{"id":"W4297929165","doi":"10.21428/594757db.09aa0c75","title":"Bridging Reality Gap Between Virtual and Physical Robot through Domain Randomization and Induced Noise","year":2022,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Bridging (networking); Computer science; Virtual reality; Noise (video); Human–computer interaction; Artificial intelligence; Computer network","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":[0.001922271,0.0007067106,0.000575864,0.0002647803,0.0003990858,0.0009394071,0.001024521,0.0007781446,0.001330658],"category_scores_gemma":[0.007096355,0.0003730559,0.0004162347,0.000136776,0.001877536,0.00195142,0.002855917,0.001389464,0.0002414318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004930595,"about_ca_system_score_gemma":0.0007510275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004491696,"about_ca_topic_score_gemma":0.0003386301,"domain_scores_codex":[0.9988268,0.0005026266,0.00005339496,0.0002192392,0.000293702,0.0001042836],"domain_scores_gemma":[0.9970221,0.001702007,0.0003951395,0.000558441,0.0001814183,0.0001409072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007517038,0.0003350756,0.001674755,0.0001986272,0.00007221832,0.0005578655,0.0005217179,0.8415237,0.04287504,0.04810831,0.0006970394,0.06268395],"study_design_scores_gemma":[0.00005232444,0.0004647709,0.0006070489,0.00003779045,0.00002168146,0.0001952387,0.00009173605,0.9625831,0.01803815,0.01541191,0.002461135,0.000035244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07931525,0.0001528117,0.9165726,0.0002645138,0.00006212091,0.00005581418,0.00001359171,0.0005157178,0.003047697],"genre_scores_gemma":[0.9258138,0.00007605686,0.07259955,0.0001330761,0.00001490487,0.00009563487,0.0000277029,0.00005523722,0.001183955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001922271,"threshold_uncertainty_score":0.01016605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04612733430692306,"score_gpt":0.2963235994839558,"score_spread":0.2501962651770327,"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."}}