{"id":"W7123490049","doi":"10.1109/iscc65549.2025.11326493","title":"IRSA Over Spreading Factors for Spatio-Temporal SIC in Scalable LoRaWAN IoT Networks","year":2025,"lang":"","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Aloha; Throughput; Network packet; Scalability; Leverage (statistics); Internet of Things; Wireless; Interference (communication); Random access","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009803132,0.0006734286,0.0003947972,0.0005533345,0.0005180205,0.0006401227,0.0006007663,0.0003767314,0.001032687],"category_scores_gemma":[0.002701116,0.0002292917,0.0004758103,0.000655137,0.0009663969,0.0008513554,0.0008274947,0.0007583354,0.0003712113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000642199,"about_ca_system_score_gemma":0.001072995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003057722,"about_ca_topic_score_gemma":0.004769454,"domain_scores_codex":[0.9993575,0.000199722,0.00002546142,0.00006164982,0.0002598078,0.00009574024],"domain_scores_gemma":[0.9989202,0.0005374524,0.0001191003,0.0001247725,0.0002524597,0.00004603038],"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":[0.0002383877,0.00007220932,0.001377875,0.0002308256,0.00008175828,0.0004454015,0.000278316,0.7702238,0.03411985,0.08884279,0.002228745,0.10186],"study_design_scores_gemma":[0.0000109539,0.00008755215,0.0001781566,0.00002163411,0.00001691878,0.0001684565,0.00004944848,0.9805715,0.005003912,0.01212735,0.001743452,0.00002065113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03601639,0.001179978,0.9517045,0.0002306871,0.00008611957,0.00007196513,0.00004891689,0.000482082,0.01017932],"genre_scores_gemma":[0.8848308,0.0009034448,0.1119729,0.000168754,0.00006314109,0.00009234891,0.00006263472,0.00003707596,0.001868833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003057722,"threshold_uncertainty_score":0.006079853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455213332353919,"score_gpt":0.2652634460162779,"score_spread":0.2507113126927387,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}