{"id":"W3138751964","doi":"10.1364/oe.423747","title":"Photonic computing to accelerate data processing in wireless communications","year":2021,"lang":"en","type":"article","venue":"Optics Express","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Photonics; Wireless; Signal processing; Communications system; Computational complexity theory; Efficient energy use; Data processing; Optical computing; Digital signal processing; Communication complexity","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":[0.000182636,0.0003260688,0.000199058,0.0003695264,0.0004146452,0.0009117794,0.0004906993,0.0005429265,0.004014998],"category_scores_gemma":[0.0005855403,0.0001641966,0.0001771285,0.0006051101,0.0005371632,0.001128308,0.0005163461,0.0008073301,0.001199891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004278849,"about_ca_system_score_gemma":0.0004838525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000555727,"about_ca_topic_score_gemma":0.0009516716,"domain_scores_codex":[0.9998521,0.00002342157,0.000005593002,0.00002068481,0.00007782815,0.00002042934],"domain_scores_gemma":[0.9998566,0.0000553221,0.00001426773,0.00002965771,0.00003367252,0.00001037138],"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":[0.000166385,0.0001640149,0.0005835104,0.0005148866,0.00003717596,0.0002011019,0.0001992892,0.02536746,0.1045781,0.5449749,0.02191464,0.3012986],"study_design_scores_gemma":[0.0000748124,0.0004343878,0.0009825416,0.0001988459,0.00004766062,0.0005128302,0.0001110814,0.4311841,0.1136272,0.1778271,0.2749195,0.00008005284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07989496,0.02352914,0.7284799,0.00418245,0.002711243,0.0002275767,0.0002430518,0.004271975,0.1564598],"genre_scores_gemma":[0.5719762,0.013902,0.374718,0.001134571,0.0008203207,0.0002186891,0.0002255465,0.0002892828,0.03671547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004014998,"threshold_uncertainty_score":0.01343149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08157423757073436,"score_gpt":0.3241807389742136,"score_spread":0.2426065014034793,"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."}}