{"id":"W2097036980","doi":"10.1364/ol.36.001038","title":"Optical backpropagation for fiber-optic communications using highly nonlinear fibers","year":2011,"lang":"en","type":"article","venue":"Optics Letters","topic":"Optical Network Technologies","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Optical fiber; Backpropagation; Optics; Nonlinear system; Nonlinear optics; Materials science; Fiber; Refractive index; Computer science; Artificial neural network; Physics; Laser","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":[0.0001868698,0.0003914611,0.0001269941,0.000276337,0.0005200137,0.0003813375,0.0003214209,0.0004523023,0.001040674],"category_scores_gemma":[0.0003111271,0.0001605839,0.0001229124,0.0001569963,0.0003574592,0.000723966,0.0003249246,0.0005132889,0.0003881294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002802617,"about_ca_system_score_gemma":0.000341415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00028475,"about_ca_topic_score_gemma":0.001045977,"domain_scores_codex":[0.9998283,0.0000202703,0.000005204846,0.00001493956,0.000116799,0.00001438635],"domain_scores_gemma":[0.9998679,0.00004233965,0.00002451653,0.00001374325,0.00003914858,0.0000123029],"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":[0.00007342139,0.00005939928,0.0002175895,0.0001305389,0.000005599132,0.000199052,0.00006297378,0.001518967,0.9351863,0.02001959,0.0005478831,0.04197869],"study_design_scores_gemma":[0.00004721037,0.0004506635,0.0006282884,0.0000392456,0.00002314603,0.00124631,0.00003027726,0.04759367,0.920471,0.005936495,0.02348666,0.00004711412],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4629272,0.006394982,0.4986026,0.001633785,0.0007125598,0.0001501623,0.00006686416,0.0009733679,0.02853843],"genre_scores_gemma":[0.743969,0.004224968,0.2367737,0.0002318417,0.0002236269,0.00006399702,0.00006774812,0.00006544048,0.01437968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001040674,"threshold_uncertainty_score":0.003481388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04882895164203176,"score_gpt":0.2437672587586525,"score_spread":0.1949383071166207,"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."}}