topic_score_gemma":0.00015109927,"teacher_disagreement_score":0.62460566,"about_ca_system_score_codex":0.000042323918,"about_ca_system_score_gemma":0.000017781813,"threshold_uncertainty_score":0.999843},"labels":[],"label_agreement":null},{"id":"W3013752062","doi":"10.5383/juspn.06.01.001","title":"Personal Mobile Grids: Ubiquitous Grid Environments For Personal Users","year":2015,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Plan for Science, Technology and Innovation","keywords":"Computer science; Distributed computing; Grid; Grid computing; Scheduling (production processes); Heuristic; Benchmark (surveying); Mobile device; Engineering; Operating system; Artificial intelligence","score_opus":0.03574278460480261,"score_gpt":0.25734008732048286,"score_spread":0.22159730271568023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013752062","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":[0.38104716,0.026104435,0.5730257,0.0006230246,0.016719555,0.0019987295,0.00010222081,0.00009395861,0.00028523715],"genre_scores_gemma":[0.99270034,0.00038410042,0.00052862155,0.00024813425,0.00548427,0.00011414912,0.000007619928,0.000041004478,0.0004917669],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967034,0.00034041514,0.0009628302,0.0004960233,0.00089370116,0.0006036578],"domain_scores_gemma":[0.99690264,0.0005573627,0.0010723529,0.00025436186,0.00055782316,0.0006554267],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017752146,0.00038876312,0.0008444688,0.00022125109,0.00026389366,0.00051158783,0.0006200048,0.0002686595,0.000008955778],"category_scores_gemma":[0.000090257396,0.000333381,0.00036307756,0.00021389419,0.000108005646,0.00112786,0.00018759943,0.00046375688,0.000011168488],"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":[0.0027189925,0.0025472734,0.037072256,0.0015963379,0.0046510217,0.0019858547,0.118751235,0.023489624,0.0049018813,0.0008214981,0.40417582,0.39728823],"study_design_scores_gemma":[0.010448027,0.007851636,0.0021694768,0.0017983519,0.0003455042,0.014871784,0.020171696,0.5260914,0.00024254416,0.00018977774,0.41384894,0.0019708634],"about_ca_topic_score_codex":0.0001017913,"about_ca_topic_score_gemma":0.000026543472,"teacher_disagreement_score":0.6116532,"about_ca_system_score_codex":0.00030674165,"about_ca_system_score_gemma":0.0002980797,"threshold_uncertainty_score":0.99991184},"labels":[],"label_agreement":null},{"id":"W3089405809","doi":"10.5383/juspn.14.01.002","title":"An approach of Complex Infrastructure Networks in Ecological Landscape","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Regione Autonoma della Sardegna","keywords":"Ecological network; Geography; Ecology; Environmental resource management; Landscape connectivity; Computer science; Environmental planning; Environmental science; Ecosystem; Sociology; Biology; Biological dispersal","score_opus":0.016652881853789457,"score_gpt":0.2304338842669365,"score_spread":0.21378100241314704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089405809","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":[0.9884798,0.00040741672,0.009531706,0.00024589497,0.0002573484,0.00017129982,0.0000029515813,0.0000065493055,0.0008970678],"genre_scores_gemma":[0.9982251,0.00018476509,0.0004958876,0.00045278203,0.0006109716,0.0000036753013,0.000006730278,0.000009006394,0.00001108373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987042,0.00016852803,0.0005872584,0.0001655778,0.00019394477,0.00018050692],"domain_scores_gemma":[0.99914527,0.00007691446,0.00047132417,0.000098019285,0.000046541092,0.00016193083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029967746,0.00013064433,0.00037764368,0.000036326775,0.00006319162,0.00005115593,0.0001968721,0.00015201535,0.00020623786],"category_scores_gemma":[0.000023396473,0.00009723002,0.00006995766,0.00022532648,0.000072636816,0.0002688552,0.000057403926,0.00036977712,9.855789e-7],"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":[0.000091278824,0.00006967613,0.291271,0.000016588645,0.000017936638,0.000014171871,0.0004625455,0.6998899,0.0003291199,0.00003725963,0.006226972,0.0015735663],"study_design_scores_gemma":[0.00036308265,0.00042920298,0.4176071,0.000034132387,0.000015230895,0.0001421018,0.0011939538,0.5784923,0.000001128551,0.000009609511,0.0016250698,0.0000871026],"about_ca_topic_score_codex":0.00014639135,"about_ca_topic_score_gemma":0.00004509959,"teacher_disagreement_score":0.1263361,"about_ca_system_score_codex":0.000043437023,"about_ca_system_score_gemma":0.000014674839,"threshold_uncertainty_score":0.3964925},"labels":[],"label_agreement":null},{"id":"W3089550448","doi":"10.5383/juspn.14.01.003","title":"DWPT vs OFDM Under a Noisy Industrial Channel","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Orthogonal frequency-division multiplexing; Channel (broadcasting); Mathematics; Computer science; Telecommunications","score_opus":0.04887321874001553,"score_gpt":0.2306491630763765,"score_spread":0.18177594433636096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089550448","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":[0.1482881,0.008863074,0.78498083,0.008927391,0.04757312,0.00046538655,9.359011e-7,0.00010990406,0.00079127424],"genre_scores_gemma":[0.96158046,0.00016539004,0.00033458945,0.0013049179,0.036539484,0.000001970215,6.7916216e-7,0.000019203957,0.00005330074],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979954,0.00018535073,0.0007209448,0.00027786306,0.00039754316,0.0004229242],"domain_scores_gemma":[0.9982418,0.00021136552,0.00064660213,0.00018952478,0.00031467565,0.0003960533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006595879,0.00022740124,0.0005710518,0.00009815303,0.0002215169,0.00044338818,0.000663406,0.00023020037,0.000001867117],"category_scores_gemma":[0.00006113217,0.00018156196,0.0001699739,0.00037291128,0.000039460654,0.00042015678,0.00026802396,0.0006780902,0.000005363261],"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":[0.0007271678,0.0002858384,0.005588506,0.0004518183,0.0010576162,0.0017604285,0.022779426,0.2201537,0.00073471916,0.004212446,0.68045086,0.061797444],"study_design_scores_gemma":[0.0027963002,0.0025391781,0.0011043225,0.0009948937,0.00010057024,0.0022427298,0.0010920826,0.923479,0.00008696604,0.00036086253,0.064413756,0.00078931113],"about_ca_topic_score_codex":0.000045519897,"about_ca_topic_score_gemma":0.0000014517235,"teacher_disagreement_score":0.8132924,"about_ca_system_score_codex":0.00005002454,"about_ca_system_score_gemma":0.00015967422,"threshold_uncertainty_score":0.74038815},"labels":[],"label_agreement":null},{"id":"W3090148937","doi":"10.5383/juspn.14.01.001","title":"IOT ANALYSIS AND MANAGEMENT SYSTEM FOR IMPROVING WORK PERFORMANCE WITH AN IOT OPEN SOFTWARE IN SMART BUILDINGS","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Wireless Sensor Networks and IoT","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Internet of Things; Work (physics); Computer science; Building automation; Software; Architectural engineering; Embedded system; Engineering; Operating system","score_opus":0.012055345360555242,"score_gpt":0.20417655686075145,"score_spread":0.1921212115001962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090148937","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":[0.909967,0.0045779357,0.08416284,0.00005092875,0.00038492063,0.000748842,0.0000061030523,0.000047297523,0.00005414522],"genre_scores_gemma":[0.9930638,0.0006560142,0.0052934457,0.000050837094,0.0008286302,0.000032115146,0.000003857173,0.000053203476,0.000018117686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843156,0.000053289386,0.0006596227,0.00027599878,0.00019766686,0.00038188545],"domain_scores_gemma":[0.9990355,0.000087837936,0.0003054238,0.00015826212,0.0001384184,0.00027459973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049697544,0.00027353436,0.0008208938,0.00018310943,0.0001411291,0.00038212462,0.00029607612,0.00013571486,0.0000015477784],"category_scores_gemma":[0.0000059030845,0.0002159281,0.00008577455,0.00060352974,0.000028558272,0.00022611837,0.00008648028,0.00030834362,1.7041961e-7],"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":[0.0003774553,0.000015344482,0.038848724,0.0017647039,0.0006414821,0.00008180111,0.0005602284,0.9375881,0.000027377486,0.00003604233,0.00024106698,0.019817702],"study_design_scores_gemma":[0.0018130091,0.0009945141,0.018019293,0.0016775803,0.000747264,0.0001527093,0.0019822754,0.972434,0.000025737254,0.0000010267345,0.0016976928,0.00045492157],"about_ca_topic_score_codex":0.00008961779,"about_ca_topic_score_gemma":0.00010019801,"teacher_disagreement_score":0.08309679,"about_ca_system_score_codex":0.00009078957,"about_ca_system_score_gemma":0.00001516463,"threshold_uncertainty_score":0.8805292},"labels":[],"label_agreement":null},{"id":"W3090393046","doi":"10.5383/juspn.14.01.004","title":"CLASSIFICATION OF LOGICAL VULNERABILITY BASED ON GROUP ATTACK METHOD","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Research in Systems and Signal Processing","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Group (periodic table); Computer science; Computer security; Chemistry","score_opus":0.06841061980070537,"score_gpt":0.32419497914557943,"score_spread":0.2557843593448741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090393046","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":[0.07293598,0.0038774207,0.921425,0.0002160327,0.0005401581,0.00025494542,0.000007417511,0.000032530366,0.0007104982],"genre_scores_gemma":[0.9969204,0.00014257482,0.001734844,0.00006355149,0.0011032682,0.0000058858095,0.0000018050395,0.000022359916,0.000005318751],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819404,0.00028608623,0.00075469265,0.00015931927,0.00038840537,0.00021744143],"domain_scores_gemma":[0.9985145,0.0005052716,0.0003235687,0.00012091159,0.00029243,0.00024334755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010924195,0.00016307428,0.00054193096,0.00006279281,0.000068923204,0.00005481572,0.00015796324,0.00015792265,0.000009949708],"category_scores_gemma":[0.00014730169,0.00011769442,0.00012478844,0.00019514158,0.00005368853,0.00014007122,0.000017038097,0.00054574676,6.946483e-7],"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":[0.00013690381,0.00003118821,0.0012405785,0.0007246563,0.000046737685,0.000023949262,0.00016654666,0.9815111,0.007528367,0.00018244998,0.00085584534,0.007551633],"study_design_scores_gemma":[0.0004798256,0.0006164577,0.001573462,0.00043494673,0.000019607864,0.000045635097,0.00036272008,0.99301535,0.00014106496,0.00002722536,0.0031555227,0.00012817245],"about_ca_topic_score_codex":0.000005073096,"about_ca_topic_score_gemma":9.623316e-7,"teacher_disagreement_score":0.9239844,"about_ca_system_score_codex":0.0000572522,"about_ca_system_score_gemma":0.000030269483,"threshold_uncertainty_score":0.47994393},"labels":[],"label_agreement":null},{"id":"W3091749894","doi":"10.5383/juspn.14.02.003","title":"Problems of Quantitative Estimation of the TPP’ ACS TP Intelligence Level","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Technology Assessment and Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Russian Science Foundation","keywords":"Estimation; Computer science; Statistics; Mathematics; Engineering; Systems engineering","score_opus":0.04229064465993186,"score_gpt":0.2521039277043573,"score_spread":0.20981328304442542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091749894","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":[0.31595764,0.00805479,0.673695,0.0005108594,0.0010524171,0.00040963868,0.000008686201,0.000030302057,0.00028066937],"genre_scores_gemma":[0.9981577,0.00083203294,0.0008756386,0.00001771189,0.00009010435,0.0000036621134,5.621233e-7,0.000010414079,0.000012188332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991109,0.000038679344,0.00052210473,0.000064147775,0.00015951927,0.00010466381],"domain_scores_gemma":[0.99924296,0.00007994578,0.00040988237,0.00009128025,0.00014127302,0.000034645902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023536029,0.00009941141,0.00029754348,0.00005099306,0.00003226815,0.000014590447,0.0001972554,0.00008741052,0.0000024259352],"category_scores_gemma":[0.000034825393,0.00006810673,0.00006670161,0.00018283183,0.000062675375,0.00010967367,0.00005008492,0.00022431291,2.985518e-7],"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":[0.000015100608,0.000018465593,0.0007795261,0.00054409803,0.00017035275,0.0000031449263,0.0014363473,0.9853537,0.0010187085,0.0049732104,0.0012467889,0.00444053],"study_design_scores_gemma":[0.0003749691,0.0009046983,0.0036992044,0.0013972528,0.00016198146,0.00004776607,0.0041506416,0.98454344,0.002976007,0.00052339456,0.0010357343,0.00018490359],"about_ca_topic_score_codex":0.000015666143,"about_ca_topic_score_gemma":0.000011067865,"teacher_disagreement_score":0.6822001,"about_ca_system_score_codex":0.000019140305,"about_ca_system_score_gemma":0.000016969281,"threshold_uncertainty_score":0.2777312},"labels":[],"label_agreement":null},{"id":"W3136740025","doi":"10.5383/juspn.15.02.004","title":"Towards smart manufacturing: Implementation and benefits","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Big data; Production (economics); Internet of Things; Quality (philosophy); Volume (thermodynamics); Data science; Risk analysis (engineering); Data mining; Computer security; Business","score_opus":0.01918503194965799,"score_gpt":0.23656246796258212,"score_spread":0.21737743601292414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136740025","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":[0.9729364,0.013629359,0.0053990325,0.00014332823,0.0021154261,0.00013236086,0.000022012056,0.00003473026,0.005587337],"genre_scores_gemma":[0.9968013,0.0024185493,0.0000901998,0.000034480057,0.0005825592,0.0000033220679,0.000006619838,0.000017270564,0.000045702353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913025,0.00002355513,0.00044375795,0.00007225368,0.0001664116,0.00016378977],"domain_scores_gemma":[0.99952894,0.000044290224,0.00010429454,0.0000663097,0.00013519201,0.00012099372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017157514,0.00011969566,0.00022419626,0.00005712776,0.00005585034,0.00020229063,0.00005042629,0.000103814535,0.000021950329],"category_scores_gemma":[0.0000043423315,0.00010857136,0.000047495665,0.00005689387,0.000015699918,0.00036900592,0.000016360525,0.00021808635,7.4379113e-7],"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":[0.000044777407,0.000049839247,0.010435675,0.0013896086,0.00082461257,0.00033053182,0.003131712,0.61561775,0.00044230992,0.0029492048,0.018249664,0.3465343],"study_design_scores_gemma":[0.014694786,0.0021440343,0.22446375,0.007468954,0.0010991454,0.043409705,0.09605889,0.094581604,0.054269608,0.001256081,0.45638236,0.0041710944],"about_ca_topic_score_codex":0.00001189117,"about_ca_topic_score_gemma":0.000018988261,"teacher_disagreement_score":0.52103615,"about_ca_system_score_codex":0.00003884396,"about_ca_system_score_gemma":0.000028250126,"threshold_uncertainty_score":0.44274116},"labels":[],"label_agreement":null},{"id":"W3136751090","doi":"10.5383/juspn.15.02.003","title":"EMERGING TECHNOLOGIES AND APPLICATIONS FOR SMART CITIES","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Smart city; Software deployment; Internet of Things; Computer science; Computer security; Corporate governance; Business; The Internet; Telecommunications; World Wide Web","score_opus":0.01439587093022906,"score_gpt":0.24243576975036368,"score_spread":0.22803989882013462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136751090","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":[0.018734133,0.037078656,0.9382956,0.000928963,0.0044846986,0.00020682267,4.769529e-7,0.00006033978,0.00021029942],"genre_scores_gemma":[0.9705602,0.0035981725,0.01616782,0.00019759734,0.009005035,0.00005231507,0.00000213824,0.000024304347,0.00039241384],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990859,0.000037791564,0.00036338778,0.00017366439,0.00011912215,0.0002201247],"domain_scores_gemma":[0.99882144,0.00026725943,0.0002804377,0.0001684382,0.00040638683,0.0000560603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003928804,0.000109756445,0.00027964328,0.00008919431,0.00029361655,0.0003163418,0.00023686855,0.00009571121,1.5592275e-7],"category_scores_gemma":[0.00004015376,0.00009193694,0.000069901034,0.00018181701,0.000045572484,0.000214805,0.0001769763,0.0001774614,1.8397941e-7],"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":[0.000036638237,0.00011012153,0.014091556,0.0010657897,0.0004688224,0.00020960541,0.0045698886,0.0069830734,0.0010544374,0.04889281,0.046785142,0.8757321],"study_design_scores_gemma":[0.0016124235,0.00066022127,0.0022212313,0.0013177146,0.00013319789,0.006475643,0.01072284,0.33352864,0.0006340723,0.010319937,0.6315573,0.0008168183],"about_ca_topic_score_codex":0.000007723099,"about_ca_topic_score_gemma":0.000003150675,"teacher_disagreement_score":0.9518261,"about_ca_system_score_codex":0.000019632444,"about_ca_system_score_gemma":0.000066465596,"threshold_uncertainty_score":0.37490797},"labels":[],"label_agreement":null},{"id":"W3136781297","doi":"10.5383/juspn.15.01.003","title":"Context-based Reasoning through Fuzzy Logic for Edge Intelligence","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Edge computing; Enhanced Data Rates for GSM Evolution; Cloud computing; Context (archaeology); Distributed computing; Controller (irrigation); Inference; Computational intelligence; Artificial intelligence; Fuzzy logic; Gateway (web page); Default gateway; Process (computing); Edge device; Machine learning; Computer network; Operating system","score_opus":0.037193952862485884,"score_gpt":0.27767679572936893,"score_spread":0.24048284286688304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136781297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061211116,0.023579985,0.95327336,0.0005948794,0.015663983,0.00018436066,5.239612e-7,0.000029904597,0.0005519105],"genre_scores_gemma":[0.96137816,0.00043404338,0.026278561,0.0011201132,0.010601529,0.000008987747,0.0000025855045,0.000023755985,0.00015229118],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981,0.00017345692,0.0007242289,0.00031003804,0.0002609901,0.0004312789],"domain_scores_gemma":[0.9972833,0.00067003496,0.0006330765,0.000280455,0.0009844825,0.00014867364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009147198,0.00021154944,0.0005350344,0.00006614173,0.00031913706,0.00046354518,0.00050023745,0.00015658338,0.0000011304132],"category_scores_gemma":[0.00017748572,0.00017346893,0.00022758846,0.00029021132,0.000049812304,0.00037721757,0.00013952973,0.00034454506,0.0000015389985],"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":[0.00046394378,0.00069384585,0.0062445193,0.0019097842,0.0010195404,0.0031050683,0.01849144,0.22478324,0.0013130909,0.17667928,0.13596752,0.42932874],"study_design_scores_gemma":[0.0014565376,0.0013075036,0.00032303215,0.0028859903,0.000105500825,0.00341227,0.0023995766,0.89817,0.0011472845,0.0050810655,0.0829369,0.0007743797],"about_ca_topic_score_codex":0.000026684367,"about_ca_topic_score_gemma":0.000005929433,"teacher_disagreement_score":0.955257,"about_ca_system_score_codex":0.000066848705,"about_ca_system_score_gemma":0.00026301795,"threshold_uncertainty_score":0.7073858},"labels":[],"label_agreement":null},{"id":"W3137263534","doi":"10.5383/juspn.15.01.004","title":"Contribution to Multi-Energy Flow Management for Building Energy Hub","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Energy Efficiency and Management","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Renewable energy; Fossil fuel; Environmental science; Global warming; Natural resource economics; Energy development; Primary energy; Renewable fuels; Environmental impact of the energy industry; Climate change mitigation; Environmental engineering; Environmental protection; Waste management; Climate change; Energy policy; Engineering; Ecology; Economics","score_opus":0.012728543210754784,"score_gpt":0.24628148188917817,"score_spread":0.2335529386784234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137263534","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":[0.0052749678,0.01139701,0.97765887,0.00041246662,0.0038035035,0.00018032193,0.000008553563,0.000030951076,0.0012333759],"genre_scores_gemma":[0.9848341,0.0025651895,0.006469395,0.0009714942,0.00218801,0.0000787605,0.00002250485,0.000043832708,0.0028267235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99786854,0.00017159469,0.0007915342,0.0003355206,0.00032598185,0.0005068535],"domain_scores_gemma":[0.9981252,0.00016928729,0.00040698133,0.00024692484,0.0007981188,0.00025352152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062523986,0.00026124145,0.0005554846,0.00018775897,0.00028201943,0.00018134435,0.00022359438,0.00016473749,0.000016231941],"category_scores_gemma":[0.0000670665,0.0002293753,0.00023863466,0.0003016265,0.000026027912,0.0001478343,0.00014322384,0.00012706222,6.784237e-7],"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":[0.00012305807,0.00011862126,0.000022612398,0.000089058674,0.00036434788,0.00023368151,0.00009480268,0.694256,0.00053514587,0.2732829,0.004879914,0.025999842],"study_design_scores_gemma":[0.0024381687,0.00048166525,0.00014198903,0.0007157408,0.00025440042,0.0003077516,0.0008583853,0.2141544,0.0010723484,0.0006054039,0.77854943,0.00042033373],"about_ca_topic_score_codex":0.00028336237,"about_ca_topic_score_gemma":0.00046162462,"teacher_disagreement_score":0.9795591,"about_ca_system_score_codex":0.00014803553,"about_ca_system_score_gemma":0.00004060425,"threshold_uncertainty_score":0.9353653},"labels":[],"label_agreement":null},{"id":"W3137292260","doi":"10.5383/juspn.15.02.002","title":"Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence**","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Landslide; Computer science; Warning system; Early warning system; Wireless sensor network; Scale (ratio); Novelty; Variety (cybernetics); Enhanced Data Rates for GSM Evolution; Artificial neural network; Artificial intelligence; Machine learning; Data science; Cartography; Geography; Engineering; Telecommunications; Computer network","score_opus":0.01202827704186465,"score_gpt":0.2230691084193758,"score_spread":0.21104083137751115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137292260","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":[0.9512666,0.0064362367,0.039597437,0.00013432703,0.00095534296,0.00014003665,0.000002521155,0.00002044912,0.0014470333],"genre_scores_gemma":[0.9978421,0.0005779329,0.00048362484,0.000033810105,0.00094779994,0.0000013072572,0.000001498018,0.000020182672,0.00009178028],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983667,0.00014828437,0.0005795926,0.00024168714,0.0003461207,0.0003176282],"domain_scores_gemma":[0.9989965,0.00012142495,0.00043754734,0.000119128366,0.000106282656,0.00021914058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006604489,0.00019514462,0.00046460298,0.00004203215,0.00030201167,0.00027325316,0.00011817628,0.00016929893,0.000025825175],"category_scores_gemma":[0.000021973465,0.00012432209,0.00007667296,0.00020181693,0.00011440329,0.00018262834,0.00013745876,0.00043285263,0.0000036110202],"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":[0.0006666734,0.00018441,0.26771113,0.00071721704,0.00086767005,0.0045452327,0.013287128,0.5092823,0.0011559388,0.003135157,0.0014705808,0.19697654],"study_design_scores_gemma":[0.002787817,0.0050792587,0.1348589,0.011280228,0.001132402,0.051489986,0.058048986,0.7175181,0.0011268803,0.00045950492,0.013761662,0.0024562872],"about_ca_topic_score_codex":0.00030726238,"about_ca_topic_score_gemma":0.00008639921,"teacher_disagreement_score":0.20823576,"about_ca_system_score_codex":0.00008830253,"about_ca_system_score_gemma":0.000043918135,"threshold_uncertainty_score":0.50697076},"labels":[],"label_agreement":null},{"id":"W3138322787","doi":"10.5383/juspn.15.02.001","title":"AI’S Contribution to Ubiquitous Systems and Pervasive Networks Security – Reinforcement Learning vs Recurrent Networks","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforcement learning; Computer science; Ubiquitous computing; Artificial intelligence; Network security; Computer security; State (computer science); Machine learning; Human–computer interaction","score_opus":0.009325254450105633,"score_gpt":0.2354385287060501,"score_spread":0.22611327425594446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138322787","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":[0.068266205,0.07266989,0.8419139,0.0012661724,0.014384172,0.0011832853,0.0000045124193,0.00013609568,0.00017577362],"genre_scores_gemma":[0.97764283,0.014999137,0.00013708114,0.0008566627,0.0060481476,0.000054554705,0.000021785543,0.000046868114,0.00019292264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938709,0.0012133529,0.001917955,0.0009020405,0.00094467663,0.0011510592],"domain_scores_gemma":[0.99402434,0.0005410414,0.0015311188,0.0006203222,0.00237108,0.00091210665],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0025821987,0.0006611654,0.0014228111,0.00030183257,0.0010406388,0.0016359556,0.0006672625,0.0006677447,0.00001448368],"category_scores_gemma":[0.00024558775,0.00060372544,0.00033532336,0.0009892501,0.000112957154,0.0010632755,0.00071976223,0.0020629424,0.0000042975594],"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":[0.00041347183,0.00009797603,0.000804854,0.00018168107,0.00029226628,0.00041415155,0.0014494089,0.97115266,0.00004617839,0.0066574668,0.009662761,0.008827117],"study_design_scores_gemma":[0.0013738679,0.0024623394,0.00045538376,0.0018706302,0.0001401305,0.0035862855,0.00068783556,0.9384588,0.000032044893,0.00011456922,0.050148778,0.0006693639],"about_ca_topic_score_codex":0.00024122707,"about_ca_topic_score_gemma":0.00015665469,"teacher_disagreement_score":0.9093766,"about_ca_system_score_codex":0.0003894086,"about_ca_system_score_gemma":0.00024064978,"threshold_uncertainty_score":0.9996414},"labels":[],"label_agreement":null},{"id":"W3138432582","doi":"10.5383/juspn.15.01.001","title":"VLC-based Data Transfer and Energy Harvesting Mobile System","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visible light communication; Computer science; Data transmission; Software portability; Energy harvesting; Real-time computing; Transmission (telecommunications); Efficient energy use; Computer hardware; Embedded system; Energy (signal processing); Telecommunications; Electrical engineering; Engineering; Light-emitting diode","score_opus":0.020655194530362603,"score_gpt":0.21926167896073737,"score_spread":0.19860648443037476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138432582","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":[0.32036927,0.30100295,0.37442434,0.00025477092,0.0019606915,0.000205518,0.000057803056,0.00044722608,0.001277443],"genre_scores_gemma":[0.9943188,0.004393804,0.0008913207,0.000021240781,0.0002886638,0.000009580976,0.000010993572,0.000029830298,0.000035789733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882823,0.00010306864,0.00054659595,0.00015344241,0.00016361519,0.00020506117],"domain_scores_gemma":[0.99869573,0.0003572493,0.00008910146,0.00052805763,0.00021901746,0.00011084974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035767182,0.00015986041,0.0004246759,0.000072337665,0.00010070635,0.00017787085,0.0003557645,0.00018241986,0.00000267646],"category_scores_gemma":[0.000046819674,0.00013873869,0.00004505271,0.0001567869,0.0000659307,0.0002188805,0.000114314025,0.0003428615,3.2786903e-7],"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":[0.00004943167,0.00010199778,0.0020421324,0.0025028216,0.000652018,0.0006667718,0.00039651786,0.82635987,0.0055541974,0.011424721,0.0027674283,0.14748211],"study_design_scores_gemma":[0.0005657437,0.0001328513,0.00017544243,0.0013863734,0.000074038144,0.0010742894,0.002457922,0.9743402,0.00070145086,0.000009643091,0.018829606,0.0002524175],"about_ca_topic_score_codex":0.000033345746,"about_ca_topic_score_gemma":0.000042249823,"teacher_disagreement_score":0.6739495,"about_ca_system_score_codex":0.00004727218,"about_ca_system_score_gemma":0.000043817792,"threshold_uncertainty_score":0.56575996},"labels":[],"label_agreement":null},{"id":"W3138507019","doi":"10.5383/juspn.15.01.005","title":"An Enhanced Deep Learning Model to Network Attack Detection, by using Parameter Tuning, Hidden Markov Model and Neural Network","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Artificial intelligence; Computer science; Deep learning; Artificial neural network; Generalization; Machine learning; Model selection; Hidden Markov model; Generalization error; Network model; Variance (accounting); Convergence (economics); Deep neural networks; Mathematics","score_opus":0.019926387121602253,"score_gpt":0.25749451760114533,"score_spread":0.2375681304795431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138507019","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":[0.3371319,0.0066990172,0.6546628,0.000069677524,0.0012038809,0.00015916648,8.533204e-7,0.000038737715,0.000033984506],"genre_scores_gemma":[0.97223896,0.0012107173,0.023210814,0.00055743544,0.0026293173,0.000009207564,0.0000027232043,0.000041382107,0.00009944665],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966926,0.00059509143,0.0009165332,0.00059611857,0.000455339,0.00074430153],"domain_scores_gemma":[0.9974436,0.00024600854,0.00071442866,0.00038146036,0.00066919136,0.00054529315],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00110459,0.00037117582,0.0007037483,0.00010591274,0.00082274317,0.00085603504,0.00041653973,0.00032206555,0.0000040548794],"category_scores_gemma":[0.000062765015,0.00035126577,0.00015186543,0.00060192915,0.000056287372,0.0010655602,0.00028818584,0.0009325678,5.2066827e-7],"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":[0.00008344014,0.00002624031,0.0001927196,0.000027544727,0.00006422968,0.000033635544,0.00077614683,0.9314386,0.0026146101,0.00004428797,0.0010541979,0.06364432],"study_design_scores_gemma":[0.00043410424,0.0005574179,0.00006149539,0.0002740238,0.00006021094,0.00097039895,0.00016605106,0.99625903,0.00008890341,0.0002741496,0.00046408852,0.00039010288],"about_ca_topic_score_codex":0.000037430655,"about_ca_topic_score_gemma":0.00015392296,"teacher_disagreement_score":0.6351071,"about_ca_system_score_codex":0.000101190955,"about_ca_system_score_gemma":0.00008413053,"threshold_uncertainty_score":0.99989396},"labels":[],"label_agreement":null},{"id":"W3138836727","doi":"10.5383/juspn.15.02.005","title":"Unbounded Spatial Data Stream Query Processing using Spatial Semijoins","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Spatial query; Computer science; Spatial analysis; Spatial database; Object-based spatial database; Data stream mining; Data mining; Focus (optics); Query optimization; Object (grammar); Web search query; Sargable; Information retrieval; Geography; Artificial intelligence; Remote sensing","score_opus":0.04769116251962889,"score_gpt":0.27910525443777806,"score_spread":0.23141409191814916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138836727","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":[0.01716415,0.0075687454,0.9714512,0.00025045866,0.0031456354,0.00014132683,0.000022443586,0.000028948132,0.00022706334],"genre_scores_gemma":[0.98234504,0.0008302098,0.011279412,0.00017384104,0.0051245005,0.000001429596,0.000047947557,0.000024460816,0.00017317792],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977862,0.00018922098,0.00070995174,0.0004347243,0.0005103602,0.00036954664],"domain_scores_gemma":[0.9978255,0.00009616514,0.00073882204,0.0007052997,0.00045500352,0.00017917651],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008417428,0.00022111634,0.0004807434,0.00011685208,0.00029500507,0.0014307869,0.001101355,0.00011423096,0.0000066830007],"category_scores_gemma":[0.000058811154,0.00018737986,0.00007850742,0.00031165793,0.000050667193,0.0018247754,0.001023059,0.00034922457,0.0000010381256],"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":[0.00010852663,0.0005879879,0.0096472,0.0010310813,0.000878254,0.0051767817,0.0018925002,0.054623734,0.001498083,0.002350212,0.017910004,0.9042956],"study_design_scores_gemma":[0.0006539025,0.00013047253,0.00083752867,0.0007190821,0.00009439966,0.0014593786,0.00045039094,0.98530036,0.000043782613,0.00008805135,0.009952097,0.00027056673],"about_ca_topic_score_codex":0.0006585444,"about_ca_topic_score_gemma":0.00031742247,"teacher_disagreement_score":0.9651809,"about_ca_system_score_codex":0.00006194769,"about_ca_system_score_gemma":0.0003834621,"threshold_uncertainty_score":0.99960583},"labels":[],"label_agreement":null},{"id":"W3139224746","doi":"10.5383/juspn.15.01.002","title":"Multistage Arabic and Turkish Text Compression via Characters Encoding and 7-Zip","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lossless compression; Computer science; Unicode; Decoding methods; Byte; String (physics); Encoding (memory); Substring; Data compression; Speech recognition; Arithmetic; Algorithm; Artificial intelligence; Programming language; Data structure; Mathematics","score_opus":0.010972321794472703,"score_gpt":0.22537197065596018,"score_spread":0.2143996488614875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139224746","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":[0.44911194,0.061818305,0.484876,0.00049634086,0.0032491519,0.0002520292,0.000011150329,0.00003694921,0.00014811954],"genre_scores_gemma":[0.99032474,0.005513771,0.002967113,0.00017057674,0.00089446246,0.000002570864,0.0000040835903,0.000012856643,0.000109846485],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983819,0.00019407047,0.0005223073,0.00033594173,0.00029235214,0.0002734427],"domain_scores_gemma":[0.9984268,0.00027053783,0.00049392536,0.00025442085,0.00027721538,0.00027708447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047863598,0.0002037915,0.00047527262,0.000088424174,0.0003036888,0.00058667496,0.00025175468,0.00013989683,0.0000034457032],"category_scores_gemma":[0.0000313977,0.00015383291,0.00006122481,0.00013621227,0.000062864296,0.0008100445,0.0003997522,0.000385417,5.183427e-7],"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":[0.00027872415,0.00046116172,0.038273297,0.0013780342,0.00057489355,0.0061475006,0.010395041,0.00794371,0.059466727,0.0045459694,0.012405879,0.8581291],"study_design_scores_gemma":[0.002625409,0.00058415317,0.051691204,0.0033840567,0.00008873747,0.013403163,0.0012069173,0.8976652,0.00049070065,0.00024848024,0.027843578,0.00076841196],"about_ca_topic_score_codex":0.00005840327,"about_ca_topic_score_gemma":0.0000069925704,"teacher_disagreement_score":0.88972145,"about_ca_system_score_codex":0.000026164396,"about_ca_system_score_gemma":0.000047591675,"threshold_uncertainty_score":0.6273124},"labels":[],"label_agreement":null},{"id":"W3198715244","doi":"","title":"Low-Cost IoT and LPWAN-Based Flood Forecast and Monitoring System","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"LPWAN; Flood myth; Internet of Things; Environmental science; Computer science; Flood forecasting; Remote sensing; Meteorology; Computer security; Geology; Geography","score_opus":0.021334546407896345,"score_gpt":0.2345734951541475,"score_spread":0.21323894874625116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198715244","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":[0.99136525,0.0049206107,0.0017754083,0.00019288629,0.0014233085,0.00018811044,0.000005478581,0.00004250972,0.000086407024],"genre_scores_gemma":[0.99776655,0.0004305556,0.0008193405,0.000014882145,0.00087750365,0.000009562363,7.2155905e-7,0.000022002201,0.00005889907],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983537,0.00015645934,0.0005362536,0.00028300463,0.00033759564,0.00033295082],"domain_scores_gemma":[0.99894524,0.00019911453,0.00036707125,0.00021951913,0.00007877352,0.00019028275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066299905,0.00021716602,0.0004599871,0.000058753627,0.00023513404,0.00024154382,0.0001625763,0.00020705689,0.000004186465],"category_scores_gemma":[0.00006666858,0.00017730675,0.000062753716,0.00015523264,0.00016864395,0.0001568197,0.00021794792,0.00036030827,0.0000016536276],"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":[0.00017181023,0.0001653426,0.8681755,0.0014328088,0.00026141232,0.0017057434,0.0018272826,0.06102404,0.014739571,0.00017150187,0.0015042757,0.048820715],"study_design_scores_gemma":[0.0116520515,0.0032705807,0.63203543,0.022137914,0.0010880738,0.023849083,0.060544334,0.118765414,0.10382249,0.00035255562,0.018674223,0.0038078595],"about_ca_topic_score_codex":0.00016709827,"about_ca_topic_score_gemma":0.00002419587,"teacher_disagreement_score":0.23614007,"about_ca_system_score_codex":0.00016482915,"about_ca_system_score_gemma":0.000024837327,"threshold_uncertainty_score":0.72303593},"labels":[],"label_agreement":null},{"id":"W3216567109","doi":"10.5383/juspn.15.02.006","title":"An Effective and Efficient Framework for Fast Privacy-Preserving Keyword Search on Encrypted Outsourced Cloud Data","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Computer science; Encryption; Cloud computing; Keyword search; Information retrieval; Database; Service provider; Service (business); Computer security; Operating system","score_opus":0.03049799837850337,"score_gpt":0.3047207283369527,"score_spread":0.2742227299584493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216567109","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":[0.24962555,0.0049974783,0.743032,0.00038720353,0.001415557,0.0004309719,0.00006204127,0.000023920278,0.000025279749],"genre_scores_gemma":[0.9795213,0.00056442054,0.01783215,0.00031898034,0.0016972434,0.00001160842,0.000030208248,0.000021011301,0.000003124719],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973101,0.0005519071,0.00055848854,0.0006462293,0.00048319067,0.00045007642],"domain_scores_gemma":[0.99572545,0.0016109651,0.00039164815,0.0013202608,0.0005843181,0.0003673766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018515514,0.0002547225,0.0005623026,0.0001543181,0.0004099026,0.0008275207,0.0014425496,0.00020517918,0.0000032207124],"category_scores_gemma":[0.0003582939,0.00020844932,0.00011568942,0.00043225166,0.000078113255,0.000493751,0.0009969836,0.0006950832,4.38364e-7],"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":[0.0030957721,0.003021615,0.020600747,0.0026044566,0.002498064,0.0019500534,0.0506244,0.29279867,0.0035483008,0.33185476,0.028955348,0.25844783],"study_design_scores_gemma":[0.0017070003,0.0019125399,0.0065057958,0.0017411604,0.00009192415,0.0008129471,0.0025243103,0.974506,0.00020147928,0.0023606976,0.0071374285,0.00049869524],"about_ca_topic_score_codex":0.000047946058,"about_ca_topic_score_gemma":0.00001701792,"teacher_disagreement_score":0.7298957,"about_ca_system_score_codex":0.00003481884,"about_ca_system_score_gemma":0.00009140179,"threshold_uncertainty_score":0.8500316},"labels":[],"label_agreement":null},{"id":"W4206971186","doi":"10.5383/juspn","title":"Journal of Ubiquitous Systems and Pervasive Networks","year":2024,"lang":"en","type":"paratext","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Publishing; Ubiquitous computing; Computer science; World Wide Web; Resource (disambiguation); Knowledge management; Human–computer interaction; Political science","score_opus":0.014663188168041456,"score_gpt":0.24602672867022074,"score_spread":0.23136354050217928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206971186","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0109535465,0.548591,0.1864941,0.0003962798,0.25001833,0.00088575546,0.000011238755,0.000055008553,0.002594723],"genre_scores_gemma":[0.55064607,0.10546311,0.0014593039,0.0006051149,0.31634757,0.000039308194,0.00003549562,0.0005471112,0.024856912],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.991172,0.0010094302,0.003989267,0.0009411605,0.0014922272,0.0013959034],"domain_scores_gemma":[0.9886806,0.001132457,0.0057016728,0.00080446195,0.0027360586,0.0009447587],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0038652516,0.0012710937,0.0035260392,0.001067484,0.0006015738,0.003387368,0.0022382056,0.0015384956,0.000010872051],"category_scores_gemma":[0.00012084986,0.0009857938,0.00092983246,0.0008726678,0.0002597406,0.0009905082,0.0010059272,0.004133788,0.000040798564],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014827486,0.000106687796,0.0002053693,0.002586176,0.0017740537,0.0026422495,0.0033868884,0.124245636,0.000037044465,0.0003370775,0.8548001,0.009730467],"study_design_scores_gemma":[0.0021662444,0.0034765624,0.0001293391,0.02471307,0.0010989108,0.05559605,0.0016550706,0.44651434,0.000010556299,0.0001272611,0.46253964,0.001972938],"about_ca_topic_score_codex":0.00023485832,"about_ca_topic_score_gemma":0.000010307033,"teacher_disagreement_score":0.5396925,"about_ca_system_score_codex":0.00040817034,"about_ca_system_score_gemma":0.0010537172,"threshold_uncertainty_score":0.9997577},"labels":[],"label_agreement":null},{"id":"W4283696290","doi":"10.5383/juspn.17.01.006","title":"Towards Low-Cost IoT and LPWAN-Based Flood Forecast and Monitoring System","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"LPWAN; Flooding (psychology); Warning system; Flood myth; Environmental science; Internet of Things; Computer science; Surface runoff; Water resource management; Flood warning; Computer security; Telecommunications; Geography","score_opus":0.021308806048237355,"score_gpt":0.23279998704383403,"score_spread":0.2114911809955967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283696290","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":[0.9932119,0.003334076,0.0009931948,0.00020861479,0.0017820055,0.00031597097,0.000012851095,0.000052676645,0.00008866606],"genre_scores_gemma":[0.9985814,0.00015909794,0.00044604216,0.000016970143,0.00069483183,0.000034636316,8.133936e-7,0.000025029985,0.00004117039],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981031,0.00021609619,0.0005476459,0.00027760825,0.000502089,0.0003534777],"domain_scores_gemma":[0.9989922,0.00013720417,0.00045214023,0.0002062589,0.000038724967,0.00017346571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011341377,0.00022243847,0.0004473666,0.00009573438,0.00050793577,0.00017158937,0.0002734073,0.00012135701,0.000008762865],"category_scores_gemma":[0.000035456742,0.00018670522,0.0000651721,0.0001739971,0.0001633925,0.00013622167,0.0004518631,0.0005153076,8.095753e-7],"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":[0.00039499125,0.00018895575,0.6478161,0.0010069453,0.00025145934,0.00085122354,0.0034477573,0.27699456,0.004262018,0.0002039032,0.0024774515,0.062104605],"study_design_scores_gemma":[0.01311149,0.008513348,0.5359337,0.006963154,0.0010043989,0.020127151,0.1059642,0.2517188,0.011395804,0.00045087893,0.040580716,0.0042363848],"about_ca_topic_score_codex":0.00050802884,"about_ca_topic_score_gemma":0.000010866982,"teacher_disagreement_score":0.11188244,"about_ca_system_score_codex":0.0003378732,"about_ca_system_score_gemma":0.000024386622,"threshold_uncertainty_score":0.7613618},"labels":[],"label_agreement":null},{"id":"W4283697350","doi":"10.5383/juspn.17.01.004","title":"The way it made me feel – Creating and evaluating an in-app feedback tool for mobile apps","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile apps; Computer science; Plan (archaeology); App store; Human–computer interaction; Mobile device; World Wide Web; Realization (probability); Smartphone app; Multimedia","score_opus":0.02393578191765933,"score_gpt":0.2962273497027287,"score_spread":0.27229156778506935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283697350","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":[0.4748952,0.027623627,0.49302047,0.00070850237,0.0022756436,0.0012550235,0.00000671043,0.00009874114,0.00011605244],"genre_scores_gemma":[0.98117524,0.00094265083,0.016597748,0.0001224598,0.00081847096,0.00019369308,0.000001100159,0.00002110158,0.00012754001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983564,0.00028963876,0.0005484067,0.00020775742,0.00031747558,0.00028029727],"domain_scores_gemma":[0.99712515,0.0018631315,0.00053822243,0.00022759539,0.00016408636,0.00008183195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004080261,0.00014329959,0.00028458866,0.00007492279,0.0006499749,0.00049888063,0.00048577657,0.000062042294,0.0000024075794],"category_scores_gemma":[0.00016839552,0.00010497166,0.00006453272,0.00017773232,0.000023450148,0.00048392476,0.00022571381,0.00043962416,7.579457e-8],"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":[0.0002826166,0.00012869266,0.0055473302,0.0002885052,0.00018450417,0.0000961765,0.011050878,0.7072044,0.0011464871,0.005696199,0.005879566,0.26249462],"study_design_scores_gemma":[0.0006601201,0.002081332,0.0012450935,0.00023694642,0.00003284557,0.001307104,0.0029745225,0.96238333,0.000018926634,0.00043578557,0.028375864,0.0002481309],"about_ca_topic_score_codex":0.0000661868,"about_ca_topic_score_gemma":0.000011081559,"teacher_disagreement_score":0.50628,"about_ca_system_score_codex":0.00006805803,"about_ca_system_score_gemma":0.00005928266,"threshold_uncertainty_score":0.49991474},"labels":[],"label_agreement":null},{"id":"W4283702531","doi":"10.5383/juspn.17.02.002","title":"An Optimized Kappa Architecture for IoT Data Management in Smart Farming","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Architecture; Cloud computing; Process (computing); Domain (mathematical analysis); Tweaking; Data processing; Real-time computing; Distributed computing; Database; Operating system","score_opus":0.02863241000423216,"score_gpt":0.24906414432244317,"score_spread":0.220431734318211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283702531","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":[0.98901707,0.005958762,0.0007907965,0.0015046882,0.001527739,0.0008770034,0.0001140033,0.000018220835,0.00019171453],"genre_scores_gemma":[0.996174,0.00029083856,0.0006681418,0.00033211647,0.002214652,0.0000437006,0.00012096484,0.0000025377558,0.00015305255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985582,0.00019697713,0.00045128778,0.00026231326,0.0002509269,0.00028024803],"domain_scores_gemma":[0.9991934,0.00020477748,0.0003160069,0.00009990312,0.000072408635,0.00011351435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000993236,0.00014969902,0.0003552795,0.00003168251,0.00033246135,0.00011502446,0.0005705411,0.00006529219,0.000029099105],"category_scores_gemma":[0.000009733987,0.000057723995,0.00008809498,0.00022543652,0.000018085359,0.00010489443,0.00021173093,0.000307012,1.6158427e-7],"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":[0.002092112,0.0010396892,0.015161717,0.00023518062,0.00064421335,0.0006967198,0.0021720235,0.4817981,0.0140346335,0.0008772306,0.063907474,0.41734087],"study_design_scores_gemma":[0.003690743,0.004359147,0.03535939,0.00039188887,0.00028689174,0.0019335253,0.025720013,0.057667147,0.00003130379,0.00041959292,0.8691813,0.0009590729],"about_ca_topic_score_codex":0.00015525719,"about_ca_topic_score_gemma":0.00040642597,"teacher_disagreement_score":0.80527383,"about_ca_system_score_codex":0.000034097488,"about_ca_system_score_gemma":0.000009910164,"threshold_uncertainty_score":0.25570574},"labels":[],"label_agreement":null},{"id":"W4283703245","doi":"10.5383/juspn.17.01.005","title":"Towards Performance of NLP Transformers on URL-Based Phishing Detection for Mobile Devices","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Standards and Technology; National Science Foundation","keywords":"Phishing; Computer science; Transformer; Artificial intelligence; Machine learning; Deep learning; Mobile device; Artificial neural network; Social media; Vocabulary; World Wide Web; The Internet; Engineering","score_opus":0.013457564671147792,"score_gpt":0.22892873591393545,"score_spread":0.21547117124278767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283703245","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":[0.6667891,0.0017718882,0.32778972,0.00009411254,0.0030793808,0.00037429068,0.0000058427263,0.000020598898,0.000075043725],"genre_scores_gemma":[0.9987808,0.000109136716,0.00032092445,0.000111998204,0.00058877724,0.000059247715,0.0000011597983,0.000013037461,0.000014952639],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985287,0.00013540803,0.0005197421,0.00018396188,0.00041559245,0.0002165758],"domain_scores_gemma":[0.9986927,0.00021582386,0.000626929,0.00013688338,0.00024380679,0.00008386966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012145297,0.00014174628,0.0003314359,0.00019931042,0.0004283338,0.00011799211,0.00034763454,0.00007508836,0.0000037660425],"category_scores_gemma":[0.00001600678,0.00012178215,0.00017112562,0.00028776814,0.000024053712,0.00040347976,0.000031597345,0.0003420691,1.2421155e-7],"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":[0.00059634465,0.00010930812,0.000937572,0.0003811313,0.00009851049,0.0000089475525,0.0015612817,0.84489816,0.0019735494,0.0001891182,0.00029478298,0.14895128],"study_design_scores_gemma":[0.0013447829,0.009717804,0.0014491396,0.00032006338,0.000062341314,0.00034434316,0.0008825921,0.97085524,0.0036649748,0.00004174174,0.011062155,0.00025480645],"about_ca_topic_score_codex":0.00008574495,"about_ca_topic_score_gemma":0.000022611115,"teacher_disagreement_score":0.33199164,"about_ca_system_score_codex":0.000119196,"about_ca_system_score_gemma":0.000104649,"threshold_uncertainty_score":0.49661317},"labels":[],"label_agreement":null},{"id":"W4285105143","doi":"10.5383/juspn.16.01.005","title":"Fire Risk Prediction Using Cloud-based Weather Data Services","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Norges Forskningsråd","keywords":"Environmental science; Meteorology; Risk assessment; Cloud computing; Forensic engineering; Engineering; Geography; Computer science; Computer security","score_opus":0.016713078529064958,"score_gpt":0.212630525431769,"score_spread":0.19591744690270405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285105143","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":[0.9244874,0.029759727,0.02849416,0.000045555447,0.016056135,0.00041795566,0.00038688784,0.00014436524,0.0002078037],"genre_scores_gemma":[0.9964144,0.0005592808,0.00006856626,0.00003780439,0.0028004984,0.0000070097026,0.000022493146,0.00004474263,0.000045161392],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983219,0.00025170908,0.00066435913,0.00017344923,0.00036396954,0.00022463908],"domain_scores_gemma":[0.99891496,0.00009316554,0.00041649825,0.00034531916,0.000109599925,0.00012044505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009895726,0.00018050233,0.0003752288,0.00010255782,0.00039043365,0.00010151537,0.0003267251,0.00010505126,0.000036141897],"category_scores_gemma":[0.000007962021,0.00016297106,0.00009113381,0.00020539551,0.00001786605,0.00022466524,0.000089189576,0.00056288065,9.514941e-7],"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":[0.000054711018,0.000018439661,0.0051333103,0.00019481001,0.00015582016,0.000036091613,0.00039666315,0.98916733,0.00016252228,0.000003105762,0.0031253337,0.0015518336],"study_design_scores_gemma":[0.00054128404,0.00018646494,0.00070797524,0.00019807744,0.00009497163,0.0008079757,0.0017107583,0.9440995,0.0000048958177,0.000002591966,0.051502455,0.00014307928],"about_ca_topic_score_codex":0.0003630059,"about_ca_topic_score_gemma":0.000042390606,"teacher_disagreement_score":0.07192703,"about_ca_system_score_codex":0.00014158478,"about_ca_system_score_gemma":0.000039313683,"threshold_uncertainty_score":0.6645767},"labels":[],"label_agreement":null},{"id":"W4285165793","doi":"10.5383/juspn.16.01.001","title":"Understanding the Operation of Motorcycle Taxi Drivers in Nigeria Using Causal Loop Diagram","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Causal loop diagram; Taxis; Sanctions; Deterrence theory; Outcome (game theory); Qualitative analysis; System dynamics; Computer science; Qualitative research; Risk analysis (engineering); Transport engineering; Engineering; Operations research; Computer security; Business; Economics; Political science; Sociology; Microeconomics; Artificial intelligence","score_opus":0.22332168530121677,"score_gpt":0.36441634132921724,"score_spread":0.14109465602800048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285165793","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":[0.8329806,0.0046942043,0.15801135,0.00010508738,0.0035675215,0.00039389107,0.000010615619,0.000004555926,0.000232175],"genre_scores_gemma":[0.9991711,0.0000424501,0.00006296382,0.000048222842,0.0005326989,0.000005206442,3.7468894e-7,0.000013622478,0.00012337387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951012,0.0010871908,0.0017002807,0.00025538908,0.001588659,0.00026725398],"domain_scores_gemma":[0.99602073,0.0016109479,0.0015943693,0.0003108346,0.0003591792,0.00010394048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006548879,0.00016117262,0.00065835455,0.00041837414,0.0006104186,0.00039177053,0.000566945,0.00007491639,0.00009129662],"category_scores_gemma":[0.0003421637,0.00010230852,0.00018522478,0.000745916,0.00008980496,0.00031373705,0.00027432336,0.00043865613,6.344209e-7],"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":[0.00010046731,0.00003456818,0.03133641,0.000009831547,0.000037219528,0.00008194639,0.0032243312,0.9592597,0.0006896558,0.0019699007,0.0025961753,0.00065982534],"study_design_scores_gemma":[0.0012318898,0.00054628984,0.006777375,0.00026424826,0.000032287302,0.0012610606,0.08033788,0.90401876,0.0000073123306,0.0027957335,0.0024785409,0.0002486261],"about_ca_topic_score_codex":0.00031469713,"about_ca_topic_score_gemma":0.00028795341,"teacher_disagreement_score":0.16619049,"about_ca_system_score_codex":0.00030847773,"about_ca_system_score_gemma":0.00015812067,"threshold_uncertainty_score":0.46949083},"labels":[],"label_agreement":null},{"id":"W4285689403","doi":"10.5383/juspn.12.02.004","title":"iKarate: Karate Kata Aiding System","year":2020,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Martial arts; Block (permutation group theory); Computer science; Artificial intelligence; Human–computer interaction; Visual arts; Mathematics; Art","score_opus":0.024418483500800073,"score_gpt":0.21710099827036278,"score_spread":0.19268251476956272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285689403","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":[0.12815213,0.009575054,0.8527483,0.0018455943,0.0048719,0.00036848107,0.0000061569613,0.00014720675,0.0022852058],"genre_scores_gemma":[0.99590254,0.00034557586,0.0003622327,0.0005057123,0.002808367,0.0000032781318,0.0000011710093,0.000012368342,0.000058731843],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844855,0.00017499393,0.0006285853,0.00021898655,0.00028592144,0.00024297023],"domain_scores_gemma":[0.9984747,0.0001014642,0.00063946604,0.0001480417,0.00034830396,0.00028802452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046782068,0.00016486393,0.0004071162,0.00008586105,0.00023124377,0.0004835956,0.00038629965,0.00011091487,0.0000057290736],"category_scores_gemma":[0.00002215308,0.00013129153,0.00011715515,0.00023958432,0.00002320971,0.0007104185,0.00009029209,0.00033404882,0.000018478542],"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":[0.00092106656,0.0004982756,0.008102267,0.0062398957,0.0028041606,0.008880602,0.03120683,0.2814471,0.019322341,0.14886804,0.32225025,0.16945913],"study_design_scores_gemma":[0.0018790801,0.00149736,0.00072990626,0.0018914255,0.00012965803,0.0050080535,0.0035582734,0.94581974,0.0005643273,0.0001242046,0.038117263,0.0006806901],"about_ca_topic_score_codex":0.00001854718,"about_ca_topic_score_gemma":0.0000015009037,"teacher_disagreement_score":0.86775047,"about_ca_system_score_codex":0.00004661293,"about_ca_system_score_gemma":0.000064483786,"threshold_uncertainty_score":0.5353913},"labels":[],"label_agreement":null},{"id":"W4293108473","doi":"10.5383/juspn.16.02.003","title":"Design and Study of a Digital Energy Building: Case of Morocco","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"BIM and Construction Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Industrial Revolution; Urbanization; Energy consumption; Work (physics); Consumption (sociology); Architectural engineering; Globalization; Quality (philosophy); Digital Revolution; Business; Production (economics); Energy (signal processing); Environmental economics; Operations management; Computer science; Economic growth; Engineering; Economics; Political science; Mechanical engineering; Telecommunications; Sociology; Market economy","score_opus":0.012304327759315257,"score_gpt":0.2095279771306033,"score_spread":0.19722364937128806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293108473","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":[0.94295853,0.0050373357,0.051185746,0.0000044005355,0.00060850533,0.00011187958,0.000005371802,0.000007779084,0.00008047671],"genre_scores_gemma":[0.9995619,0.0001562145,0.000074887714,0.0000025723432,0.00016849913,0.000007985008,3.9230358e-7,0.000011685734,0.000015874508],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915445,0.000075924014,0.00047423423,0.000066992376,0.00014142865,0.00008695493],"domain_scores_gemma":[0.9993851,0.00009496856,0.0002650444,0.000067118635,0.00013399096,0.00005375702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021464421,0.000093276656,0.00029075195,0.00011193725,0.000077530116,0.000036600337,0.000054866174,0.000036799378,0.000004897],"category_scores_gemma":[0.000005685079,0.00008027599,0.000040957715,0.00011410329,0.000024285499,0.00012416208,0.000027555427,0.00015883934,1.0359063e-8],"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":[0.00010425272,0.000091774884,0.0020472293,0.00008570849,0.00028400417,0.0003503026,0.0020769502,0.9759795,0.0009217578,0.0007922925,0.0005311787,0.01673503],"study_design_scores_gemma":[0.0034855083,0.006492944,0.00061566033,0.00032393305,0.00038035557,0.07188801,0.06901771,0.8438973,0.0004598553,0.00033060368,0.0026061966,0.0005019711],"about_ca_topic_score_codex":0.00010476638,"about_ca_topic_score_gemma":0.000010956606,"teacher_disagreement_score":0.13208227,"about_ca_system_score_codex":0.000026702162,"about_ca_system_score_gemma":0.00001834895,"threshold_uncertainty_score":0.32735598},"labels":[],"label_agreement":null},{"id":"W4293108487","doi":"10.5383/juspn.16.02.006","title":"Access Control Metamodels: Review, Critical Analysis, and Research Issues","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Access Control and Trust","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Cegep de Sept Iles; Université du Québec à Rimouski","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Access control; Cloud computing; Authentication (law); Computer security; Abstraction; The Internet; Control (management); World Wide Web","score_opus":0.07539906703943597,"score_gpt":0.4432467667958854,"score_spread":0.3678476997564495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293108487","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024170293,0.9418125,0.008406698,0.019876096,0.0016763395,0.00091117027,0.000034838282,0.000023810622,0.003088213],"genre_scores_gemma":[0.9404674,0.0567066,0.000019550707,0.00056655944,0.0018712472,0.000040883227,0.0000014029068,0.000010694698,0.00031565485],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945881,0.002801587,0.0006776221,0.00023885223,0.0012206114,0.00047325977],"domain_scores_gemma":[0.9965803,0.0014744559,0.0003634107,0.00015865572,0.0011016971,0.00032149014],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009275617,0.00013745388,0.00086587155,0.00032347275,0.0017301852,0.0005611044,0.000532326,0.00009130648,0.00018462697],"category_scores_gemma":[0.0006499474,0.00010808,0.00020892576,0.0009800708,0.00036059887,0.0005580864,0.0002036609,0.0008174732,5.3673455e-7],"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":[0.0020640881,0.0013090444,0.32561427,0.0038483094,0.015429002,0.0028895717,0.030577477,0.074984595,0.00009942032,0.22570017,0.2482103,0.06927374],"study_design_scores_gemma":[0.0040991507,0.0020157334,0.020865368,0.0021228255,0.007996165,0.0007076421,0.03870574,0.066774614,0.000002636113,0.005493151,0.84996575,0.0012512453],"about_ca_topic_score_codex":0.0036654614,"about_ca_topic_score_gemma":0.000552392,"teacher_disagreement_score":0.91629714,"about_ca_system_score_codex":0.000090846224,"about_ca_system_score_gemma":0.00018828921,"threshold_uncertainty_score":0.9995694},"labels":[],"label_agreement":null},{"id":"W4293159709","doi":"10.5383/juspn.09.02.001","title":"Virtual Resources & Blockchain for Configuration Management in IoT","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cloud computing; Blockchain; Computer science; Provisioning; Virtualization; Permission; Enhanced Data Rates for GSM Evolution; Software deployment; Computer network; Distributed computing; Protocol (science); Computer security; Operating system; Telecommunications","score_opus":0.018763330529177672,"score_gpt":0.2657307037329076,"score_spread":0.2469673732037299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293159709","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":[0.45239678,0.0025776576,0.5403397,0.0026475585,0.00093717163,0.00064769,0.000002821693,0.000028218694,0.00042235863],"genre_scores_gemma":[0.9963596,0.0002598469,0.0027203641,0.000090692985,0.00033804902,0.00004324051,5.3871327e-7,0.000006911259,0.00018076882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988924,0.00005741827,0.0004756943,0.00020736567,0.00015387988,0.00021323588],"domain_scores_gemma":[0.9984211,0.000119629905,0.00069658353,0.0004908624,0.00018753184,0.00008434378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009948122,0.000116613235,0.00029087736,0.00015107584,0.000420105,0.0003060006,0.0008006698,0.00016679337,0.0000011113502],"category_scores_gemma":[0.000048963153,0.00010182825,0.000069071124,0.00007509052,0.00008195432,0.00009278906,0.00014083371,0.00022984896,7.0773416e-7],"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":[0.00020828757,0.00035854793,0.004450065,0.00023879869,0.00039936404,0.00014967911,0.0053610615,0.04404107,0.00043065415,0.65834934,0.010538253,0.27547488],"study_design_scores_gemma":[0.0053945817,0.0013790684,0.022349348,0.0010510888,0.0001125391,0.00091201236,0.002476153,0.76555103,0.0001323659,0.018305296,0.18145803,0.0008784851],"about_ca_topic_score_codex":0.000054436066,"about_ca_topic_score_gemma":0.00012922203,"teacher_disagreement_score":0.72150993,"about_ca_system_score_codex":0.000034514676,"about_ca_system_score_gemma":0.000022943152,"threshold_uncertainty_score":0.41524354},"labels":[],"label_agreement":null},{"id":"W4293159724","doi":"10.5383/juspn.09.02.002","title":"Evaluation of Privacy Preserving In-Network Aggregation for Different Routing Structures in WSNs","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Data aggregator; Computer science; Scheme (mathematics); Encryption; Wireless sensor network; Computer network; Cryptosystem; Routing protocol; Routing (electronic design automation); Cryptography; Distributed computing; Computer security; Mathematics","score_opus":0.04897081613066196,"score_gpt":0.31172298908434914,"score_spread":0.2627521729536872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293159724","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":[0.9173401,0.006848256,0.07227598,0.00017223794,0.0024426093,0.0007940016,0.000001493354,0.000007838662,0.00011745647],"genre_scores_gemma":[0.996686,0.0004015492,0.0013073779,0.000015600895,0.001550195,0.000018665503,0.0000012488429,0.000014750689,0.0000046306477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99706376,0.00047944108,0.0010560569,0.00026411982,0.0007435883,0.00039301233],"domain_scores_gemma":[0.99584,0.00057707896,0.002060594,0.0005477449,0.00088815513,0.000086432345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004039393,0.0001998646,0.00061578146,0.00016293162,0.00023218869,0.0003814313,0.0009930151,0.00020803825,0.0000014891765],"category_scores_gemma":[0.00063520164,0.00016745944,0.00011686386,0.00012950168,0.000050640716,0.00066468935,0.00025836818,0.00037818193,4.700037e-8],"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":[0.00006461714,0.000054109878,0.063751765,0.00014470037,0.00008056531,0.0000143295465,0.0033586838,0.89081836,0.00007601819,0.0054591848,0.0002380891,0.03593958],"study_design_scores_gemma":[0.0014774748,0.00016923898,0.10166982,0.0016452327,0.000048910046,0.00006217577,0.00021692939,0.8895652,0.000042810094,0.004905952,0.000044386437,0.00015183304],"about_ca_topic_score_codex":0.0002036649,"about_ca_topic_score_gemma":0.00042406083,"teacher_disagreement_score":0.07934585,"about_ca_system_score_codex":0.00017633087,"about_ca_system_score_gemma":0.00011046387,"threshold_uncertainty_score":0.68287975},"labels":[],"label_agreement":null},{"id":"W4293595602","doi":"10.5383/juspn.07.01.003","title":"A Guard Node (GN) based Technique against Misbehaving Nodes in MANET","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Computer network; Guard (computer science); Network packet; Routing protocol; Mobile ad hoc network; Intrusion detection system; Node (physics); Overhead (engineering); Wireless ad hoc network; Computer security; Wireless; Engineering; Telecommunications","score_opus":0.01147508621031084,"score_gpt":0.22721665920873688,"score_spread":0.21574157299842603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293595602","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":[0.05919794,0.0044289986,0.93304545,0.0007565117,0.0015053048,0.0005783967,0.0000037852399,0.0000608304,0.00042280767],"genre_scores_gemma":[0.99152213,0.0007005323,0.006161025,0.00040677213,0.0010425613,0.000053058386,7.345615e-7,0.000031739288,0.000081420185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997122,0.00036785973,0.0010613397,0.00040100256,0.00045916453,0.00058864424],"domain_scores_gemma":[0.9975215,0.00056522683,0.0008044025,0.00053759,0.0003198156,0.00025142333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016657488,0.00031281036,0.0006732892,0.00028782597,0.000115387054,0.0002549394,0.00091674604,0.00029735567,0.0000075923203],"category_scores_gemma":[0.000059577156,0.00021023005,0.00016887033,0.00037339522,0.00007871518,0.00060011103,0.00018279694,0.0004898095,0.0000028913903],"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":[0.0005547866,0.0008860197,0.15531367,0.0008351011,0.0003937507,0.008006205,0.0021725586,0.43733585,0.03824724,0.0067784716,0.03268819,0.31678817],"study_design_scores_gemma":[0.00823452,0.0019022134,0.025211174,0.018889394,0.00011969072,0.0050229845,0.00044037247,0.9014793,0.0015703855,0.00065974175,0.034088336,0.0023818875],"about_ca_topic_score_codex":0.00006841626,"about_ca_topic_score_gemma":0.000060559458,"teacher_disagreement_score":0.93232423,"about_ca_system_score_codex":0.00019257746,"about_ca_system_score_gemma":0.00016357447,"threshold_uncertainty_score":0.85729325},"labels":[],"label_agreement":null},{"id":"W4296499191","doi":"10.5383/juspn.015.01.004","title":"Contribution to Multi-Energy Flow Management for Building Energy Hub,","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Renewable energy; Fossil fuel; Environmental science; Global warming; Natural resource economics; Energy development; Renewable fuels; Primary energy; Environmental impact of the energy industry; Climate change mitigation; Environmental engineering; Environmental protection; Waste management; Climate change; Energy policy; Engineering; Ecology; Economics","score_opus":0.012728543210754784,"score_gpt":0.24628148188917817,"score_spread":0.2335529386784234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296499191","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":[0.0053676036,0.011328296,0.9776161,0.00041395985,0.0038199222,0.00018183816,0.00000863809,0.000031269003,0.0012324242],"genre_scores_gemma":[0.9847495,0.002570536,0.006544124,0.0009749516,0.002190518,0.00007930442,0.000022495022,0.000044174365,0.002824406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978558,0.00017267076,0.0007960819,0.00033771168,0.00032784772,0.0005099149],"domain_scores_gemma":[0.99811393,0.00017048065,0.00040906988,0.0002485961,0.0008026847,0.0002552304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006283999,0.00026301862,0.00055878464,0.00018914985,0.00028352631,0.00018201198,0.00022479132,0.00016582212,0.00001629356],"category_scores_gemma":[0.00006759875,0.00023103844,0.00024019487,0.00030381445,0.000026262696,0.00014874914,0.00014388571,0.00012793709,6.860411e-7],"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":[0.00012433942,0.00012128397,0.000022772136,0.00008968537,0.00036688804,0.00023535328,0.000095383424,0.69371355,0.00053494796,0.27367717,0.0048892736,0.02612937],"study_design_scores_gemma":[0.0024917494,0.00048559622,0.00014309747,0.0007199656,0.0002567293,0.00031098974,0.0008634237,0.21646337,0.001073051,0.00060713105,0.7761604,0.0004244812],"about_ca_topic_score_codex":0.0002864545,"about_ca_topic_score_gemma":0.00046140928,"teacher_disagreement_score":0.97938186,"about_ca_system_score_codex":0.00014878857,"about_ca_system_score_gemma":0.000040933668,"threshold_uncertainty_score":0.94214743},"labels":[],"label_agreement":null},{"id":"W4297905948","doi":"10.5383/juspn.09.02.003","title":"Content-aware and QoE Optimization of Video Stream Scheduling over LTE Networks using Genetic Algorithm and Random Neural Networks","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Quality of experience; Scheduling (production processes); Quality of service; Telecommunications link; Real-time computing; Computer network; Algorithm; Distributed computing; Engineering","score_opus":0.03877358244616819,"score_gpt":0.2909627661485324,"score_spread":0.2521891837023642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297905948","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":[0.10116781,0.018317074,0.8784811,0.00010369468,0.0016027363,0.00030577177,0.0000024355368,0.000011806843,0.0000075616113],"genre_scores_gemma":[0.97036207,0.004205446,0.023656232,0.00011866306,0.0016071919,0.00000416393,0.0000019983438,0.000025241025,0.000018973422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974671,0.0003368836,0.0010327512,0.0003699667,0.0003640602,0.00042923473],"domain_scores_gemma":[0.99658877,0.00029096165,0.0018418671,0.0004467516,0.0005672482,0.00026442122],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010784859,0.00031414084,0.0008554486,0.000119682656,0.00064792455,0.0011530279,0.0004704995,0.00024070356,0.0000020750513],"category_scores_gemma":[0.00005638738,0.00026049578,0.00013807266,0.00010231953,0.0001917825,0.0011491511,0.00035988074,0.00045275854,3.221376e-8],"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":[0.00007579168,0.000032487984,0.008448335,0.00007916287,0.00015457245,0.00009209581,0.00027394557,0.96770036,0.00001517004,0.000058593112,0.00005554524,0.02301393],"study_design_scores_gemma":[0.0025976475,0.00032621677,0.0059717027,0.00075685757,0.00013444021,0.00076038484,0.0003178755,0.98883,0.000005054802,0.000018052593,0.000023571118,0.00025821466],"about_ca_topic_score_codex":0.00044265957,"about_ca_topic_score_gemma":0.000015361857,"teacher_disagreement_score":0.86919427,"about_ca_system_score_codex":0.000044058463,"about_ca_system_score_gemma":0.00006796854,"threshold_uncertainty_score":0.99998474},"labels":[],"label_agreement":null},{"id":"W4297913661","doi":"10.5383/juspn.07.01.002","title":"Comparison and Analysis Study between AODV and DSR Routing Protocols in VANET with IEEE 802.11","year":2016,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Ad hoc On-Demand Distance Vector Routing; Computer network; Computer science; Vehicular ad hoc network; Destination-Sequenced Distance Vector routing; Dynamic Source Routing; Mobile ad hoc network; Optimized Link State Routing Protocol; Distance-vector routing protocol; Routing protocol; Wireless ad hoc network; Routing (electronic design automation); Wireless; Telecommunications","score_opus":0.02934762940618573,"score_gpt":0.30029803509186825,"score_spread":0.2709504056856825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297913661","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":[0.79904884,0.0009266084,0.19596449,0.000091403446,0.00017547025,0.0037385854,0.000002595392,0.000020280364,0.000031710588],"genre_scores_gemma":[0.99819934,0.00008324723,0.0006632974,0.000024839448,0.000728913,0.00024817736,4.5290915e-7,0.000018183746,0.000033521257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969849,0.00050158845,0.0010924643,0.000483506,0.00047188211,0.0004656894],"domain_scores_gemma":[0.99733174,0.00069210905,0.0010474782,0.00038566135,0.00025314567,0.00028989176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018916196,0.00030625326,0.0012252374,0.00030425887,0.0001641725,0.00043832112,0.00044212854,0.00015775466,0.0000017158806],"category_scores_gemma":[0.000023652727,0.00018417106,0.00007347834,0.0006724748,0.00009178358,0.00057377457,0.00018326179,0.0003800498,2.8336933e-7],"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":[0.00005096056,0.00008499341,0.97766954,0.000033565386,0.00035749993,0.000121818026,0.0014274011,0.0097911265,0.000014972276,0.00007219525,0.00019868882,0.010177237],"study_design_scores_gemma":[0.003996177,0.0034111831,0.8488685,0.0017796393,0.0004930825,0.00044087708,0.00134594,0.13851044,0.000010850437,0.000038208247,0.00053908775,0.00056605326],"about_ca_topic_score_codex":0.00022551912,"about_ca_topic_score_gemma":0.0007925381,"teacher_disagreement_score":0.1991505,"about_ca_system_score_codex":0.00006870259,"about_ca_system_score_gemma":0.00006350897,"threshold_uncertainty_score":0.75102776},"labels":[],"label_agreement":null},{"id":"W4299951465","doi":"10.5383/juspn.09.01.003","title":"Improved SingleTapBraille: Developing a single tap text entry method based on Grade 1 and 2 braille encoding","year":2017,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Taif University; Saudi Arabian Cultural Bureau","keywords":"Touchscreen; Braille; Computer science; Text entry; Visually impaired; Human–computer interaction; Thumb; Object (grammar); Gesture; Computer vision; Artificial intelligence; Operating system; Medicine","score_opus":0.05871958580612116,"score_gpt":0.31207007793814534,"score_spread":0.2533504921320242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299951465","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":[0.9098635,0.0012914056,0.05922605,0.0047029387,0.010913229,0.0010960712,0.000029338626,0.00008225369,0.0127952425],"genre_scores_gemma":[0.9963284,0.00032298936,0.0008195945,0.00079213583,0.0012421373,0.0000082138695,4.7457556e-7,0.000029744568,0.00045632306],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981569,0.00029360515,0.00057420164,0.00033879725,0.00027591316,0.0003606066],"domain_scores_gemma":[0.99691015,0.0012879516,0.0011268783,0.00031054436,0.0001577378,0.00020670831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033098547,0.0002494887,0.0004900383,0.00016968792,0.001130452,0.0008206129,0.00027898606,0.00016352616,0.000012294504],"category_scores_gemma":[0.0008962112,0.00019817846,0.00013425156,0.00007737418,0.000109693974,0.00050331926,0.00007481967,0.0005437195,0.0000013796582],"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":[0.00082104007,0.00059481413,0.003460476,0.000428469,0.00020641804,0.0013868039,0.002929064,0.01918382,0.9079461,0.0026409552,0.005336448,0.055065565],"study_design_scores_gemma":[0.0069144405,0.004132477,0.004588147,0.005222852,0.00041039422,0.014091082,0.0049610343,0.7220307,0.1073675,0.00020011849,0.12811598,0.001965306],"about_ca_topic_score_codex":0.00007146352,"about_ca_topic_score_gemma":0.000032817556,"teacher_disagreement_score":0.80057865,"about_ca_system_score_codex":0.00009200404,"about_ca_system_score_gemma":0.00008290352,"threshold_uncertainty_score":0.8694638},"labels":[],"label_agreement":null},{"id":"W4300221961","doi":"10.5383/juspn.03.01.000","title":"Signal-Layer Security and Trust-Boundary Identification based on Hardware-Software Interface Definition","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Safety Systems Engineering in Autonomy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automotive industry; Computer security; Domain (mathematical analysis); Functional safety; Computer science; Process (computing); Identification (biology); Cyber-physical system; Risk analysis (engineering); Engineering","score_opus":0.021070187669767617,"score_gpt":0.20852958452209658,"score_spread":0.18745939685232896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300221961","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":[0.44837868,0.018338602,0.5256196,0.00003538151,0.0053707366,0.0006531842,0.000037200494,0.0002700664,0.0012965121],"genre_scores_gemma":[0.9983425,0.00031456474,0.0006031725,0.000025433925,0.0006137953,0.00001875233,0.0000047048256,0.00005545303,0.00002160106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984997,0.00009197191,0.0007423235,0.00018363824,0.0002344963,0.00024788023],"domain_scores_gemma":[0.99895155,0.0001760648,0.00029705756,0.0002044133,0.0002080913,0.00016281761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059732137,0.00026103365,0.00043206225,0.00019732788,0.00010489815,0.00013507919,0.00014575431,0.00021195384,0.000020323856],"category_scores_gemma":[0.000036160724,0.0002416426,0.00009498849,0.00012416617,0.000045095338,0.0002580048,0.000020976926,0.00043686756,0.0000044885314],"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":[0.00028065412,0.000111116235,0.011118996,0.0020036055,0.00050760724,0.0001633697,0.007225999,0.96591496,0.0016474676,0.00043662003,0.0043155234,0.0062740697],"study_design_scores_gemma":[0.0016530266,0.0007818641,0.019394865,0.0029049579,0.00021475485,0.001084595,0.001490019,0.9622686,0.0013702917,0.00021664552,0.0077807913,0.0008395925],"about_ca_topic_score_codex":0.000032854234,"about_ca_topic_score_gemma":0.0000054556285,"teacher_disagreement_score":0.54996383,"about_ca_system_score_codex":0.00013585776,"about_ca_system_score_gemma":0.00003539954,"threshold_uncertainty_score":0.98538995},"labels":[],"label_agreement":null},{"id":"W4390580944","doi":"10.5383/juspn.17.01.003","title":"From Collective Memory to Map Services","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Collective memory; Refugee; Alienation; Group cohesiveness; Palimpsest; Crowdsourcing; Point (geometry); Context (archaeology); Cohesion (chemistry); Quality (philosophy); Computer science; Affect (linguistics); Social group; Psychology; Social psychology; Sociology; Business; Internet privacy; Public relations; World Wide Web; Political science; Geography; Communication; Epistemology","score_opus":0.011504995477134511,"score_gpt":0.2194003465203374,"score_spread":0.2078953510432029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390580944","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":[0.10353031,0.019584505,0.85656285,0.0018356078,0.015399997,0.0007070839,0.000054695625,0.00007388799,0.0022510341],"genre_scores_gemma":[0.9932034,0.00011664903,0.0013505211,0.001295029,0.0029263985,0.000024916571,0.000004528861,0.000019783382,0.0010587948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976632,0.00033466905,0.00068297505,0.0003380293,0.000608149,0.00037300657],"domain_scores_gemma":[0.9979751,0.000359223,0.0006200234,0.00034024852,0.0003266151,0.00037875044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083509507,0.00022053612,0.0005683919,0.00016743131,0.0005371157,0.00033042158,0.0008978905,0.000092779024,0.000046488243],"category_scores_gemma":[0.0000031291063,0.00019199913,0.00013577561,0.00039179917,0.000027480153,0.00029568453,0.00056418346,0.00053688185,0.0000042491347],"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":[0.0010094756,0.000516826,0.003838996,0.00024554602,0.0012533154,0.004685786,0.04786282,0.48994106,0.0003036318,0.002894603,0.34265405,0.10479388],"study_design_scores_gemma":[0.0012271845,0.0015611104,0.00054709864,0.00032379726,0.00008956033,0.0015216441,0.0084378375,0.9233894,0.000005685235,0.001175498,0.061207615,0.0005135832],"about_ca_topic_score_codex":0.0003870952,"about_ca_topic_score_gemma":0.000025526144,"teacher_disagreement_score":0.88967305,"about_ca_system_score_codex":0.00016466959,"about_ca_system_score_gemma":0.0002504679,"threshold_uncertainty_score":0.78294975},"labels":[],"label_agreement":null},{"id":"W4390580964","doi":"10.5383/juspn.17.01.002","title":"Small Towns and Regional Municipalities Implement SMART Solutions, Identified Issues, and Challenges","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Univerzita Komenského v Bratislave","keywords":"Investment (military); Smart city; Process (computing); Business; Population; Rural area; Environmental planning; Data collection; Regional science; Economic growth; Environmental economics; Geography; Computer science; Political science; Computer security; Economics; Internet of Things; Sociology","score_opus":0.07639389386362117,"score_gpt":0.2356979303155628,"score_spread":0.15930403645194163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390580964","genre_codex":"review","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":[0.4624954,0.53404415,0.00023793949,0.0014782106,0.0013226673,0.000185061,0.000021741755,0.000069847425,0.00014499939],"genre_scores_gemma":[0.856602,0.14252107,0.000082010556,0.00003734395,0.0005209081,0.00002927374,0.000003746304,0.000020828005,0.00018282796],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988755,0.00008051196,0.00042897524,0.0001316823,0.0001900634,0.00029324475],"domain_scores_gemma":[0.99941987,0.00013414955,0.00015002314,0.00013638147,0.00007616278,0.000083400206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006044661,0.00016545736,0.00035946045,0.00013211381,0.00036087862,0.00010413863,0.00013246713,0.00008349828,0.000014786119],"category_scores_gemma":[0.000011533125,0.00014948659,0.000055596574,0.000059318318,0.00007134456,0.00010223025,0.00021283628,0.00034811016,1.1331464e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056893326,0.00033816075,0.023587324,0.00644454,0.0053506545,0.0012471895,0.057042576,0.23311993,0.00095450337,0.2068477,0.29543167,0.1690668],"study_design_scores_gemma":[0.0014187223,0.0009844758,0.008363372,0.00044686883,0.00017579057,0.0045524067,0.13254817,0.028754134,0.000014921607,0.0013217123,0.8208085,0.0006109321],"about_ca_topic_score_codex":0.00038910654,"about_ca_topic_score_gemma":0.00037713954,"teacher_disagreement_score":0.5253768,"about_ca_system_score_codex":0.00005997814,"about_ca_system_score_gemma":0.000016960907,"threshold_uncertainty_score":0.6095886},"labels":[],"label_agreement":null},{"id":"W4390580986","doi":"10.5383/juspn.17.01.001","title":"Remote Collaboration Needs for New Work: Concepts, Procedure and Evaluation","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Work (physics); Knowledge management; Computer science; Context (archaeology); Focus (optics); Management science; Data science; Process management; Engineering","score_opus":0.030513611641523417,"score_gpt":0.2768791926272612,"score_spread":0.24636558098573777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390580986","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":[0.9472454,0.0147553645,0.023778593,0.005191133,0.004915972,0.0024079925,0.0000046323403,0.000053838336,0.00164708],"genre_scores_gemma":[0.99579346,0.00008454569,0.0003790076,0.0006173258,0.0027187194,0.000034710887,0.000015751635,0.000015860096,0.00034059625],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894655,0.00004473265,0.00042433376,0.00012619616,0.0002876036,0.00017056926],"domain_scores_gemma":[0.9983279,0.00006388175,0.0007407732,0.0000629112,0.0007901594,0.000014348577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019008187,0.0001235711,0.00026513904,0.00021368201,0.0005714143,0.00017024975,0.00011597254,0.00011479436,0.000016010837],"category_scores_gemma":[0.0001331922,0.00011174244,0.00003800841,0.0006891732,0.000052094958,0.00034025245,0.000108487795,0.00026753597,2.695071e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018346735,0.00019283158,0.035589874,0.0011184107,0.0009387157,0.000042239917,0.0125881415,0.04884089,0.00024524686,0.19490632,0.37684968,0.32685298],"study_design_scores_gemma":[0.008868373,0.00076681573,0.015814891,0.000767756,0.000831946,0.00040138376,0.10538573,0.21653515,0.000024290695,0.024866732,0.6245108,0.0012261306],"about_ca_topic_score_codex":0.000031434243,"about_ca_topic_score_gemma":0.000010318836,"teacher_disagreement_score":0.32562685,"about_ca_system_score_codex":0.00009859994,"about_ca_system_score_gemma":0.00015779541,"threshold_uncertainty_score":0.45567244},"labels":[],"label_agreement":null},{"id":"W4390594529","doi":"10.5383/juspn.18.01.005","title":"5G-enhanced Positioning Accuracy in Smart City","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Computer science; Implementation; Smart grid; Automation; Smart city; Wireless; Key (lock); Wireless broadband; Cover (algebra); Telecommunications; Wireless network; Systems engineering; Computer security; Engineering; Internet of Things; Software engineering","score_opus":0.01253039291681504,"score_gpt":0.23078521834991356,"score_spread":0.21825482543309851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390594529","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":[0.956498,0.005112509,0.034580607,0.00009824482,0.0021503621,0.00018479151,0.0000036234069,0.00024729155,0.001124543],"genre_scores_gemma":[0.9963517,0.0030830768,0.00003913697,0.000025244148,0.00042075684,0.000007174161,0.0000028896154,0.00001963203,0.000050372037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989794,0.000038672573,0.0004851852,0.00008858749,0.00015263753,0.00025553454],"domain_scores_gemma":[0.99939954,0.00017887581,0.00013949766,0.00009751348,0.00012857401,0.00005599441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037796661,0.0001279743,0.00030554112,0.00025348566,0.000079864214,0.00008784074,0.00012754573,0.00016843698,0.0000072006383],"category_scores_gemma":[0.000085570624,0.00011227457,0.00006290754,0.0004502219,0.000028016188,0.00020098769,0.000023841772,0.00033687553,0.0000037967588],"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":[0.000025742926,0.000012104378,0.008653829,0.00016648283,0.000072109724,0.00015811616,0.00091541756,0.9745289,0.0019553092,0.0003238927,0.0045829923,0.008605074],"study_design_scores_gemma":[0.002939048,0.00053813856,0.055747643,0.0037302254,0.00008910485,0.00095659215,0.008268958,0.91247934,0.0064357105,0.0008855005,0.006905275,0.0010244662],"about_ca_topic_score_codex":0.000036389025,"about_ca_topic_score_gemma":0.00003572516,"teacher_disagreement_score":0.062049594,"about_ca_system_score_codex":0.00006698271,"about_ca_system_score_gemma":0.000017530312,"threshold_uncertainty_score":0.4578424},"labels":[],"label_agreement":null},{"id":"W4390594677","doi":"10.5383/juspn.18.01.006","title":"Hybrid-MiGrror: An Extension to the Hybrid Live Migration to Support Mobility in Edge Computing","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cloud computing; Edge computing; Downtime; Computer network; sync; Mobile edge computing; Enhanced Data Rates for GSM Evolution; Server; Latency (audio); Distributed computing; Channel (broadcasting); Operating system; Telecommunications","score_opus":0.028081639733733073,"score_gpt":0.27641551136810666,"score_spread":0.2483338716343736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390594677","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":[0.8704303,0.00039266254,0.11729868,0.0011167106,0.010224694,0.00045339597,9.131662e-7,0.000054631048,0.000028048837],"genre_scores_gemma":[0.9925887,0.000051472725,0.00067237916,0.00060181104,0.0060118684,0.000005755237,0.0000043875884,0.000017182387,0.000046416582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973303,0.00036875412,0.00088860054,0.00042886636,0.00043607055,0.0005474144],"domain_scores_gemma":[0.9979717,0.00037861036,0.00039174306,0.00045762575,0.0004752378,0.00032509133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035026586,0.00022686592,0.00047609655,0.0002965533,0.00035346491,0.00044422364,0.0007511415,0.000067272595,8.216465e-7],"category_scores_gemma":[0.00012592471,0.00016393565,0.0001156166,0.00060683454,0.000024293731,0.00042065012,0.00041906143,0.00042410076,0.000023776845],"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":[0.00013772502,0.00022202915,0.015488128,0.0001469916,0.00006985884,0.0011395918,0.026905991,0.6373459,0.0007229317,0.00015315779,0.17408285,0.14358483],"study_design_scores_gemma":[0.0003822822,0.0013042197,0.039587628,0.00056427455,0.000015676364,0.0012224355,0.0010539807,0.9430748,0.000080117585,0.000095158095,0.0122926645,0.00032676753],"about_ca_topic_score_codex":0.0004239619,"about_ca_topic_score_gemma":0.00017340385,"teacher_disagreement_score":0.30572888,"about_ca_system_score_codex":0.00011377822,"about_ca_system_score_gemma":0.00011879495,"threshold_uncertainty_score":0.66851014},"labels":[],"label_agreement":null},{"id":"W4390594749","doi":"10.5383/juspn.18.01.004","title":"A Study of the Ambient Noise in the Public Space on Campus and the Correlation Between the Campus Crowds’ Ambient Noise and the WiFi Log","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Research Foundation Singapore; National Research Foundation","keywords":"Noise (video); Crowds; Ambient noise level; Computer science; Perspective (graphical); The Internet; Software deployment; Mobile device; Environmental noise; Human–computer interaction; Internet privacy; World Wide Web; Acoustics; Computer security; Sound (geography); Artificial intelligence","score_opus":0.013968557832956656,"score_gpt":0.23136497627594887,"score_spread":0.2173964184429922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390594749","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":[0.9902539,0.002918803,0.0005054495,0.0038660464,0.0010623252,0.0012346478,0.0000060970174,0.000012703724,0.00013997572],"genre_scores_gemma":[0.9980507,0.0011942144,0.0000012337212,0.00016945037,0.00042836156,0.00004163987,0.0000014898241,0.000021314734,0.00009162756],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975935,0.000863252,0.00065360963,0.0001418778,0.0004971461,0.00025061108],"domain_scores_gemma":[0.99740463,0.0015634648,0.00045880085,0.00035264617,0.00015919331,0.00006123992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003284216,0.00020687822,0.00041600585,0.000091254784,0.00041828424,0.00027938222,0.00032311448,0.00011195948,0.0000010182531],"category_scores_gemma":[0.00014477744,0.000078054814,0.00010650355,0.0005461439,0.0002656407,0.00008814936,0.00009508794,0.00073138217,7.485058e-7],"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":[0.00037752217,0.000119228134,0.10833028,0.00012023857,0.0004980893,0.000039952032,0.054853782,0.82237095,0.000050837596,0.0065654013,0.004474129,0.0021995772],"study_design_scores_gemma":[0.007602629,0.00047327083,0.40131646,0.00046693694,0.00037762037,0.0004204143,0.052005626,0.5349726,0.0000039773436,0.00036849125,0.0017302001,0.0002617695],"about_ca_topic_score_codex":0.00017823308,"about_ca_topic_score_gemma":0.00062696513,"teacher_disagreement_score":0.29298618,"about_ca_system_score_codex":0.000053633023,"about_ca_system_score_gemma":0.00003242563,"threshold_uncertainty_score":0.32171464},"labels":[],"label_agreement":null},{"id":"W4390594794","doi":"10.5383/juspn.18.01.003","title":"Segment Routing v6 - Security Issues and Experimental Results","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Header; Computer network; Computer science; Testbed; Source routing; IPv6; Network packet; Routing (electronic design automation); Link-state routing protocol; Distributed computing; Routing protocol; The Internet; World Wide Web","score_opus":0.01219001462905075,"score_gpt":0.24623888840892633,"score_spread":0.23404887377987557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390594794","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":[0.9432338,0.050646488,0.0005057107,0.00011056163,0.0044202735,0.00040975882,0.000026075322,0.00017042455,0.0004768959],"genre_scores_gemma":[0.99229455,0.004024027,0.000045006567,0.000031195166,0.003436844,0.000012496823,0.000009406596,0.00005001983,0.00009645457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976633,0.00016908837,0.0009565053,0.00027460055,0.00039841566,0.0005380775],"domain_scores_gemma":[0.99878937,0.00024857526,0.00030823893,0.00023156215,0.0001574805,0.00026479064],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014425284,0.00032626887,0.0006606747,0.00013249379,0.00020369141,0.00023471967,0.00017571168,0.0002510166,0.000006827689],"category_scores_gemma":[0.000042632288,0.00029135065,0.0001266958,0.00025528367,0.0000815081,0.00029609402,0.00013508441,0.0005791543,0.0000035253838],"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":[0.0012823729,0.00034412212,0.0140688,0.00163112,0.0015176332,0.0015056954,0.04891174,0.7987068,0.004180855,0.0008059705,0.11794366,0.009101196],"study_design_scores_gemma":[0.005335582,0.0011788046,0.005394488,0.0019964096,0.00020527928,0.0016515354,0.0139747625,0.947438,0.0017003211,0.00022901996,0.019726971,0.0011688397],"about_ca_topic_score_codex":0.00014389055,"about_ca_topic_score_gemma":0.000053032374,"teacher_disagreement_score":0.14873116,"about_ca_system_score_codex":0.0001432225,"about_ca_system_score_gemma":0.000022288807,"threshold_uncertainty_score":0.99995387},"labels":[],"label_agreement":null},{"id":"W4390595017","doi":"10.5383/juspn.18.01.002","title":"Control of autonomous UAV using an onboard LSTM neural network","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Embedding; Global Positioning System; Artificial intelligence; Artificial neural network; Control (management); Lift (data mining); Control engineering; Real-time computing; Engineering; Machine learning; Telecommunications","score_opus":0.03414590375742107,"score_gpt":0.2692528413358813,"score_spread":0.2351069375784602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390595017","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":[0.28701273,0.0043099024,0.70175654,0.00018530471,0.006281611,0.00029438623,0.000005164993,0.000095995216,0.000058362544],"genre_scores_gemma":[0.9857604,0.00010590218,0.010921577,0.00010495412,0.0030397621,0.0000030294802,0.0000016091203,0.000025715997,0.000037064605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972486,0.00039984373,0.0010030619,0.0002906231,0.0004788688,0.0005789871],"domain_scores_gemma":[0.9973053,0.00041884204,0.0011376091,0.0004002771,0.00044046962,0.0002975074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016743169,0.00024710645,0.00081399875,0.00020306808,0.00020921187,0.00023064612,0.0007412466,0.00018669476,0.0000011787301],"category_scores_gemma":[0.000049940933,0.00020498932,0.00017154877,0.0005862772,0.00007523952,0.0005570556,0.00013296999,0.00042623567,0.0000016105561],"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":[0.000026033835,0.000028914286,0.0037303744,0.00004179615,0.00010094346,0.00036912897,0.0006026028,0.9902232,0.00022009911,0.0003717006,0.000860271,0.003424932],"study_design_scores_gemma":[0.0007484216,0.000650778,0.005092449,0.0003559438,0.000055452067,0.0014611573,0.0001996311,0.9909209,0.000007185646,0.000074170726,0.00023314214,0.00020074812],"about_ca_topic_score_codex":0.000119244716,"about_ca_topic_score_gemma":0.0000038467706,"teacher_disagreement_score":0.69874763,"about_ca_system_score_codex":0.00006238421,"about_ca_system_score_gemma":0.00016256806,"threshold_uncertainty_score":0.8359222},"labels":[],"label_agreement":null},{"id":"W4390595257","doi":"10.5383/juspn.18.01.001","title":"Empowering Reality: A New Injury Prevention Education System to Promote the Empowerment of Child Caregivers","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Persona Design and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Empowerment; Inclusion (mineral); Psychology; Object (grammar); Nursing; Medical education; Medicine; Computer science; Social psychology; Artificial intelligence","score_opus":0.01707611705331877,"score_gpt":0.2928342257396686,"score_spread":0.2757581086863498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390595257","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":[0.4228926,0.006368894,0.5459998,0.013880978,0.0059475987,0.002823407,0.000014453439,0.00018203096,0.0018902544],"genre_scores_gemma":[0.9980492,0.00023772387,0.0004114567,0.0000801876,0.000795745,0.00002632886,0.0000017713852,0.000009672037,0.00038788765],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99869615,0.000114293136,0.0004970536,0.00018374067,0.00031850304,0.00019023533],"domain_scores_gemma":[0.9986904,0.00004839621,0.00051893544,0.00031750335,0.00025065374,0.00017406078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008042014,0.00012118837,0.00026406653,0.00014907354,0.00019109153,0.00014411726,0.0004709208,0.00006744332,6.7849174e-7],"category_scores_gemma":[0.000017026281,0.0000864747,0.00010842912,0.00058757316,0.00001932826,0.00020000906,0.000109644694,0.0001631771,0.0000026754092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026529733,0.0004518842,0.0011143086,0.0014491066,0.0008100936,0.0000675103,0.066089414,0.06349879,0.0067558037,0.06541839,0.41641676,0.37766263],"study_design_scores_gemma":[0.0032478939,0.0059387945,0.027548954,0.023681264,0.0005804681,0.0047404314,0.07182765,0.31586877,0.0012727185,0.0014162866,0.54188013,0.0019966548],"about_ca_topic_score_codex":0.00018703328,"about_ca_topic_score_gemma":0.000013126976,"teacher_disagreement_score":0.5751566,"about_ca_system_score_codex":0.00010030565,"about_ca_system_score_gemma":0.00027005657,"threshold_uncertainty_score":0.35263357},"labels":[],"label_agreement":null},{"id":"W4390596133","doi":"10.5383/juspn.18.02.002","title":"Combining the Internet of Things (IoT) and the Internet of Behavior (IoB) to create a robust educational environment","year":2023,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"The Internet; Computer science; Distance education; Internet of Things; E learning; Knowledge management; World Wide Web; Psychology; Mathematics education","score_opus":0.016802825319113354,"score_gpt":0.24674276574758536,"score_spread":0.229939940428472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390596133","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":[0.9527038,0.0029096708,0.03590328,0.0070971074,0.00096260716,0.00029978415,0.000002415801,0.00001161737,0.00010972283],"genre_scores_gemma":[0.9975615,0.00037781062,0.00068724673,0.00014158996,0.00031503531,0.0000070261904,0.0000010809242,0.000009064465,0.00089962047],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985614,0.00021274498,0.0005920489,0.00014732864,0.00031902787,0.00016744147],"domain_scores_gemma":[0.9983098,0.00060577405,0.0006526137,0.0002036751,0.00014086481,0.00008729873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014387675,0.00012399403,0.00036814142,0.00010066986,0.00007871221,0.00013202967,0.0005284591,0.000059629165,0.000004692561],"category_scores_gemma":[0.000063972766,0.0000682168,0.000105951345,0.00018010652,0.00014369686,0.00010185698,0.00028865016,0.00032321754,0.0000014468602],"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":[0.00056308956,0.00064065674,0.1454521,0.0006162218,0.0014241259,0.00014488254,0.11999361,0.58614266,0.0006596379,0.06454831,0.033885587,0.04592914],"study_design_scores_gemma":[0.0012894582,0.0008833982,0.034238573,0.0013044793,0.0001925532,0.0006158837,0.002916519,0.95562375,0.000037264694,0.00041063718,0.0022815152,0.00020594498],"about_ca_topic_score_codex":0.00030349958,"about_ca_topic_score_gemma":0.0000058072064,"teacher_disagreement_score":0.36948115,"about_ca_system_score_codex":0.000022975511,"about_ca_system_score_gemma":0.000050531064,"threshold_uncertainty_score":0.27818003},"labels":[],"label_agreement":null},{"id":"W4390597111","doi":"10.5383/juspn.16.01.004","title":"The Flipped Classroom Opportunities within The Hybrid Learning Approach in the UAE","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flipped classroom; Mathematics education; Blended learning; Attractiveness; Computer science; Class (philosophy); Psychology; Pedagogy; Educational technology","score_opus":0.07070597751039749,"score_gpt":0.31770007572099734,"score_spread":0.24699409821059987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597111","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":[0.90273404,0.022268249,0.0139514385,0.016295137,0.008249014,0.0016435118,0.0000076194196,0.000048910504,0.03480207],"genre_scores_gemma":[0.99537504,0.0006013697,0.00010519712,0.0004594233,0.0021152247,0.000045172666,0.0000014439173,0.000016731761,0.0012804248],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9866375,0.011208418,0.0007017408,0.00014171917,0.00091716164,0.00039350137],"domain_scores_gemma":[0.9959172,0.0025493524,0.0010339145,0.00018799359,0.00025398514,0.000057582653],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.033274353,0.00014938184,0.00030765004,0.000084757376,0.0049209725,0.0004852609,0.0008995791,0.000058255635,0.000008008185],"category_scores_gemma":[0.0004907569,0.000072375995,0.00011234948,0.00040624503,0.00040848585,0.00015831047,0.00013766356,0.0022481447,2.0426971e-7],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035001468,0.00018774829,0.020706236,0.000065360735,0.00036900485,0.00032836694,0.36575288,0.300862,0.000051737992,0.24975914,0.03303171,0.02853577],"study_design_scores_gemma":[0.00037872835,0.00033311633,0.0015336876,0.000072540686,0.00004480376,0.0007111111,0.72330564,0.016191699,8.0543657e-7,0.0011334886,0.25610888,0.00018550082],"about_ca_topic_score_codex":0.001005136,"about_ca_topic_score_gemma":0.00023765094,"teacher_disagreement_score":0.35755274,"about_ca_system_score_codex":0.0001719903,"about_ca_system_score_gemma":0.00033065892,"threshold_uncertainty_score":0.9963745},"labels":[],"label_agreement":null},{"id":"W4390597120","doi":"10.5383/juspn.16.02.005","title":"Use Cases of Data Reduction to Time Series Data in Sensor Monitoring","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Process (computing); Computer science; Reduction (mathematics); Data mining; Real-time computing; Wireless sensor network; Blueprint; Time series; SIGNAL (programming language); Data reduction; Network packet; Series (stratigraphy); Machine learning; Engineering; Mathematics; Computer security","score_opus":0.04677952308500457,"score_gpt":0.26581142814182823,"score_spread":0.21903190505682366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597120","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":[0.9867427,0.0073099653,0.0006065513,0.00007281351,0.004682783,0.0003196116,0.00020164941,0.000033414748,0.000030543364],"genre_scores_gemma":[0.9977447,0.0004054836,0.00012731862,0.0000046864443,0.0014856238,0.000007861765,0.000016798553,0.000025371062,0.00018215411],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985335,0.00016746452,0.0006652337,0.00017622179,0.0002756336,0.00018197924],"domain_scores_gemma":[0.99890864,0.00015225413,0.00022561669,0.0005282642,0.00009089149,0.00009431634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080864574,0.00013041167,0.00041932357,0.00018229481,0.00009262548,0.000083119805,0.00040076932,0.000057043537,0.000008957602],"category_scores_gemma":[0.00007385659,0.00012428571,0.000032560623,0.00024776155,0.000014081783,0.0006941724,0.00023547487,0.0003097777,8.1729763e-7],"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":[0.00026158846,0.00003391139,0.0032713674,0.00017921059,0.0001872792,0.00023605341,0.00078714965,0.9692939,0.013389615,0.000004949708,0.008044026,0.004310944],"study_design_scores_gemma":[0.0020884124,0.0016464102,0.0061578252,0.0016668938,0.00022981997,0.024224017,0.025338864,0.81346273,0.00048196106,0.000003601565,0.12382625,0.0008732324],"about_ca_topic_score_codex":0.0004935566,"about_ca_topic_score_gemma":0.00004679356,"teacher_disagreement_score":0.15583119,"about_ca_system_score_codex":0.00008849164,"about_ca_system_score_gemma":0.000028376131,"threshold_uncertainty_score":0.5068224},"labels":[],"label_agreement":null},{"id":"W4390597121","doi":"10.5383/juspn.16.02.004","title":"A Novel Micro-services Cluster Based Framework for Autonomous Vehicles","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"United Arab Emirates University","keywords":"Microservices; Computer science; Cloud computing; Encryption; Vehicular ad hoc network; Orchestration; Service (business); Computer security; Service provider; Intelligent transportation system; Distributed computing; Computer network; Wireless ad hoc network; Telecommunications; Operating system","score_opus":0.01182029841242596,"score_gpt":0.23756559490551327,"score_spread":0.2257452964930873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052699517,0.0058179945,0.93743986,0.002552608,0.0009873611,0.00041538072,0.000017775237,0.00004948091,0.00002000372],"genre_scores_gemma":[0.94131905,0.000060097245,0.056675892,0.0012245753,0.0005366341,0.00013239171,0.0000024908868,0.000016194432,0.000032681124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986231,0.00008634386,0.0005264166,0.00026276315,0.00021377126,0.0002876437],"domain_scores_gemma":[0.9981768,0.00045824263,0.0006481745,0.0003677222,0.00025014055,0.00009888987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091134326,0.00015859902,0.000362807,0.00015487072,0.0005871687,0.0001695512,0.0009371026,0.00017403343,0.0000031955792],"category_scores_gemma":[0.000014327633,0.00013997722,0.00014651823,0.00026987327,0.000049835107,0.00012863806,0.00027629916,0.0005514645,3.1328142e-7],"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":[0.0005087247,0.001609744,0.004373188,0.0010111008,0.00073247065,0.00014857361,0.007776214,0.41283053,0.0048187757,0.5050162,0.015207024,0.045967452],"study_design_scores_gemma":[0.0012459318,0.000786586,0.00040788538,0.00015311602,0.000048939706,0.0013562354,0.000926086,0.927482,0.00010506477,0.0061486447,0.061041977,0.00029751542],"about_ca_topic_score_codex":0.000042416723,"about_ca_topic_score_gemma":0.000008831449,"teacher_disagreement_score":0.88861954,"about_ca_system_score_codex":0.0000702869,"about_ca_system_score_gemma":0.00010492204,"threshold_uncertainty_score":0.57081056},"labels":[],"label_agreement":null},{"id":"W4390597122","doi":"10.5383/juspn.17.02.003","title":"Low Rank Graph Regularization Embedding for 2D+3D Facial Expression Recognition","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Hebei Province Science and Technology Support Program; National Natural Science Foundation of China","keywords":"Embedding; Tensor (intrinsic definition); Facial expression; Regularization (linguistics); Graph embedding; Rank (graph theory); Pattern recognition (psychology); Support vector machine; Graph; Computer science; Artificial intelligence; Mathematics; Theoretical computer science; Combinatorics; Pure mathematics","score_opus":0.03549677848626891,"score_gpt":0.29689852905576325,"score_spread":0.26140175056949433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597122","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":[0.32395434,0.0010924282,0.6708909,0.0003610694,0.00201763,0.0012482393,0.00012933432,0.00005618849,0.00024985147],"genre_scores_gemma":[0.99161595,0.00017592097,0.0059195613,0.000117661664,0.0016152584,0.00017352469,0.000063226864,0.000038023165,0.0002808476],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856436,0.0001845904,0.00063582597,0.00015634837,0.00027970364,0.00017914458],"domain_scores_gemma":[0.9982777,0.00033638728,0.0008126764,0.00012380224,0.00035461527,0.00009481375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066893967,0.00013415523,0.00033021616,0.00014008529,0.0006361761,0.000092754155,0.00012217928,0.00009089647,0.000046229598],"category_scores_gemma":[0.000058882593,0.00012063298,0.00015923602,0.00015540316,0.000022835788,0.00014725646,0.000041887193,0.0002626328,5.0865043e-7],"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":[0.0040245685,0.002968439,0.0010661021,0.0030702467,0.0012323398,0.00016222912,0.017114496,0.33369127,0.12987922,0.037811942,0.35007712,0.118902],"study_design_scores_gemma":[0.023659494,0.006048223,0.0008220489,0.005559396,0.0020515898,0.008787115,0.031755764,0.52909094,0.0089096185,0.23934877,0.14053424,0.003432773],"about_ca_topic_score_codex":0.0000032611788,"about_ca_topic_score_gemma":0.0000017725826,"teacher_disagreement_score":0.66766167,"about_ca_system_score_codex":0.000064921805,"about_ca_system_score_gemma":0.000032510045,"threshold_uncertainty_score":0.49192703},"labels":[],"label_agreement":null},{"id":"W4390597123","doi":"10.5383/juspn.17.02.001","title":"New and Reliable Points Shifting - Based Algorithm for Indoor Location Services","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Telus (Canada); Sheridan College","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Algorithm; Set (abstract data type); Metric (unit); Multipath propagation; Grid; Upper and lower bounds; k-nearest neighbors algorithm; Bounded function; Data mining; Artificial intelligence; Mathematics; Telecommunications","score_opus":0.006482775096025587,"score_gpt":0.20059111306842434,"score_spread":0.19410833797239874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597123","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":[0.033788268,0.029244913,0.9338391,0.00020616304,0.0022159321,0.00047553008,0.000018492992,0.00013586509,0.000075754055],"genre_scores_gemma":[0.99089366,0.0005163333,0.007552035,0.00013259293,0.0007624355,0.000026523287,0.0000093574245,0.00003828992,0.000068769186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990823,0.00003127454,0.00040783547,0.00010797989,0.00017136091,0.00019919714],"domain_scores_gemma":[0.9993452,0.00010802008,0.00021407503,0.00008895689,0.0001668833,0.00007688365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043306497,0.00013237806,0.00027386236,0.00013663928,0.00024404164,0.000101013604,0.00013105822,0.00009690662,0.000009288888],"category_scores_gemma":[0.000011948984,0.000122040045,0.00004655881,0.0001940846,0.000014499392,0.00014995526,0.00004155432,0.00024691378,1.8961472e-7],"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":[0.000047535075,0.000016973594,0.0020762808,0.00061342405,0.0001134273,0.000019073712,0.0008178127,0.88561594,0.00008028405,0.0002749796,0.00694732,0.10337696],"study_design_scores_gemma":[0.00089397444,0.0002681705,0.00022518206,0.00019982568,0.00004437061,0.0001550802,0.0022687688,0.980942,0.00012659476,0.00010900158,0.014611927,0.00015508437],"about_ca_topic_score_codex":0.0000732992,"about_ca_topic_score_gemma":0.000010878333,"teacher_disagreement_score":0.9571054,"about_ca_system_score_codex":0.00006945313,"about_ca_system_score_gemma":0.000044670243,"threshold_uncertainty_score":0.49766487},"labels":[],"label_agreement":null},{"id":"W4390597125","doi":"10.5383/juspn.16.02.002","title":"A Filtering Method for Fast Convex Hull Construction","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Convex hull; Polygon (computer graphics); Hull; Vertex (graph theory); Computer science; Computer graphics; Set (abstract data type); Regular polygon; Computational geometry; Speedup; Algorithm; Convex set; Computer graphics (images); Theoretical computer science; Mathematics; Convex optimization; Parallel computing; Geometry; Engineering","score_opus":0.01025088592619701,"score_gpt":0.2233157069374328,"score_spread":0.2130648210112358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597125","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":[0.018561708,0.0027641396,0.9749037,0.00004786614,0.0033140874,0.00022982588,0.000016279131,0.000026135716,0.0001362367],"genre_scores_gemma":[0.9896879,0.00034044107,0.008403822,0.000060592658,0.001370392,0.00002384482,0.000010657623,0.000041380863,0.000060963415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990346,0.00008654065,0.00044521707,0.00009232965,0.00016171766,0.00017958986],"domain_scores_gemma":[0.99933493,0.00014618746,0.00020510278,0.000077428595,0.00015494782,0.00008138368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045331844,0.000119922355,0.00031802032,0.00009875306,0.00019707534,0.000072680494,0.000079759324,0.00006328644,0.000016483878],"category_scores_gemma":[0.000013348753,0.00011442062,0.00009627686,0.000101766396,0.000015997484,0.00007676428,0.000021910037,0.00023266936,1.5016667e-7],"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":[0.000036109857,0.0000073112424,0.00015392673,0.0001217746,0.00008407805,0.000013736765,0.0002780856,0.990566,0.0011781773,0.00068452815,0.0021068384,0.00476943],"study_design_scores_gemma":[0.0005573951,0.00027588406,0.000039832696,0.00007362969,0.000051893574,0.0010616514,0.0015425261,0.98213804,0.0000826832,0.00006610291,0.013977103,0.0001332639],"about_ca_topic_score_codex":0.000017292472,"about_ca_topic_score_gemma":0.0000036006422,"teacher_disagreement_score":0.9711262,"about_ca_system_score_codex":0.00008152751,"about_ca_system_score_gemma":0.000021647096,"threshold_uncertainty_score":0.46659374},"labels":[],"label_agreement":null},{"id":"W4390597126","doi":"10.5383/juspn.16.01.002","title":"Dynamic Segmentation, Configuration, and Governance of SDN","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Forwarding plane; Computer science; Scalability; Software-defined networking; Distributed computing; Routing control plane; Segmentation; Computer network; Dynamic network analysis; Artificial intelligence","score_opus":0.00786230717124912,"score_gpt":0.21997762274830132,"score_spread":0.2121153155770522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597126","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":[0.26657867,0.0706495,0.65645635,0.001168002,0.0043418906,0.00049433,0.000024005563,0.0000383214,0.00024894995],"genre_scores_gemma":[0.99624556,0.0020067657,0.0012034879,0.00016692992,0.00022061483,0.000010153308,0.0000022171537,0.000009942641,0.00013433148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984832,0.00016484897,0.00061168463,0.00017904409,0.00038259153,0.00017865343],"domain_scores_gemma":[0.9982624,0.00023695685,0.00095036865,0.00017439641,0.0002809569,0.00009489881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006251973,0.00012871498,0.00034888613,0.00006169026,0.00024877605,0.00011443811,0.00031285977,0.000050153958,0.000012338689],"category_scores_gemma":[0.000023825614,0.00011175877,0.00006542045,0.00024351722,0.000047316433,0.00030823846,0.00014567116,0.00025349902,2.0045196e-7],"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":[0.00031538925,0.00032664332,0.035276573,0.00047555502,0.00063159596,0.00035881944,0.009258977,0.7509776,0.0019094269,0.055318724,0.04306022,0.10209048],"study_design_scores_gemma":[0.0038527397,0.0032122985,0.049471423,0.0006226589,0.00014692034,0.005828466,0.0033326442,0.90418077,0.00009827256,0.0016661986,0.026792377,0.00079525786],"about_ca_topic_score_codex":0.00006403098,"about_ca_topic_score_gemma":0.00001299527,"teacher_disagreement_score":0.7296669,"about_ca_system_score_codex":0.00006007955,"about_ca_system_score_gemma":0.00008642907,"threshold_uncertainty_score":0.45573902},"labels":[],"label_agreement":null},{"id":"W4390597127","doi":"10.5383/juspn.17.02.005","title":"An Architecture for Cognitive Computing in Healthcare","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cognitive computing; Big data; Computer science; Health care; Cognition; Analytics; Data science; Cognitive architecture; Service (business); Architecture; Knowledge management; Medicine","score_opus":0.01807221522818127,"score_gpt":0.2795919864777059,"score_spread":0.26151977124952464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597127","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":[0.2069704,0.009259498,0.78050125,0.0007260177,0.0020189567,0.00045471586,0.000010423418,0.000028609164,0.000030166862],"genre_scores_gemma":[0.9963884,0.000090994225,0.0013649893,0.00067859737,0.0014247065,0.000016629208,0.0000056969616,0.000018563363,0.000011465773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975818,0.00066169683,0.00065247656,0.00033932002,0.00032113583,0.00044357276],"domain_scores_gemma":[0.9975545,0.001002006,0.000616419,0.00016409138,0.0004682554,0.00019472216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018050246,0.0001928426,0.0004944041,0.00024673634,0.00050521956,0.00018782166,0.0005306258,0.000081324215,0.0000012301663],"category_scores_gemma":[0.000049927377,0.00017739934,0.00012745945,0.00040123824,0.000035777244,0.00016644453,0.00024295102,0.0008325647,1.0790875e-7],"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":[0.000387768,0.00026307115,0.012141577,0.00017881129,0.00011779236,0.00039734482,0.006977876,0.6086503,0.00004153337,0.0037174777,0.0014409741,0.36568543],"study_design_scores_gemma":[0.001921583,0.0030240156,0.0059583928,0.00062144635,0.000025613264,0.0023376597,0.0020820645,0.98098457,0.000005569762,0.00077481003,0.0019163963,0.00034785102],"about_ca_topic_score_codex":0.00010469497,"about_ca_topic_score_gemma":0.00005484768,"teacher_disagreement_score":0.789418,"about_ca_system_score_codex":0.00009126455,"about_ca_system_score_gemma":0.00014307135,"threshold_uncertainty_score":0.7234135},"labels":[],"label_agreement":null},{"id":"W4390597136","doi":"10.5383/juspn.16.01.006","title":"An Enhanced Fuzzy Clustering to Pattern Recognition for Cloud Computing, by using Model Aggregation and Model Selection","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Cluster analysis; Cloud computing; Computer science; Fuzzy clustering; Data mining; Fuzzy logic; Adaptive resonance theory; Artificial intelligence; Machine learning; Model selection","score_opus":0.03468317124047883,"score_gpt":0.30431706792857116,"score_spread":0.26963389668809234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597136","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":[0.26076877,0.00036822067,0.7379676,0.000054341042,0.00046707946,0.0003379131,0.000011518748,0.000020853775,0.000003695929],"genre_scores_gemma":[0.9465711,0.00007009928,0.05253658,0.00013000972,0.0006137473,0.000024463936,0.0000054514444,0.000025734584,0.000022830525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99827445,0.00017495076,0.00048965943,0.00033835496,0.00037751536,0.00034509518],"domain_scores_gemma":[0.9986546,0.00010875333,0.00045016923,0.00014298008,0.00043851044,0.00020498529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009415849,0.00016473282,0.00030308578,0.00017168606,0.0006164529,0.00029220743,0.00029217472,0.00007153559,4.525088e-7],"category_scores_gemma":[0.000022515322,0.00016983812,0.000051576553,0.00021700413,0.000017210657,0.0005626314,0.00024365724,0.00033872036,7.4906936e-8],"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":[0.000055347853,0.000025696016,0.000021558306,0.00005185877,0.000018224806,0.0000025786721,0.0012424912,0.87017936,0.0049254512,0.000006171597,0.00013273105,0.12333852],"study_design_scores_gemma":[0.00057124277,0.00077303813,0.0000067152478,0.00015510732,0.000013642427,0.0004137278,0.0003326315,0.99702704,0.00024201997,0.00024775972,0.000026486847,0.00019056012],"about_ca_topic_score_codex":0.00005959126,"about_ca_topic_score_gemma":0.000016752301,"teacher_disagreement_score":0.6858023,"about_ca_system_score_codex":0.00020448091,"about_ca_system_score_gemma":0.00007772155,"threshold_uncertainty_score":0.69257975},"labels":[],"label_agreement":null},{"id":"W4390597144","doi":"10.5383/juspn.17.02.004","title":"Design and Specification of a Privacy-Preserving Registration for Blockchain-Based Energy Markets","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Blockchain; Computer security; Computer science; Context (archaeology); Traceability; Scalability; Smart grid; Flexibility (engineering); Smart contract; Cryptography; Database","score_opus":0.019068215937560362,"score_gpt":0.2287233170963033,"score_spread":0.20965510115874295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597144","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":[0.06547051,0.0043990356,0.92873734,0.0008312109,0.00021846018,0.000302689,0.0000024522278,0.000015845415,0.000022481885],"genre_scores_gemma":[0.9815823,0.00010311049,0.017997922,0.00006366798,0.00015851653,0.000059102244,0.000001170711,0.000007840846,0.000026403739],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987112,0.0001863848,0.0005379078,0.0001925502,0.00021561317,0.00015632376],"domain_scores_gemma":[0.99791956,0.0005161499,0.00087014877,0.0003166524,0.00031643355,0.0000610723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018946569,0.000101540325,0.00025498617,0.00017422094,0.00028626577,0.00004973479,0.00050055573,0.000095476506,0.0000017561582],"category_scores_gemma":[0.00004587898,0.00009512337,0.000055430744,0.00024405854,0.00005179352,0.000035069508,0.00014728108,0.00018294908,1.2108243e-8],"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":[0.00090835826,0.0005703959,0.0015316162,0.00049295794,0.00030484592,0.0000538265,0.0029928256,0.64344895,0.008749967,0.24008057,0.012429099,0.08843658],"study_design_scores_gemma":[0.00054721965,0.0005007793,0.00036462536,0.00005355504,0.000020389327,0.00023616738,0.00026425588,0.98991567,0.000451948,0.002498357,0.0050407234,0.000106321975],"about_ca_topic_score_codex":0.000030980373,"about_ca_topic_score_gemma":0.000004773174,"teacher_disagreement_score":0.91611177,"about_ca_system_score_codex":0.000043134547,"about_ca_system_score_gemma":0.00008438182,"threshold_uncertainty_score":0.38790184},"labels":[],"label_agreement":null},{"id":"W4390597156","doi":"10.5383/juspn.17.02.006","title":"Some Results on Colored Network Contraction","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Scalability; Leverage (statistics); Node (physics); Distributed computing; Graph; Theoretical computer science; Colored; Property (philosophy); Artificial intelligence; Engineering; Database","score_opus":0.012612228035950907,"score_gpt":0.24706371041568484,"score_spread":0.23445148237973393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597156","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":[0.90048313,0.028472532,0.04020596,0.0021036048,0.014627575,0.0024183264,0.00022534617,0.00021344358,0.011250089],"genre_scores_gemma":[0.9887117,0.00017161712,0.00007562573,0.00015594457,0.010455476,0.000036456953,0.00002506147,0.000027332017,0.00034075705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976167,0.0004228767,0.0009212532,0.0002370933,0.00043086073,0.0003711888],"domain_scores_gemma":[0.99766845,0.00041623687,0.0013071039,0.00023916436,0.00021955752,0.0001494749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012981308,0.00022219833,0.00061772874,0.00012863938,0.0005875489,0.0001290523,0.0002471092,0.000057050194,0.00006515697],"category_scores_gemma":[0.000010014511,0.00019572272,0.0002666998,0.0002730495,0.000040340667,0.00016449418,0.000113957205,0.0007832384,0.0000012630773],"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":[0.0008397552,0.00017267685,0.004704455,0.000009127727,0.00048023078,0.00005074428,0.0002066453,0.83189493,0.00005407884,0.01343911,0.14278728,0.005360982],"study_design_scores_gemma":[0.0077626375,0.0075730653,0.010807218,0.0007703142,0.000980425,0.0007072656,0.0057192016,0.3261796,0.00007100212,0.0129978545,0.6248408,0.0015906442],"about_ca_topic_score_codex":0.00021802171,"about_ca_topic_score_gemma":0.000008046655,"teacher_disagreement_score":0.5057153,"about_ca_system_score_codex":0.00011818135,"about_ca_system_score_gemma":0.00007026236,"threshold_uncertainty_score":0.7981341},"labels":[],"label_agreement":null},{"id":"W4390597269","doi":"10.5383/juspn.15.01.006","title":"Internet of Things (IoT) based Network Integrated with Sensor Nodes for Intruder Detection and Low Energy Consumption","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Intrusion detection system; Energy consumption; Wireless sensor network; Cloud computing; Scheduling (production processes); Real-time computing; Key (lock); Constant false alarm rate; Queueing theory; Distributed computing; Computer network; Algorithm; Data mining; Computer security; Engineering","score_opus":0.013456153846749853,"score_gpt":0.21022964391197813,"score_spread":0.19677349006522826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597269","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":[0.1740653,0.0033036105,0.81909615,0.00007004248,0.0033399246,0.00009250164,2.8426513e-7,0.000015763946,0.00001643559],"genre_scores_gemma":[0.98726434,0.00017444947,0.01008372,0.00018924806,0.0022123482,0.000004218724,0.0000022760446,0.000015974465,0.000053440497],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986057,0.00017986196,0.00054027786,0.000230184,0.00018814212,0.00025579706],"domain_scores_gemma":[0.99780947,0.00043323255,0.0006584477,0.00014433281,0.0008468588,0.0001076502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005911778,0.00017793666,0.0004505236,0.00009399927,0.00012708323,0.00024103477,0.00015889414,0.00014189759,9.675599e-7],"category_scores_gemma":[0.00004009775,0.00013246624,0.00008316107,0.00021254618,0.000060900893,0.00024112583,0.000068807574,0.00022567762,9.040163e-8],"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":[0.0028025452,0.00048728194,0.047824178,0.0035733138,0.0020742882,0.00079641474,0.009345399,0.4040559,0.0165312,0.0035255428,0.015675958,0.49330798],"study_design_scores_gemma":[0.0009969597,0.0005564988,0.0009889936,0.0015110509,0.000055376473,0.0010409239,0.00013811595,0.9910595,0.0015709389,0.00006487457,0.0018350085,0.00018177908],"about_ca_topic_score_codex":0.00009473327,"about_ca_topic_score_gemma":0.000024798683,"teacher_disagreement_score":0.813199,"about_ca_system_score_codex":0.000044413835,"about_ca_system_score_gemma":0.000112314905,"threshold_uncertainty_score":0.5401817},"labels":[],"label_agreement":null},{"id":"W4390597271","doi":"10.5383/juspn.15.01.007","title":"Performance Analysis and Functionality Comparison of First Hop Redundancy Protocols","year":2021,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Computer network; Redundancy (engineering); Router; Hop (telecommunications); Downtime; Network packet; Routing protocol; Packet loss; Distributed computing; Operating system","score_opus":0.02827432174962817,"score_gpt":0.2804504250216055,"score_spread":0.2521761032719773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390597271","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":[0.5951913,0.019387955,0.3817895,0.00045397607,0.0013424513,0.0015359486,0.000007798159,0.00003582929,0.0002552362],"genre_scores_gemma":[0.9965467,0.00078975456,0.0018161006,0.000045132525,0.000638269,0.00007523421,0.0000026462028,0.000008939077,0.00007725903],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99791986,0.0001699441,0.00094615924,0.00028359663,0.0004257304,0.00025470185],"domain_scores_gemma":[0.99729526,0.00036458357,0.0009720028,0.00034726277,0.00084767904,0.00017323202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007711328,0.00018563331,0.00084885495,0.00015252168,0.00023474403,0.00022449356,0.0002890492,0.00014577086,0.000009098145],"category_scores_gemma":[0.000057534606,0.00014935642,0.00020140737,0.00088086375,0.00007510857,0.00036784747,0.00016097147,0.0003191522,3.1445336e-7],"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":[0.00008204016,0.00016879797,0.8989956,0.00038796928,0.00076707813,0.000045656074,0.0008537774,0.08296257,0.00003863525,0.00061703223,0.0025111486,0.012569698],"study_design_scores_gemma":[0.0012446372,0.0009903,0.32522494,0.0012271714,0.00044429224,0.00078187365,0.00046349707,0.6586611,0.00012551922,0.00009763044,0.010353487,0.00038550814],"about_ca_topic_score_codex":0.00005314203,"about_ca_topic_score_gemma":0.000085591404,"teacher_disagreement_score":0.57569855,"about_ca_system_score_codex":0.000035565332,"about_ca_system_score_gemma":0.00011101531,"threshold_uncertainty_score":0.6090578},"labels":[],"label_agreement":null},{"id":"W4390602193","doi":"10.5383/juspn.16.02.001","title":"A smart spontaneous crowd evacuation system for large multi-exit exhibition centers based on IoT","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Zayed University","keywords":"Exhibition; Scalability; Computer science; Hazard; Internet of Things; Computer security; Transport engineering; Simulation; Engineering; Database; Geography","score_opus":0.012364515864840074,"score_gpt":0.2240559034531087,"score_spread":0.2116913875882686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390602193","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":[0.4102401,0.003091478,0.57610476,0.00017690453,0.007977311,0.0015159204,0.00027665,0.00019454546,0.00042230726],"genre_scores_gemma":[0.9987526,0.00007568731,0.00026804532,0.00013366382,0.0005155763,0.00007413586,0.000049964186,0.000051647265,0.00007868545],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839395,0.00015416613,0.0006310175,0.00015450842,0.00036996073,0.00029642176],"domain_scores_gemma":[0.99898183,0.00019680333,0.00032047185,0.0001435567,0.00022554674,0.00013180604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091842987,0.00020224125,0.00036869186,0.00028390222,0.0003582425,0.000100015386,0.0001293762,0.0001056022,0.00001804067],"category_scores_gemma":[0.000024755012,0.00019420905,0.0001768597,0.00018980769,0.000009783919,0.00007260679,0.000020021389,0.00034710995,0.0000012289961],"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":[0.0002478174,0.00007489754,0.00032288764,0.00033883052,0.000072653624,0.00014747509,0.00025670655,0.99441075,0.00034159792,0.00036282695,0.0030044925,0.00041905887],"study_design_scores_gemma":[0.0020757755,0.0005618859,0.00033229977,0.00033029914,0.00006764106,0.0010736362,0.0017815959,0.9886261,0.000016110473,0.0000037648072,0.0049381647,0.00019269103],"about_ca_topic_score_codex":0.000014139015,"about_ca_topic_score_gemma":0.000042504813,"teacher_disagreement_score":0.5885125,"about_ca_system_score_codex":0.00040195888,"about_ca_system_score_gemma":0.00004171886,"threshold_uncertainty_score":0.7919615},"labels":[],"label_agreement":null},{"id":"W4390602345","doi":"10.5383/juspn.16.01.003","title":"DATABASE MANAGEMENT SYSTEM FOR SMART GYM USING IOT","year":2022,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Technologies and Applied Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Track (disk drive); Computer science; Payment; Work (physics); Internet privacy; Management system; System administrator; Internet of Things; World Wide Web; Computer security; Engineering; Operations management","score_opus":0.023598312339320134,"score_gpt":0.24864622654406238,"score_spread":0.22504791420474224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390602345","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026032316,0.004413886,0.96632797,0.00010106965,0.002507266,0.00043109033,0.000007723465,0.000074483534,0.00010419067],"genre_scores_gemma":[0.93855536,0.00009870732,0.060656294,0.00007685164,0.0005120567,0.000035124227,0.0000014528987,0.000018839004,0.000045302262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983731,0.00007360007,0.00058183906,0.00028209097,0.0003260343,0.00036332646],"domain_scores_gemma":[0.9985469,0.00015059132,0.00072208495,0.00035582038,0.00013470229,0.00008988383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087310094,0.00017005308,0.00038309803,0.00015231314,0.0006872779,0.00016484046,0.00080877036,0.000049781625,8.318781e-7],"category_scores_gemma":[0.000007426265,0.00014880783,0.000115384464,0.00029293422,0.000024243123,0.00014350312,0.0009046833,0.00032287682,1.6745086e-7],"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":[0.00006006881,0.000056672783,0.00014989293,0.00045623834,0.0001841503,0.00039268972,0.00020090537,0.8345263,0.0003623928,0.115532786,0.0018118771,0.04626604],"study_design_scores_gemma":[0.00085539673,0.0003891286,0.000020225772,0.00032830253,0.00005350821,0.002262306,0.0040583163,0.9653488,0.000043209177,0.0004505503,0.02593885,0.00025143218],"about_ca_topic_score_codex":0.000018263601,"about_ca_topic_score_gemma":8.992761e-7,"teacher_disagreement_score":0.91252303,"about_ca_system_score_codex":0.00020142393,"about_ca_system_score_gemma":0.000036534497,"threshold_uncertainty_score":0.60682076},"labels":[],"label_agreement":null},{"id":"W611711171","doi":"10.5383/juspn.05.01.003","title":"Dynamic Service Composition for Telecommunication Services and Its Challenges","year":2013,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Service provider; Provisioning; Computer science; Telecommunications; Service (business); Computer network; Telecommunications service; Middleware (distributed applications); The Internet; Mobile QoS; Service-oriented architecture; Data as a service; Web service; World Wide Web; Business; Distributed computing","score_opus":0.012581032426510663,"score_gpt":0.23151009646935597,"score_spread":0.21892906404284532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W611711171","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":[0.7538183,0.14909834,0.08162433,0.012175697,0.0016307739,0.0013436734,0.000007702797,0.00008438997,0.00021681114],"genre_scores_gemma":[0.98756766,0.007817481,0.0031884792,0.0009811847,0.00037196244,0.000039702696,0.000007001179,0.000016834432,0.000009681119],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985944,0.00015549948,0.00052000117,0.00024635228,0.00020893062,0.000274805],"domain_scores_gemma":[0.9976953,0.00033590654,0.00060633884,0.00030038573,0.00089101,0.00017104021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041742634,0.00020892077,0.0003851464,0.00013976614,0.0002570884,0.0003511961,0.0006823157,0.00014843422,0.0000016595171],"category_scores_gemma":[0.0000022917502,0.00016415896,0.00006670759,0.00017831792,0.0000141706705,0.0009068889,0.00019723541,0.00023260605,0.000002266977],"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":[0.00072889804,0.0013216354,0.0027280382,0.024442637,0.0028364714,0.000090947375,0.12288952,0.13900721,0.043999232,0.08234046,0.0013086267,0.5783063],"study_design_scores_gemma":[0.00111421,0.00066154025,0.008069585,0.0010882156,0.000075976546,0.0009250976,0.0029414422,0.97869796,0.00008819987,0.0012465491,0.0047338097,0.0003574191],"about_ca_topic_score_codex":0.00018999235,"about_ca_topic_score_gemma":0.0003191762,"teacher_disagreement_score":0.83969074,"about_ca_system_score_codex":0.000025543837,"about_ca_system_score_gemma":0.000027503398,"threshold_uncertainty_score":0.66942084},"labels":[],"label_agreement":null}]}