{"id":"W4396722964","doi":"10.1515/nanoph-2024-0044","title":"Reconfigurable quantum photonic circuits based on quantum dots","year":2024,"lang":"en","type":"article","venue":"Nanophotonics","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Queen's University","funders":"Vector Institute; Natural Sciences and Engineering Research Council of Canada; Queen's University; Canada Foundation for Innovation","keywords":"Quantum dot; Photonics; Electronic circuit; Quantum; Nanomaterials; Photonic integrated circuit; Optoelectronics; Physics; Nanotechnology; Materials science; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006281689,0.0003460115,0.0003279943,0.0001974457,0.0003065238,0.000777819,0.001371865,0.0001917644,0.0000920132],"category_scores_gemma":[0.00004443168,0.0002874412,0.0002495995,0.001227665,0.0000471073,0.00033573,0.0001379058,0.0006468641,0.0004805882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001513281,"about_ca_system_score_gemma":0.0004155692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003473206,"about_ca_topic_score_gemma":0.000005649084,"domain_scores_codex":[0.9970613,0.0001100963,0.0004259564,0.001005811,0.000587219,0.0008096251],"domain_scores_gemma":[0.9980783,0.0004308097,0.00009035295,0.001100052,0.00008545922,0.000215038],"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":[0.00007790216,0.0008672226,0.0001451049,0.001121319,0.0002360805,0.003910677,0.001052548,0.2319923,0.07316174,0.431722,0.04980509,0.205908],"study_design_scores_gemma":[0.0002357569,0.000250292,0.00002894282,0.0003456021,0.000007408525,0.00003579396,0.000005073943,0.9060907,0.008975527,0.003256374,0.08041651,0.000352037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6522015,0.01871286,0.1865532,0.01306246,0.04065207,0.002937068,0.00004701041,0.007658486,0.07817543],"genre_scores_gemma":[0.9955588,0.000171692,0.001907592,0.001420507,0.0001220727,0.00003150586,0.000005973501,0.000050821,0.0007310089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6740984,"threshold_uncertainty_score":0.9999578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01939777314053513,"score_gpt":0.2483210412239878,"score_spread":0.2289232680834526,"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."}}