{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"8daf2fc1b116","filters":{"venue":"Frontiers in Computing and Intelligent Systems"}},"results":[{"id":"W4392785361","doi":"10.54097/astapa66","title":"Research on Data Security and Privacy Protection in the Context of Big Data","year":2024,"lang":"en","type":"article","venue":"Frontiers in Computing and Intelligent Systems","topic":"Medical Research and Treatments","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Data Protection Act 1998; Internet privacy; Big data; Computer security; Context (archaeology); Information privacy; Data security; Privacy protection; Computer science; Business; Data mining; Encryption; Geography","authors":[{"name":"Wenjun Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3123620869535642,"gpt":0.4471937525700636,"spread":0.1348316656164993,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004878879,0.00008602983,0.0002425913,0.0003318999,0.00005723857,0.00007266301,0.0003608247,0.00006765456,0.000001329513],"category_scores_gemma":[0.0008728174,0.00005226862,0.00001063043,0.0004091954,0.0001614025,0.00005617043,0.0003840228,0.0006037764,0.000003381748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007437505,"about_ca_system_score_gemma":0.0001050887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001644749,"about_ca_topic_score_gemma":0.00003165319,"domain_scores_codex":[0.9979694,0.0004663716,0.00031254,0.0004449492,0.0005613682,0.0002454009],"domain_scores_gemma":[0.9986368,0.0004434111,0.00002865956,0.000760062,0.00004036216,0.00009063591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004642773,0.0005433736,0.04513839,0.003744421,0.0002135498,0.0003131702,0.008003132,0.000006320538,0.00002360846,0.0009981366,0.04360877,0.8969429],"study_design_scores_gemma":[0.001223783,0.001298729,0.003809594,0.009005554,0.00003319396,0.0001103076,0.02687109,0.8957443,0.0001523688,0.0008141033,0.0607947,0.0001423091],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9123803,0.05165823,0.02418659,0.003299235,0.002667048,0.003786159,0.0001267261,0.00004564039,0.001850105],"genre_scores_gemma":[0.9983996,0.001128812,0.00008322385,0.00002190468,0.0002046922,0.0000104029,0.00008250532,0.000007646486,0.00006117459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8968005,"threshold_uncertainty_score":0.2623142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4311300305","doi":"10.54097/fcis.v2i1.3162","title":"A Review of Security Research on the Internet of Things, Based on Artificial Intelligence and Blockchain","year":2022,"lang":"en","type":"review","venue":"Frontiers in Computing and Intelligent Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Blockchain; Internet of Things; Computer science; Computer security; Key (lock); Intrusion detection system; Cryptography; The Internet; World Wide Web","authors":[{"name":"Ni Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1050603091636239,"gpt":0.3565495524644708,"spread":0.2514892433008469,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00816134,0.000328935,0.001451152,0.0008204784,0.0001859231,0.00005725442,0.001826947,0.0002518615,0.000006139001],"category_scores_gemma":[0.0004390304,0.0002381202,0.0001580637,0.001535484,0.0004157762,0.00002078879,0.0008038809,0.001572902,0.000001696144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001433238,"about_ca_system_score_gemma":0.0001434963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000141757,"about_ca_topic_score_gemma":0.000001123626,"domain_scores_codex":[0.9952453,0.001675378,0.001390938,0.000792433,0.0005534253,0.0003424867],"domain_scores_gemma":[0.9958719,0.002086186,0.0007324239,0.001132876,0.0001161891,0.00006042066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005033742,0.0001778022,0.000005878199,0.03193722,0.00004458145,0.000003316397,0.0006596902,0.00006675951,2.632252e-8,0.1175614,0.002069353,0.8474689],"study_design_scores_gemma":[0.00002444205,0.0004397409,1.818164e-7,0.09912103,0.00003690338,0.00001760631,0.0005374388,0.5238631,0.00001653995,0.005486725,0.3701795,0.0002768374],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001626881,0.8649475,0.1325981,0.0002128573,0.000539396,0.001400107,0.000008111777,0.0000398579,0.000237774],"genre_scores_gemma":[0.006026476,0.9922918,0.001352022,0.0001216906,0.00003436846,0.0001396548,0.000006074872,0.0000188636,0.000009045471],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.847192,"threshold_uncertainty_score":0.9710261,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388813328","doi":"10.54097/fcis.v5i3.14055","title":"Using IGMP Protocol to Improve the Latency of Cloud Computing","year":2023,"lang":"en","type":"article","venue":"Frontiers in Computing and Intelligent Systems","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cloud computing; Latency (audio); Server; Computer network; Distributed computing; The Internet; Operating system","authors":[{"name":"Jing Zhong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04162219016330913,"gpt":0.3128993400945768,"spread":0.2712771499312676,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002362382,0.000270299,0.0004997107,0.0004498442,0.0003611644,0.0002598806,0.001044979,0.0001044432,1.987046e-7],"category_scores_gemma":[0.0001117894,0.0002124637,0.00009496013,0.001589289,0.00007614945,0.0001276065,0.0009520148,0.0003037214,0.00001247137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083027,"about_ca_system_score_gemma":0.00007811458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002988437,"about_ca_topic_score_gemma":7.722151e-7,"domain_scores_codex":[0.9970976,0.0002718502,0.0009505384,0.0006140691,0.000380685,0.0006853003],"domain_scores_gemma":[0.9985826,0.0002505115,0.0003436822,0.0005661793,0.0001332898,0.0001237582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008769266,0.0002513543,0.1141024,0.002305452,0.0002622534,0.00008751301,0.04276232,0.214154,0.001731886,0.006559303,0.07474588,0.54295],"study_design_scores_gemma":[0.000215826,0.0001022941,0.0008350949,0.0006140263,0.000004910588,0.00001697854,0.0006862498,0.9878894,0.0006507816,0.0003609117,0.008363921,0.000259587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06946194,0.000165888,0.8924655,0.0001362721,0.02435248,0.01281223,4.67292e-7,0.0002469344,0.0003583333],"genre_scores_gemma":[0.9269289,0.00001039955,0.06715766,0.000192466,0.00459475,0.0008007857,0.000002736184,0.000071654,0.0002405978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.857467,"threshold_uncertainty_score":0.8664019,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4392785352","doi":"10.54097/fx3btx22","title":"Behavior Prediction of Vespa mandarinia based on Convolutional Neural Networks","year":2024,"lang":"en","type":"article","venue":"Frontiers in Computing and Intelligent Systems","topic":"Insect and Arachnid Ecology and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Machine learning","authors":[{"name":"Shihao Wu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01084503816324806,"gpt":0.245828970980697,"spread":0.2349839328174489,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002469152,0.0001052005,0.0001408583,0.00009707061,0.0000630404,0.00002373009,0.00006297814,0.0001514811,0.000003151168],"category_scores_gemma":[0.000008291646,0.00009659617,0.00005345227,0.00006861465,0.00007772182,0.000002924587,0.00002459285,0.0001393852,6.849852e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001905637,"about_ca_system_score_gemma":0.00002397209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001339664,"about_ca_topic_score_gemma":0.000001535059,"domain_scores_codex":[0.999227,0.00006163479,0.0002500344,0.0002358935,0.0000721824,0.0001532732],"domain_scores_gemma":[0.9997878,0.00001600604,0.00004244069,0.00009657269,0.00002491531,0.00003228403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003615868,0.000322362,0.8325936,0.0002673791,0.00007627867,0.00003728664,0.000148798,0.1246815,0.007839164,0.0002674001,0.01365241,0.01975225],"study_design_scores_gemma":[0.000207426,0.0004748589,0.02378464,0.0001518356,0.00002871404,0.00001948094,0.00008905838,0.9707371,0.002332964,0.000003824569,0.002054767,0.0001153435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9062205,0.00284067,0.08472356,0.00001374518,0.005848244,0.0002128186,0.00002411486,0.00002105507,0.00009530866],"genre_scores_gemma":[0.9991432,0.00004078308,0.0001498811,0.00002758961,0.0003685453,0.00001391539,0.0001003938,0.000009767075,0.0001459049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8460556,"threshold_uncertainty_score":0.3939077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410878489","doi":"10.54097/6f8s2419","title":"Olympic Medal Count Prediction Model for Various Countries based on LSTM and Supervised Machine Learning","year":2025,"lang":"en","type":"article","venue":"Frontiers in Computing and Intelligent Systems","topic":"Diverse Approaches in Healthcare and Education Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Medal; Artificial intelligence; Machine learning; Computer science; History; Art history","authors":[{"name":"Saijie Wang","is_ca":false},{"name":"Dongyang He","is_ca":false},{"name":"Hongjia Li","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03906753435359512,"gpt":0.3040560953380902,"spread":0.2649885609844951,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000706176,0.0001523071,0.0003862694,0.0002636608,0.0002539706,0.00004998633,0.00004401229,0.00009850452,7.999577e-7],"category_scores_gemma":[0.0001271636,0.0001363159,0.00003556615,0.0001252717,0.00007874942,0.00003039592,0.00002944576,0.0001857121,4.803388e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888723,"about_ca_system_score_gemma":0.0001256163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002120119,"about_ca_topic_score_gemma":0.000003658762,"domain_scores_codex":[0.9988624,0.00006537757,0.0003754563,0.0003160464,0.0001607273,0.000220028],"domain_scores_gemma":[0.99942,0.000201739,0.00007310538,0.0001219988,0.0001173064,0.00006584067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005235123,0.0001533651,0.9018796,0.002430079,0.0001604889,0.000002280402,0.005090626,0.06586449,0.000002701762,0.001349176,0.007966342,0.01457736],"study_design_scores_gemma":[0.0008255116,0.0002021405,0.002244657,0.0007575062,0.00006105874,0.000003651187,0.003762956,0.9864032,0.0000148988,0.00007526619,0.005557076,0.00009209633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1622237,0.01007225,0.820864,0.00104652,0.003467555,0.001310208,0.00003165512,0.0001150296,0.0008690412],"genre_scores_gemma":[0.9946045,0.0006462657,0.00314049,0.0004630355,0.0001123754,0.00004743877,0.00004457936,0.00001224981,0.0009290854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9205387,"threshold_uncertainty_score":0.55588,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}