{"id":"W4406549050","doi":"10.3390/s25020518","title":"LoRa Resource Allocation Algorithm for Higher Data Rates","year":2025,"lang":"en","type":"article","venue":"Sensors","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Resource allocation; Algorithm; Resource (disambiguation); Data mining; Computer network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001233412,0.00007363004,0.000080235,0.00003162085,0.00003972656,0.00003091043,0.0001608845,0.0000580808,0.0000233807],"category_scores_gemma":[0.000008055172,0.00007170042,0.00001724252,0.0001149891,0.00001021268,0.00004481981,0.00003182904,0.00006047337,0.00001939047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001604178,"about_ca_system_score_gemma":0.000006692552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005494609,"about_ca_topic_score_gemma":0.000002662121,"domain_scores_codex":[0.9995761,0.00001245737,0.0001021071,0.0001288247,0.00004159601,0.0001389285],"domain_scores_gemma":[0.9995363,0.00006995747,0.00001017289,0.0003455509,0.00001894399,0.00001905136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001594469,0.00001451703,0.00004252119,0.0001478925,0.00009211311,0.000002069082,0.0000672862,0.08106685,0.0002690146,0.001577826,0.476234,0.4404699],"study_design_scores_gemma":[0.0001338244,0.000005051504,0.00009092598,0.00002321788,0.00000673482,1.547473e-7,0.000009113111,0.4331255,0.0007542855,0.0002464453,0.5655494,0.00005528726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01728388,0.00394125,0.7786406,0.006010693,0.006583972,0.0379682,0.0006243836,0.00356133,0.1453858],"genre_scores_gemma":[0.3671351,0.00039366,0.3542604,0.004968584,0.01233216,0.01510758,0.006556037,0.0007531475,0.2384933],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4404146,"threshold_uncertainty_score":0.2923858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839258459042791,"score_gpt":0.2971185884786924,"score_spread":0.2687260038882645,"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."}}