{"meta":{"query_hash":"68976e0a0637","filters":{"venue":"International Journal of Communication Networks and Information Security (IJCNIS)"},"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/68976e0a0637","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Communication+Networks+and+Information+Security+%28IJCNIS%29"},"results":[{"id":"W2904885747","doi":"10.17762/ijcnis.v10i3.3624","title":"BotCap: Machine Learning Approach for Botnet Detection Based on Statistical Features","year":2022,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Information Security (IJCNIS)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Botnet; Computer science; Artificial intelligence; Network packet; Machine learning; Set (abstract data type); Deep packet inspection; Data mining; Computer security; The Internet; World Wide Web","score_opus":0.007643147577651825,"score_gpt":0.2393358168784427,"score_spread":0.23169266930079085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904885747","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012166423,0.00023648086,0.9726283,0.00014881216,0.000069660775,0.00017714639,0.00040986523,0.01268418,0.0014790433],"genre_scores_gemma":[0.30309036,0.00028681036,0.68828726,0.0002958518,0.00013076875,0.0004488549,0.0017095682,0.00054924225,0.0052012717],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930835,0.00013127142,0.00003299189,0.00015607596,0.00030247978,0.00006881486],"domain_scores_gemma":[0.9989361,0.0004849382,0.00012299747,0.0001652163,0.00022991141,0.0000607802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010052832,0.0013766459,0.00095411926,0.0029882323,0.0006227805,0.0008291384,0.0015624267,0.0014131368,0.0026604976],"category_scores_gemma":[0.0022132252,0.00049956195,0.00074762676,0.0014058696,0.0004892579,0.0014040285,0.0010496641,0.0016769441,0.0012392121],"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":[0.0002724566,0.0010448882,0.009530293,0.0004048781,0.00040522788,0.00041024355,0.00013084247,0.15412451,0.031622697,0.0118719805,0.018519603,0.77166235],"study_design_scores_gemma":[0.000014783237,0.00007895518,0.0013711896,0.000012064795,0.000020989584,0.00015436752,0.000013713288,0.9807165,0.0077850316,0.0059682736,0.0038414674,0.00002252799],"about_ca_topic_score_codex":0.0017974826,"about_ca_topic_score_gemma":0.0023489906,"teacher_disagreement_score":0.0029882323,"about_ca_system_score_codex":0.0006574892,"about_ca_system_score_gemma":0.0008036489,"threshold_uncertainty_score":0.008900225},"labels":[],"label_agreement":null},{"id":"W4282030205","doi":"10.17762/ijcnis.v14i1.5065","title":"Lightweight Scheme for Smart Home Environments using Offloading Technique","year":2022,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Information Security (IJCNIS)","topic":"IoT and Edge/Fog Computing","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":"École de Technologie Supérieure; Université du Québec","funders":"","keywords":"Computer science; Cloud computing; Computer security; Service provider; Access control; Encryption; Home automation; Wearable technology; Analytics; Wearable computer; Service (business); Internet privacy; Telecommunications; Embedded system; Data science; Business","score_opus":0.011322084677498798,"score_gpt":0.2488517455381488,"score_spread":0.23752966086065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282030205","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":[0.10824355,0.00094083353,0.8549649,0.0006809889,0.0006314118,0.00048260222,0.00020764976,0.0025754708,0.03127265],"genre_scores_gemma":[0.8769751,0.00035188394,0.10458467,0.00026115627,0.00013920192,0.00024037744,0.00027059167,0.00009800451,0.01707895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991961,0.00018027134,0.00006596804,0.0001055931,0.0002209881,0.0002311],"domain_scores_gemma":[0.9992913,0.00013168459,0.00005865684,0.0003210097,0.00013759515,0.000059811464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033482365,0.00052331557,0.0008502691,0.000473573,0.0014183836,0.0010389605,0.0008662072,0.0007874078,0.006531488],"category_scores_gemma":[0.00090971147,0.00014537894,0.00048817418,0.00047565476,0.0005793157,0.0023697184,0.0025069343,0.00085966865,0.0017539322],"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":[0.0025625885,0.00076650566,0.0018726212,0.0005281231,0.00012236285,0.0020435688,0.0013837939,0.03821111,0.19976845,0.22019476,0.021342685,0.51120347],"study_design_scores_gemma":[0.00036067053,0.0013610045,0.0024811535,0.00016788421,0.00016098634,0.0044364803,0.0010952699,0.67365336,0.09728326,0.14184046,0.076919906,0.00023956626],"about_ca_topic_score_codex":0.00068143144,"about_ca_topic_score_gemma":0.00077905675,"teacher_disagreement_score":0.006531488,"about_ca_system_score_codex":0.0005169634,"about_ca_system_score_gemma":0.00055211515,"threshold_uncertainty_score":0.02184999},"labels":[],"label_agreement":null},{"id":"W4312440284","doi":"10.17762/ijcnis.v8i3.1420","title":"Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks","year":2022,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Information Security (IJCNIS)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Multipath routing; Wireless Routing Protocol; Cognitive radio; Dynamic Source Routing; Optimized Link State Routing Protocol; Zone Routing Protocol; Link-state routing protocol; Destination-Sequenced Distance Vector routing; Routing protocol; Robustness (evolution); Distributed computing; Routing (electronic design automation); Wireless; Telecommunications","score_opus":0.013363654180158717,"score_gpt":0.27904077490865714,"score_spread":0.2656771207284984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312440284","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":[0.02246769,0.008445841,0.9540863,0.0008890851,0.0007671867,0.00026649874,0.00014971025,0.0015102804,0.01141756],"genre_scores_gemma":[0.7291664,0.007028405,0.25362736,0.0005598509,0.00031607304,0.0005594821,0.00045465323,0.0001001179,0.008187766],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995459,0.00011274726,0.00003258583,0.000072108225,0.00017283666,0.00006384366],"domain_scores_gemma":[0.9994754,0.00017541168,0.000084754574,0.00007153344,0.00016308088,0.000029859868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045944692,0.0005960927,0.0004782355,0.0006941768,0.00072095345,0.0007230541,0.0009987549,0.0005772892,0.0009854819],"category_scores_gemma":[0.0013655032,0.00017981064,0.00041147767,0.00077624194,0.00037550967,0.00087820896,0.000875014,0.0008228704,0.00029261722],"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":[0.00042314132,0.00014568919,0.0012139713,0.00081945397,0.0002839528,0.001015558,0.00035634075,0.21132627,0.063269116,0.10573368,0.018005358,0.59740746],"study_design_scores_gemma":[0.00010783918,0.0006500459,0.0011747531,0.0001357477,0.00023764123,0.0018719726,0.00019665336,0.81719124,0.025419919,0.056415476,0.096408576,0.00019022744],"about_ca_topic_score_codex":0.0014581626,"about_ca_topic_score_gemma":0.002166966,"teacher_disagreement_score":0.0014581626,"about_ca_system_score_codex":0.0006644432,"about_ca_system_score_gemma":0.00096651574,"threshold_uncertainty_score":0.0048208833},"labels":[],"label_agreement":null}]}