{"id":"W4391492101","doi":"10.1109/tim.2024.3351262","title":"Understanding LoRaWAN Transmissions in Harsh Environments: A Measurement-Based Campaign Through Unmanned Aerial/Surface Vehicles","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Ministry of Agriculture and Rural Development","keywords":"Default gateway; Computer science; Data collection; Range (aeronautics); Transmission (telecommunications); Data acquisition; Real-time computing; Data transmission; Gateway (web page); Computer network; Engineering; Telecommunications; Aerospace engineering","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":[0.0005068344,0.0004074822,0.000413309,0.0006673203,0.0003833227,0.0003426124,0.0004429503,0.0004034542,0.0002323499],"category_scores_gemma":[0.00125313,0.0001345095,0.0002706946,0.0006422187,0.0004152081,0.0005885546,0.0003657143,0.0006099168,0.0001516771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004692229,"about_ca_system_score_gemma":0.0003551057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006951813,"about_ca_topic_score_gemma":0.008407176,"domain_scores_codex":[0.9994897,0.000131255,0.00002441183,0.00008648986,0.000177062,0.00009107175],"domain_scores_gemma":[0.9992076,0.0002473574,0.0001184103,0.0001142381,0.0002466131,0.0000658905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005813507,0.001983171,0.2519906,0.000519647,0.0003284013,0.002924778,0.003050441,0.5340425,0.04919619,0.005667638,0.008612144,0.1411031],"study_design_scores_gemma":[0.0001006772,0.001415833,0.2723131,0.00008077738,0.0001026997,0.0007181856,0.003133458,0.6770737,0.03212304,0.001373469,0.01144178,0.0001233232],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893408,0.00009200253,0.008077678,0.0000870423,0.00001883393,0.00005032556,0.0004828562,0.0001531506,0.001697198],"genre_scores_gemma":[0.9960421,0.00008176349,0.002881204,0.00001723413,0.000009626007,0.00002789831,0.0006461515,0.000009975529,0.0002840641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006951813,"threshold_uncertainty_score":0.01382267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1177866815383923,"score_gpt":0.2635150644976303,"score_spread":0.145728382959238,"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."}}