{"id":"W4409359489","doi":"10.1016/j.phycom.2025.102672","title":"Moment based analysis over generalized fading accompanying hypergeometric and exponential functions with diversity","year":2025,"lang":"en","type":"article","venue":"Physical Communication","topic":"Radio Wave Propagation Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Univerzita Hradec Králové","keywords":"Fading; Confluent hypergeometric function; Computer science; Exponential function; Moment (physics); Hypergeometric function; Diversity (politics); Applied mathematics; Diversity scheme; Mathematics; Telecommunications; Mathematical analysis; Physics; Law","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":[0.00007708216,0.00009607093,0.0001870427,0.0003701465,0.0004039419,0.00003930874,0.0001294425,0.00001798204,0.00001055274],"category_scores_gemma":[0.00001057414,0.00009053768,0.00005967985,0.001517865,0.00004551832,0.0001348901,0.0001811518,0.0001051236,0.00000373703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009440372,"about_ca_system_score_gemma":0.000004653817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006434622,"about_ca_topic_score_gemma":0.00002149216,"domain_scores_codex":[0.9994926,0.00005312069,0.0001067538,0.0001184078,0.0001291026,0.00009994626],"domain_scores_gemma":[0.9994181,0.0001316375,0.00002956021,0.0003440619,0.00004908992,0.00002755363],"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":[0.0001189101,0.0005414864,0.1536003,0.0001641654,0.006211581,8.259917e-7,0.001997176,0.7840377,0.0192665,0.002507997,0.001384418,0.03016894],"study_design_scores_gemma":[0.0006988513,0.000009088434,0.2546378,0.0000165188,0.0006928058,8.337659e-8,0.00009707153,0.7419608,0.001163155,0.0001397156,0.0004395212,0.0001446286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.888942,0.0003432242,0.1094961,0.000105951,0.00002096811,0.00009474945,0.000004387395,0.0001280108,0.0008645345],"genre_scores_gemma":[0.9983658,0.00006151258,0.001419425,0.00002459239,0.00001223553,0.00002870282,0.00003395214,0.000006446548,0.0000473661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1094237,"threshold_uncertainty_score":0.369202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0154372733332704,"score_gpt":0.2396255277537808,"score_spread":0.2241882544205104,"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."}}