{"id":"W4302027371","doi":"10.1364/ome.477577","title":"Emerging Optical Materials, Devices and Systems for Photonic Neuromorphic Computing: introduction to special issue","year":2022,"lang":"en","type":"article","venue":"Optical Materials Express","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council","keywords":"Neuromorphic engineering; Materials science; Photonics; Optoelectronics; Optical computing; Nanotechnology; Computer science; Engineering physics; Electronic engineering; Optics; Physics; Engineering; Artificial neural network; Artificial intelligence","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":[0.000905155,0.0009122447,0.0007064588,0.001574863,0.0007501374,0.002604939,0.0009701826,0.002291834,0.0218086],"category_scores_gemma":[0.001717348,0.0004819377,0.0005959004,0.0009812088,0.0007898788,0.00355757,0.001347643,0.004677154,0.008919667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007494332,"about_ca_system_score_gemma":0.0007973737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003633165,"about_ca_topic_score_gemma":0.001116418,"domain_scores_codex":[0.9994474,0.00004736202,0.00005283681,0.0000982452,0.000285684,0.00006852717],"domain_scores_gemma":[0.998664,0.0003781497,0.0001231762,0.00005884485,0.0005340741,0.0002417249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004249402,0.00007696463,0.0001898877,0.0009622794,0.00001845855,0.0001416625,0.00004370357,0.0001788193,0.0048559,0.009905686,0.8399987,0.1435855],"study_design_scores_gemma":[0.000003408225,0.00005827,0.0002334882,0.0001638401,0.000008698452,0.0003304089,0.00002410696,0.0002516963,0.0009195102,0.002543631,0.9954492,0.00001362107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.002111181,0.279266,0.01000739,0.04072611,0.6104353,0.0001318524,0.0003702602,0.0003483524,0.05660349],"genre_scores_gemma":[0.008885184,0.2547539,0.007599676,0.02056489,0.5445461,0.0001538304,0.0005268408,0.0004855036,0.1624841],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0218086,"threshold_uncertainty_score":0.07295704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01933844808970897,"score_gpt":0.2500202983984789,"score_spread":0.23068185030877,"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."}}