{"id":"W4402968346","doi":"10.1109/ap-s/inc-usnc-ursi52054.2024.10686997","title":"Path Loss Analysis for Near-Ground Mining Communication at 2.4 GHz","year":2024,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Path loss; Computer science; Path (computing); Telecommunications; Computer network; Wireless","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":[0.000289344,0.0004131507,0.0002273397,0.0005263265,0.0002054411,0.0003235886,0.0003249228,0.0002908047,0.001258792],"category_scores_gemma":[0.00120364,0.0001260201,0.0002528177,0.0005797565,0.0002127192,0.0007346201,0.0003152893,0.0003164188,0.0004553615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003869453,"about_ca_system_score_gemma":0.0001976935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008970214,"about_ca_topic_score_gemma":0.0007750416,"domain_scores_codex":[0.9996818,0.00006518131,0.000006986124,0.00004377076,0.0001457715,0.00005640477],"domain_scores_gemma":[0.9993826,0.0003051645,0.0001116359,0.00004482504,0.0001404108,0.00001522943],"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":[0.0006568388,0.0001262573,0.02677323,0.0002559949,0.0001398038,0.001286792,0.0004769085,0.7371356,0.1235363,0.006053349,0.002400538,0.1011583],"study_design_scores_gemma":[0.00002021184,0.0005460809,0.02489554,0.0000320741,0.00006112358,0.00153888,0.0004518621,0.9402611,0.02453365,0.003621516,0.003988716,0.00004914008],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7281999,0.000935949,0.2624456,0.0003211508,0.00004489056,0.00004290307,0.0002922043,0.0005119984,0.007205453],"genre_scores_gemma":[0.9932509,0.0003265168,0.00492113,0.00004229402,0.00001074693,0.00002262543,0.0001361236,0.00002800801,0.001261646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001258792,"threshold_uncertainty_score":0.004211068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03083410839391713,"score_gpt":0.2572737571256393,"score_spread":0.2264396487317222,"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."}}