{"id":"W2592867787","doi":"10.1016/j.optcom.2017.03.006","title":"Tracking channel alignment in blind polarization de-multiplexing","year":2017,"lang":"en","type":"article","venue":"Optics Communications","topic":"Optical Network Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Multiplexing; Phase-shift keying; Computer science; Polarization (electrochemistry); Polarization-division multiplexing; Algorithm; Optics; Polarization mode dispersion; Physics; Bit error rate; Wavelength-division multiplexing; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001844256,0.00008682421,0.00009679693,0.00008022899,0.0003174825,0.0001495325,0.001092995,0.0001092639,0.000002463834],"category_scores_gemma":[0.0002243187,0.000103242,0.00002309442,0.00008622038,0.000118403,0.0002019167,0.0003392972,0.0002795536,0.00001275921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054229,"about_ca_system_score_gemma":0.000009444064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001943068,"about_ca_topic_score_gemma":0.0001467425,"domain_scores_codex":[0.9994419,0.00001732251,0.0001803013,0.00007977893,0.00006719393,0.0002135148],"domain_scores_gemma":[0.9980471,0.00009840733,0.00004203889,0.001751306,0.0000281614,0.00003301704],"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":[0.000008153435,0.0002790868,0.01616171,0.00006487045,0.00008443281,0.000006616963,0.001631348,0.2972601,0.01066877,0.6305941,0.00007634958,0.04316441],"study_design_scores_gemma":[0.0002564355,0.000006995292,0.012953,0.00006435076,0.000006926449,0.000001192807,0.0001526904,0.9812582,0.0007437402,0.003933958,0.0004893278,0.0001332087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6700495,0.002581641,0.1355657,0.01132932,0.0005663942,0.00121091,0.00004022935,0.00236381,0.1762925],"genre_scores_gemma":[0.9068909,0.0007754997,0.09221188,0.00001333831,0.00001639547,0.00003284759,0.00001520125,0.00002090688,0.00002305256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6839981,"threshold_uncertainty_score":0.4210086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06310478979377657,"score_gpt":0.3029894233187826,"score_spread":0.2398846335250061,"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."}}