{"id":"W2967829315","doi":"10.1109/phosst.2019.8795081","title":"Neuromorphic Silicon Photonics on Foundry and Cryogenic Platforms","year":2019,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Neuromorphic engineering; Foundry; Photonics; Silicon photonics; Silicon; Materials science; Computer science; Optoelectronics; Engineering; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001208584,0.0001223093,0.0001318844,0.00004941283,0.0000900798,0.0001646357,0.0004665219,0.00004838561,0.00003094153],"category_scores_gemma":[0.000005816662,0.00008516091,0.00004763955,0.0001776102,0.00001882104,0.000243359,0.0003659647,0.0001782177,0.0001533456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001100682,"about_ca_system_score_gemma":0.00001880359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001012641,"about_ca_topic_score_gemma":0.000004460373,"domain_scores_codex":[0.9990143,0.00001149764,0.0001385463,0.0003773303,0.0001837762,0.0002745813],"domain_scores_gemma":[0.9992738,0.0001269577,0.00004503327,0.0004456635,0.00001965158,0.00008888699],"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":[0.0001193313,0.0004348592,0.02541933,0.0002096867,0.0001316578,0.0003421771,0.0007144997,0.06540415,0.03130624,0.6931337,0.005950572,0.1768339],"study_design_scores_gemma":[0.0004050365,0.0003553382,0.003675258,0.00002506816,0.000001801302,0.00006634853,0.000006326956,0.9878542,0.001319934,0.003433354,0.002645758,0.0002116159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989765,0.00009200024,0.004674091,0.0004325529,0.000601708,0.0001713496,1.544856e-7,0.0001471591,0.004115941],"genre_scores_gemma":[0.9948556,0.00003363754,0.002315073,0.001599576,0.0000396948,0.000001691786,4.557861e-7,0.000008455926,0.001145755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.92245,"threshold_uncertainty_score":0.3472761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167765891222561,"score_gpt":0.2074628734559423,"score_spread":0.1906862843336862,"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."}}