{"id":"W2158952093","doi":"10.1109/leosst.2002.1027562","title":"Enabling the dynamic enablers: advanced optical performance monitors","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"JDSU (Canada)","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006430534,0.0003527489,0.0001355449,0.0002316398,0.0002491273,0.0008432785,0.0005787547,0.0003825136,0.001271796],"category_scores_gemma":[0.001247462,0.0001586306,0.0001162022,0.0001483662,0.0004260088,0.001537479,0.0007017028,0.0008544718,0.0003340413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001902547,"about_ca_system_score_gemma":0.0002165168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003350689,"about_ca_topic_score_gemma":0.0003805694,"domain_scores_codex":[0.9995168,0.00005907314,0.00001841264,0.00006577345,0.0002642213,0.00007555793],"domain_scores_gemma":[0.9995964,0.000125277,0.00008400427,0.00005046506,0.0001055243,0.00003828094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000160896,0.00006441896,0.001543518,0.00008387934,0.00001206149,0.0002722656,0.0001984825,0.00241699,0.9131559,0.02773449,0.00105205,0.05330507],"study_design_scores_gemma":[0.0000160025,0.0001779357,0.0005870044,0.00001185093,0.00001623684,0.0002428109,0.00004752598,0.01139954,0.9663989,0.002697006,0.01838239,0.0000228209],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6113376,0.005014361,0.3489406,0.00217748,0.0003463349,0.00009281049,0.0001563013,0.001698567,0.03023598],"genre_scores_gemma":[0.9516006,0.00164114,0.04219707,0.00019371,0.00009435973,0.00002846775,0.0000518355,0.00004923165,0.004143659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001271796,"threshold_uncertainty_score":0.00425452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00742208990023717,"score_gpt":0.2129100201504728,"score_spread":0.2054879302502356,"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."}}