{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":6,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":6,"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":"704d570fba8c","filters":{"venue":"EAI Endorsed Transactions on Internet of Things"}},"results":[{"id":"W4389765855","doi":"10.4108/eetiot.4604","title":"Enhancing Crop Growth Efficiency through IoT-enabled Smart Farming System","year":2023,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Sustainability; Agricultural engineering; Computer science; Agriculture; Precision agriculture; Business; Environmental economics; Engineering","authors":[{"name":"Neha Jadhav","is_ca":true},{"name":"B Rajnivas","is_ca":false},{"name":"V. Subaprıya","is_ca":false},{"name":"S. Sivaramakrishnan","is_ca":true},{"name":"S. Premalatha","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01273477795047504,"gpt":0.2096005998323391,"spread":0.1968658218818641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001616137,0.0002334682,0.0002424177,0.0002844466,0.0002070862,0.0005151694,0.0003971751,0.0004161425,0.001203561],"category_scores_gemma":[0.0002204834,0.0001051892,0.0002026126,0.0002943722,0.0001318133,0.0007661777,0.0004005649,0.0001635169,0.0005181933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001670405,"about_ca_system_score_gemma":0.0002244275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000460359,"about_ca_topic_score_gemma":0.0007571591,"domain_scores_codex":[0.9998798,0.00001688936,0.00001006784,0.00003531871,0.0000375828,0.00002042718],"domain_scores_gemma":[0.9998813,0.00002372847,0.00002483687,0.00002011748,0.00003881963,0.0000111885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004780267,0.0005331378,0.01734936,0.0004774251,0.00009641414,0.001269025,0.0003807303,0.08377047,0.6304967,0.004441999,0.00573707,0.2549695],"study_design_scores_gemma":[0.0001182986,0.001046097,0.0270559,0.00008968257,0.0001635201,0.0007442817,0.0004113482,0.7287618,0.1974466,0.005027655,0.03903584,0.00009893375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6550701,0.0004891625,0.3127745,0.0005524334,0.000195745,0.0003062883,0.0006228071,0.003380795,0.02660811],"genre_scores_gemma":[0.9581131,0.0002494623,0.0376892,0.0001212675,0.00001821847,0.0001104073,0.0002240063,0.00002482409,0.003449406],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001203561,"threshold_uncertainty_score":0.004026353,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4224930295","doi":"10.4108/eetiot.v7i28.685","title":"A facial expression recognizer using modified ResNet-152","year":2022,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Facial expression recognition; Computer science; Facial expression; Speech recognition; Expression (computer science); Artificial intelligence; Residual neural network; Emotion recognition; Facial recognition system; Mainstream; Pattern recognition (psychology); Deep learning","authors":[{"name":"Wenle Xu","is_ca":false},{"name":"Rayan S Cloutier","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02971128683699219,"gpt":0.2529198750965703,"spread":0.2232085882595781,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005248504,0.0009826467,0.0006870397,0.0008419842,0.0002996241,0.0003817489,0.0009092656,0.000437541,0.004626713],"category_scores_gemma":[0.0004692665,0.0002712042,0.0006208411,0.0004046568,0.0001618022,0.0007017119,0.0003582187,0.0005625056,0.002670048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004664344,"about_ca_system_score_gemma":0.0004688475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006016696,"about_ca_topic_score_gemma":0.00652726,"domain_scores_codex":[0.9997037,0.0000341955,0.00002194125,0.00008737799,0.000101633,0.0000511115],"domain_scores_gemma":[0.9999005,0.00001347578,0.000006881103,0.00001600437,0.00005322005,0.000009999912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007348029,0.0005404099,0.002052231,0.0001944353,0.0002149987,0.0004913342,0.00008950229,0.01871951,0.182289,0.002436071,0.02183395,0.7704038],"study_design_scores_gemma":[0.0001124031,0.0007589436,0.007582965,0.00003593247,0.0001865362,0.0008408868,0.00006723505,0.8347629,0.1371314,0.002174376,0.01624165,0.0001047182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2260601,0.001965765,0.7118013,0.0007383812,0.001528795,0.001215713,0.002912211,0.02531709,0.02846065],"genre_scores_gemma":[0.6550753,0.0009075986,0.3108696,0.0007711995,0.000236352,0.0008536673,0.005358359,0.0004710006,0.02545694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006016696,"threshold_uncertainty_score":0.0154779,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400508553","doi":"10.4108/eetiot.6574","title":"Mitigating Adversarial Reconnaissance in IoT Anomaly Detection Systems: A Moving Target Defense Approach based on Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adversarial system; Anomaly detection; Reinforcement learning; Computer science; Artificial intelligence; Internet of Things; Anomaly (physics); Computer security; Machine learning","authors":[{"name":"Arnold Brendan Osei","is_ca":true},{"name":"Yaser Al Mtawa","is_ca":true},{"name":"Talal Halabi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01096985263195278,"gpt":0.2145043552474633,"spread":0.2035345026155105,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001538987,0.0005395593,0.000673153,0.0003970853,0.0002792581,0.0004819257,0.00107486,0.0007219611,0.0006181667],"category_scores_gemma":[0.004171336,0.0001976381,0.0003278117,0.0002393165,0.0009057088,0.000958748,0.0009424938,0.001124626,0.0001052293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007142002,"about_ca_system_score_gemma":0.0008293067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001876933,"about_ca_topic_score_gemma":0.001562619,"domain_scores_codex":[0.9993999,0.0002308563,0.00002389393,0.0001281437,0.0001331785,0.00008396325],"domain_scores_gemma":[0.9977651,0.001303054,0.0003171894,0.0002090034,0.0002812287,0.0001244441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004023089,0.00006442349,0.000981493,0.00002092572,0.0000224402,0.00004192321,0.0000319892,0.960303,0.002558217,0.004852996,0.0003016957,0.0307806],"study_design_scores_gemma":[0.000002786892,0.00002952179,0.00007566024,0.000001439357,0.000002594324,0.00001225852,0.000003298286,0.9980916,0.0004190784,0.001255236,0.0001043329,0.000002131582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04572052,0.0001579996,0.9523716,0.0002889921,0.0000286512,0.00004188922,0.00001146969,0.0002543569,0.001124526],"genre_scores_gemma":[0.9524946,0.00008265729,0.04657365,0.0000966617,0.00002270201,0.00003300094,0.00001424343,0.00001779169,0.0006645878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001876933,"threshold_uncertainty_score":0.008139074,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4224247521","doi":"10.4108/eetiot.v7i28.562","title":"A Review of Image Classification Algorithms in IoT","year":2022,"lang":"en","type":"review","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Contextual image classification; Deep learning; Image (mathematics); Machine learning; Pattern recognition (psychology); Algorithm","authors":[{"name":"Xiaopeng Zheng","is_ca":false},{"name":"Rayan S Cloutier","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09562636689838824,"gpt":0.3447139841280424,"spread":0.2490876172296542,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069446,0.001098125,0.0009807084,0.0032762,0.0004636764,0.001531823,0.001308403,0.001456917,0.006078824],"category_scores_gemma":[0.001578989,0.0005591633,0.0008482101,0.004648553,0.0005460258,0.002476109,0.0007482294,0.001390478,0.00464743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006791572,"about_ca_system_score_gemma":0.001164374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001833608,"about_ca_topic_score_gemma":0.001574631,"domain_scores_codex":[0.99959,0.00004844795,0.00005930761,0.00009717523,0.0001708777,0.00003423964],"domain_scores_gemma":[0.9992612,0.0003347014,0.00005362613,0.00004024969,0.0002847787,0.00002543644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003385299,0.00007242883,0.0003059391,0.005746672,0.00004649125,0.00009983528,0.00005235713,0.001196052,0.001064267,0.009966115,0.03383866,0.9475773],"study_design_scores_gemma":[0.000007249906,0.0001221742,0.001139368,0.003288094,0.00009328744,0.0009994551,0.00008071168,0.003478772,0.001498159,0.009513881,0.9797237,0.00005518407],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007215622,0.9672641,0.01548348,0.001122878,0.001226634,0.00005169634,0.0001760334,0.0001654409,0.01378824],"genre_scores_gemma":[0.005579967,0.9744017,0.01211967,0.0006724492,0.001358253,0.00006422766,0.0003866717,0.00003716336,0.005379997],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006078824,"threshold_uncertainty_score":0.02033561,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2793000811","doi":"10.4108/eai.15-1-2018.153566","title":"Secure ID-Based Routing for Data Communication in IoT","year":2017,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Fonds de Recherche du Québec - Santé; Ministry of Science, ICT and Future Planning","keywords":"Internet of Things; Computer science; Authentication (law); Scope (computer science); Computer security; Computer network; Authorization; Routing (electronic design automation); Wireless; Secure communication; The Internet; World Wide Web; Telecommunications; Encryption","authors":[{"name":"Madhusudan Singh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05137526173561943,"gpt":0.2962383500836993,"spread":0.2448630883480798,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001008811,0.0004346817,0.0005057662,0.001056768,0.001232856,0.00166914,0.001113066,0.0009787476,0.002006953],"category_scores_gemma":[0.001854406,0.0002973509,0.0006491839,0.001256315,0.0007712083,0.002292011,0.00140872,0.001475193,0.001093302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128686,"about_ca_system_score_gemma":0.001545695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00132983,"about_ca_topic_score_gemma":0.001412071,"domain_scores_codex":[0.9986138,0.0003787558,0.0001271241,0.0001697345,0.0006042016,0.0001064056],"domain_scores_gemma":[0.9990243,0.0002078984,0.000107594,0.0002841775,0.0003327106,0.00004339101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002588067,0.0002333905,0.002165447,0.001098415,0.0001461633,0.0007149977,0.0005900078,0.04467805,0.03470839,0.4701794,0.04685893,0.398368],"study_design_scores_gemma":[0.0001027624,0.0004688488,0.001493591,0.0003832911,0.0001466321,0.002188072,0.0004331431,0.3905362,0.03231813,0.2546411,0.317102,0.0001862234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01329818,0.008729289,0.9374857,0.002843892,0.001571731,0.0004430254,0.0002609083,0.001744307,0.03362294],"genre_scores_gemma":[0.5344558,0.01139556,0.4202855,0.001317918,0.0005760156,0.0007036835,0.001325887,0.0002251236,0.02971439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002006953,"threshold_uncertainty_score":0.009336889,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396870012","doi":"10.4108/eetiot.6039","title":"A Self-Supervised GCN Model for Link Scheduling in Downlink NOMA Networks","year":2024,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Internet of Things","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; Western University","funders":"","keywords":"Noma; Telecommunications link; Computer science; Scheduling (production processes); Link (geometry); Computer network; Distributed computing; Mathematical optimization; Mathematics","authors":[{"name":"Caiya Zhang","is_ca":true},{"name":"Fang Fang","is_ca":true},{"name":"Congsong Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01381865768747857,"gpt":0.2397460224115837,"spread":0.2259273647241052,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006503435,0.0006006995,0.0005978468,0.0003359287,0.0003547325,0.0006337825,0.001383633,0.001084056,0.001652553],"category_scores_gemma":[0.001628826,0.0003087369,0.0003464593,0.0004816075,0.0008183636,0.0008456075,0.0006124493,0.00126995,0.0002882918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325033,"about_ca_system_score_gemma":0.000891407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01299713,"about_ca_topic_score_gemma":0.01571898,"domain_scores_codex":[0.9997661,0.00007593526,0.00000691398,0.00006477494,0.00004047347,0.00004582241],"domain_scores_gemma":[0.9994412,0.0002724034,0.00008583604,0.00003893391,0.0001242708,0.00003744574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002281622,0.00001480852,0.0002848039,0.0000131211,0.000006523187,0.00002370955,0.00001659325,0.987384,0.0004230135,0.005815554,0.0005496963,0.005445324],"study_design_scores_gemma":[8.585566e-7,0.000002266409,0.00002458387,7.487992e-7,8.854148e-7,0.000001864265,0.000001049993,0.9990473,0.00003036282,0.0008439262,0.00004530065,8.31403e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1098529,0.0005686252,0.8794934,0.0009902559,0.000125899,0.00006262532,0.0003423117,0.0003833695,0.008180531],"genre_scores_gemma":[0.9646018,0.0002267989,0.02856486,0.0001584179,0.00006025596,0.00007962825,0.0001843013,0.00003700149,0.006086986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01299713,"threshold_uncertainty_score":0.02584296,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}