{"id":"W2165828402","doi":"10.1109/glocomw.2010.5700087","title":"Diversity gains for MIMO wireless optical intensity channels with atmospheric fading and misalignment","year":2010,"lang":"en","type":"article","venue":"","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Fading; MIMO; Diversity gain; Computer science; Channel (broadcasting); Diversity scheme; Electronic engineering; Diversity combining; Optical wireless; Antenna diversity; Wireless; Free-space optical communication; Maximal-ratio combining; Time diversity; Diversity (politics); Channel state information; Optical communication; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008331084,0.0001287169,0.0001708193,0.00001131711,0.0002400967,0.00002874162,0.0002433914,0.0001148068,0.00001258938],"category_scores_gemma":[0.00003761975,0.0001069812,0.00002509968,0.00008832223,0.0001760471,0.00009283559,0.0005256934,0.0002277464,0.00000416456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002990034,"about_ca_system_score_gemma":0.000004039959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001294664,"about_ca_topic_score_gemma":0.00004078614,"domain_scores_codex":[0.9994323,0.000003306025,0.0001017988,0.000152527,0.00008946616,0.000220613],"domain_scores_gemma":[0.9994008,0.0001167389,0.00001408714,0.0003326132,0.00005681815,0.00007893273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004092569,0.000676083,0.07721914,0.0008550938,0.0009840975,0.00003680402,0.005691595,0.009124102,0.1548522,0.5322323,0.003225377,0.2146938],"study_design_scores_gemma":[0.001698213,0.0003516714,0.01171357,0.00007092519,0.0000718034,0.00003615634,0.00257209,0.7766704,0.200486,0.002800476,0.002471032,0.001057593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9268768,0.00002764148,0.07049448,0.000455711,0.0001085309,0.0002086232,0.000001783673,0.0007080981,0.001118268],"genre_scores_gemma":[0.943245,0.00004848628,0.05655875,0.00003742442,0.00001458155,0.0000228387,0.00000178447,0.00001728865,0.00005387285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7675463,"threshold_uncertainty_score":0.4362567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748933637112601,"score_gpt":0.2223877974917974,"score_spread":0.2048984611206714,"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."}}