{"id":"W2038848748","doi":"10.1364/ofc.2015.th2a.19","title":"Enhancing Clock Tone via Polarization Pre-rotation: A Low-complexity, Extended Kalman Filter-based Approach","year":2015,"lang":"en","type":"article","venue":"Optical Fiber Communication Conference","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Kalman filter; Computer science; Rotation (mathematics); Extended Kalman filter; Electronic engineering; Algorithm; Computer vision; Artificial intelligence; 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":[0.0002703553,0.0002025648,0.0002106357,0.00007899819,0.0001375426,0.0001215915,0.0004018655,0.0001534524,0.0001539174],"category_scores_gemma":[0.00010186,0.0002177104,0.00005125604,0.0002959256,0.0001216912,0.0003127157,0.00007904063,0.0003190934,0.0001418977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001258547,"about_ca_system_score_gemma":0.00006193065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007460993,"about_ca_topic_score_gemma":0.00005142888,"domain_scores_codex":[0.9986382,0.0001419194,0.0004250479,0.0002186705,0.0003197741,0.0002564282],"domain_scores_gemma":[0.9985132,0.0001106579,0.00006924277,0.0007469294,0.0003769134,0.0001831161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006069358,0.001684538,0.0008055998,0.001033096,0.0002068989,0.000007459615,0.007594281,0.2376499,0.3488207,0.3168491,0.001104713,0.08363669],"study_design_scores_gemma":[0.0009855512,0.00008913279,0.003403739,0.0001188757,0.00003933326,0.000008272638,0.0001073698,0.9270093,0.06220999,0.004802986,0.0007437149,0.0004816726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1212109,0.0001381285,0.8472033,0.0004520481,0.0001186388,0.000533498,0.00001121016,0.0005203121,0.02981199],"genre_scores_gemma":[0.9340883,0.000008219256,0.06489017,0.00007227366,0.00005638639,0.00006168098,0.0005672433,0.0000310714,0.0002246129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8128774,"threshold_uncertainty_score":0.8877973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548381957303445,"score_gpt":0.2817202949554573,"score_spread":0.2362364753824228,"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."}}