{"id":"W3113055384","doi":"10.1109/jlt.2020.3024057","title":"Estimating the Outage Probability Due to Polarization Dependent Loss Using Threshold Exceedances","year":2020,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Optical Network Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada); Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Probability distribution; Statistics; Outage probability; Probability density function; Fisher information; Entropy (arrow of time); Cumulative distribution function; Mean squared error; Statistical physics; Physics; Fading; Decoding methods","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002602353,0.0006512949,0.0006606646,0.001389152,0.0003785662,0.0007773523,0.0005916672,0.0006445755,0.0007210847],"category_scores_gemma":[0.0167365,0.0002861226,0.0005811019,0.001238459,0.0007277237,0.001513743,0.001139525,0.0008666265,0.00012832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009354927,"about_ca_system_score_gemma":0.0007735036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002289559,"about_ca_topic_score_gemma":0.002167891,"domain_scores_codex":[0.9987078,0.000354331,0.00009743805,0.0001933335,0.0005196334,0.0001274796],"domain_scores_gemma":[0.9828659,0.01278614,0.002030033,0.001410347,0.0007177538,0.0001898828],"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":[0.00019862,0.00004019007,0.02080015,0.00006926733,0.00007971418,0.0002366358,0.0001931048,0.9385573,0.008579982,0.006219374,0.0002235593,0.02480205],"study_design_scores_gemma":[0.000005162214,0.00008883356,0.005904037,0.00001335974,0.00001331605,0.0002479396,0.00004590478,0.9840439,0.005695732,0.003723832,0.0001899571,0.00002806282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4383761,0.0001945699,0.5587158,0.00008415743,0.00001279325,0.00006083588,0.0002934537,0.0006635613,0.001598628],"genre_scores_gemma":[0.9656685,0.00009001748,0.03364187,0.00001390477,0.000006325001,0.00004938731,0.000202868,0.00003908416,0.0002880241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002602353,"threshold_uncertainty_score":0.01376271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02453265732744252,"score_gpt":0.2450829459578797,"score_spread":0.2205502886304372,"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."}}