{"id":"W4389584362","doi":"10.1364/fio.2023.fw6e.4","title":"Fully Integrated Photonic Tensor Core Accelerator for Neural Network Applications","year":2023,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Photonics; Artificial neural network; Computer science; Core (optical fiber); Integrated optics; Photonic integrated circuit; Physics; Artificial intelligence; Optoelectronics; Telecommunications","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":[0.0003242955,0.0003991943,0.0003121441,0.0002339426,0.0003510073,0.0007152577,0.0008490725,0.0004351116,0.008275013],"category_scores_gemma":[0.0005426666,0.0002014309,0.0002248835,0.0003118532,0.0003207349,0.00133525,0.0007548284,0.0008953558,0.001231222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000644171,"about_ca_system_score_gemma":0.0008983185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008828465,"about_ca_topic_score_gemma":0.001357488,"domain_scores_codex":[0.9998233,0.00001622163,0.000005923425,0.00002227537,0.0000924485,0.000039861],"domain_scores_gemma":[0.999778,0.00004106689,0.00002486788,0.0000301381,0.00008587643,0.00003999304],"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":[0.002305033,0.0007089583,0.002627977,0.00101021,0.0002267521,0.000564985,0.0002750271,0.0362791,0.4972801,0.1789868,0.05418614,0.2255489],"study_design_scores_gemma":[0.0001429699,0.001214939,0.001197286,0.00008821051,0.00008412628,0.0004722953,0.00007590195,0.6410412,0.2509874,0.02093313,0.08365855,0.000103904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3095169,0.005483059,0.583387,0.002208116,0.001673842,0.000254006,0.001241372,0.01157806,0.08465767],"genre_scores_gemma":[0.8493116,0.001062938,0.1331458,0.0003831065,0.000154125,0.0001576597,0.0007050752,0.000277379,0.01480247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008275013,"threshold_uncertainty_score":0.02768266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04771239198957271,"score_gpt":0.2868222063031489,"score_spread":0.2391098143135761,"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."}}