{"id":"W4225933121","doi":"10.1115/1.4054272","title":"Neural Network Based Transfer Learning for Robot Path Generation","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanisms and Robotics","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Artificial neural network; Initialization; Transfer of learning; Artificial intelligence; Process (computing); Robot; Convergence (economics); Machine learning; Path (computing); Displacement (psychology)","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":[0.0003973729,0.00008881556,0.0001560924,0.00006603943,0.0002980815,0.00003976882,0.00005712719,0.00003492639,0.00005941524],"category_scores_gemma":[0.00001146818,0.0000847754,0.00008111929,0.00008059904,0.000004086109,0.00007502808,0.000009507533,0.0003326231,2.304916e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003227582,"about_ca_system_score_gemma":0.00001516783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.148034e-7,"about_ca_topic_score_gemma":9.010899e-7,"domain_scores_codex":[0.9992985,0.00005737896,0.0002651221,0.00006242037,0.0001687699,0.0001478544],"domain_scores_gemma":[0.999756,0.00004399403,0.0000560057,0.00003940097,0.0000456383,0.00005900648],"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":[0.00001432069,0.000008568575,0.00003493189,0.00001594773,0.00001742787,0.000005245494,0.00009504807,0.9893644,0.006091001,0.002282873,0.0002565369,0.001813665],"study_design_scores_gemma":[0.000549972,0.000315747,0.0001114981,0.000008413791,0.00003689833,0.00003884685,0.00009614335,0.9972019,0.00009462961,0.0002031928,0.001242404,0.0001004134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004715348,0.0002959793,0.99373,0.0002169845,0.0009119103,0.00008243845,3.120249e-7,0.00002889989,0.00001810594],"genre_scores_gemma":[0.9086288,0.00002763303,0.0907119,0.0001413043,0.0003861825,0.000003827384,0.000007949097,0.0000293121,0.00006308888],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9039134,"threshold_uncertainty_score":0.345704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02530336722163467,"score_gpt":0.2168262611605927,"score_spread":0.191522893938958,"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."}}