{"meta":{"query_hash":"83d767524558","filters":{"venue":"International Journal of Wireless Communications and Mobile Computing"},"cohort_total":3,"direct_labels_cover":0,"predictions_cover":3,"exported":3,"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/83d767524558","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Wireless+Communications+and+Mobile+Computing"},"results":[{"id":"W2108795729","doi":"10.11648/j.wcmc.20130104.15","title":"Optimal Resource Allocation for LTE Uplink Scheduling in Smart Grid Communications","year":2013,"lang":"en","type":"article","venue":"International Journal of Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Dynamic priority scheduling; Fair-share scheduling; Smart grid; Distributed computing; Computer network; Quality of service; Round-robin scheduling; Base station; Telecommunications link; Grid; 3rd Generation Partnership Project 2; Mathematical optimization; Engineering","score_opus":0.01488178823185648,"score_gpt":0.27540153578358084,"score_spread":0.26051974755172436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108795729","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16961706,0.00114938,0.82077503,0.0003973672,0.00008712333,0.000100888115,0.000082567065,0.00026472457,0.0075258976],"genre_scores_gemma":[0.95037174,0.0001970292,0.04880669,0.000043297918,0.000020355701,0.000032113927,0.000029524812,0.000016612175,0.00048259084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999488,0.00022094032,0.000019423891,0.000049813916,0.000106340754,0.00011545678],"domain_scores_gemma":[0.9994844,0.00030691593,0.000075437834,0.000032911685,0.00006262132,0.000037687325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007187223,0.00033783366,0.00061244686,0.00040657097,0.00053659466,0.00057853956,0.0003875354,0.0003415686,0.0008553609],"category_scores_gemma":[0.0023618978,0.0002089064,0.00017908978,0.0005288001,0.000480531,0.00068346394,0.0002819768,0.00027748095,0.00010626996],"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":[0.00009767949,0.000029904648,0.0003790511,0.000029013008,0.000009564884,0.000029864605,0.000026664131,0.96996105,0.0018886103,0.0089991065,0.00077841495,0.017771097],"study_design_scores_gemma":[0.000008790307,0.000014084646,0.00008487845,0.00000194769,0.000002371124,0.000008197727,0.000012603405,0.997168,0.00038515197,0.002141019,0.00016992787,0.000002948498],"about_ca_topic_score_codex":0.008084918,"about_ca_topic_score_gemma":0.008719937,"teacher_disagreement_score":0.008084918,"about_ca_system_score_codex":0.0013759532,"about_ca_system_score_gemma":0.0024034018,"threshold_uncertainty_score":0.01607573},"labels":[],"label_agreement":null},{"id":"W2115353956","doi":"10.11648/j.wcmc.20140202.11","title":"Optimal Load Balancing Algorithm for Multi-Cell LTE Networks","year":2014,"lang":"en","type":"article","venue":"International Journal of Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Handover; Load balancing (electrical power); Latency (audio); Computer network; Network packet; Bandwidth (computing); LTE Advanced; Algorithm; Distributed computing; Telecommunications link; Telecommunications; Mathematics; Grid","score_opus":0.011289238741396689,"score_gpt":0.2675107536138493,"score_spread":0.2562215148724526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115353956","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032120958,0.00050977315,0.9630015,0.00025685033,0.00009186236,0.00007524499,0.00004484415,0.00037255918,0.0035263477],"genre_scores_gemma":[0.8047422,0.00037374493,0.19094005,0.0001468242,0.00010805065,0.00020353365,0.00016450888,0.00007595834,0.0032450845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995834,0.00008748721,0.000023112665,0.00007589996,0.00012879203,0.00010126651],"domain_scores_gemma":[0.99951804,0.00019290717,0.00007775683,0.000024605399,0.00014398425,0.000042760894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007210603,0.0009077763,0.0010856899,0.0007508944,0.00084828166,0.0009959466,0.0011777517,0.0009158319,0.002168609],"category_scores_gemma":[0.0014749259,0.00038561504,0.00033237098,0.00073787355,0.00051647704,0.0010205086,0.00093560596,0.00060885074,0.00040439688],"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":[0.00012939771,0.000047759277,0.0004350351,0.000038277118,0.000019462976,0.000042932734,0.000054663407,0.9419733,0.0022587765,0.0034196482,0.0014034348,0.050177198],"study_design_scores_gemma":[0.000009697833,0.000011663232,0.000044339216,0.0000016380959,0.000001951508,0.000006599348,0.000006308984,0.9989303,0.00013084261,0.00070159184,0.00015308363,0.0000020303119],"about_ca_topic_score_codex":0.0061331317,"about_ca_topic_score_gemma":0.0048579546,"teacher_disagreement_score":0.0061331317,"about_ca_system_score_codex":0.0010116334,"about_ca_system_score_gemma":0.0013181644,"threshold_uncertainty_score":0.012194872},"labels":[],"label_agreement":null},{"id":"W4416904534","doi":"10.11648/j.wcmc.20251202.14","title":"Slice-Specific Machine Learning Models for Intrusion Detection in 5G Telecommunication Networks","year":2025,"lang":"en","type":"article","venue":"International Journal of Wireless Communications and Mobile Computing","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Island Health","funders":"","keywords":"Intrusion detection system; Support vector machine; Software deployment; Random forest; Confusion matrix; Network security; Cellular network","score_opus":0.021522358098128327,"score_gpt":0.2798013770270883,"score_spread":0.25827901892896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416904534","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30717823,0.004376089,0.68074346,0.0009881745,0.00031752794,0.0001504628,0.0012047107,0.0021649478,0.0028764543],"genre_scores_gemma":[0.9488667,0.00092503073,0.046798863,0.00017155,0.00008713153,0.00010126326,0.0012656779,0.00004787276,0.0017359734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995289,0.00013665677,0.000030839234,0.00014337167,0.0000743569,0.000085838976],"domain_scores_gemma":[0.998968,0.00048439766,0.0001417875,0.00010005353,0.00026995834,0.000035752157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011198049,0.0012173894,0.0008713914,0.0007428083,0.00026860088,0.0007853007,0.00090882,0.00073527393,0.0007260594],"category_scores_gemma":[0.0028305207,0.0002462277,0.0008369017,0.0006127286,0.00036621248,0.0012844775,0.00060352846,0.0013039018,0.00038878093],"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":[0.0003923482,0.00014698473,0.01182387,0.000117404335,0.00018321037,0.00018498996,0.00013537458,0.82070494,0.004439003,0.004104246,0.0034180009,0.15434965],"study_design_scores_gemma":[0.0000025539025,0.00005218805,0.00089608104,0.000009768686,0.00001569108,0.000033011285,0.000019133802,0.9960955,0.00075569755,0.0017505715,0.0003628848,0.000006999158],"about_ca_topic_score_codex":0.007252553,"about_ca_topic_score_gemma":0.008217489,"teacher_disagreement_score":0.007252553,"about_ca_system_score_codex":0.00075321645,"about_ca_system_score_gemma":0.0006264103,"threshold_uncertainty_score":0.014420688},"labels":[],"label_agreement":null}]}