{"id":"W2116213015","doi":"10.1109/tit.2010.2080470","title":"Capacity Bounds for Wireless Optical Intensity Channels With Gaussian Noise","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Upper and lower bounds; Channel capacity; Mathematics; Topology (electrical circuits); Entropy (arrow of time); Optical wireless; Channel (broadcasting); Gaussian; Telecommunications; Wireless; Mathematical analysis; Combinatorics; Physics; Computer science; Quantum mechanics","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":[0.0002537197,0.000191519,0.0001880377,0.0002216105,0.0002339481,0.0001024093,0.000303135,0.0002191995,0.00005018833],"category_scores_gemma":[0.00002262029,0.0001624095,0.00007591109,0.0002128998,0.0002896517,0.0008665146,0.000002110793,0.0006749185,0.000110363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006020923,"about_ca_system_score_gemma":0.00002062247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000285762,"about_ca_topic_score_gemma":0.00001572858,"domain_scores_codex":[0.9992157,0.00001273202,0.0002972562,0.00009274052,0.000134662,0.0002468863],"domain_scores_gemma":[0.9989355,0.0002126043,0.00004571041,0.0005518992,0.0001650702,0.00008923738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008141389,0.0003116234,0.000007675865,0.0003627286,0.0003193583,7.295866e-7,0.003713784,0.09037763,0.01842126,0.4045556,0.0003770491,0.4807384],"study_design_scores_gemma":[0.001226957,0.0002717343,0.0001110749,0.00006778273,0.00004356128,0.00003825427,0.001252316,0.2156096,0.7670739,0.0102679,0.003382529,0.0006544318],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1633562,0.00000239588,0.8320621,0.000273533,0.0005861868,0.0003055944,0.00004072835,0.0009925518,0.002380715],"genre_scores_gemma":[0.9919102,0.0000148323,0.007632558,0.0001110661,0.00001963548,0.0002430138,0.00001093932,0.00002287455,0.00003493849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.828554,"threshold_uncertainty_score":0.6622866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009872243119052807,"score_gpt":0.2060927511542161,"score_spread":0.1962205080351633,"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."}}