{"id":"W7010554554","doi":"","title":"Investigation of Stochastic Deep Learning Motion Planning Methods for Autonomous Robots","year":2023,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Motion planning; Motion (physics); Reliability (semiconductor); Path (computing); Deep learning; Robot; Artificial neural 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":[0.001505588,0.000743276,0.0006419714,0.0003889083,0.0003229075,0.0007281278,0.001243115,0.0008349359,0.002083896],"category_scores_gemma":[0.003964134,0.0005709518,0.000572757,0.0004327723,0.0007733274,0.001470446,0.0008893763,0.001508357,0.000250945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001860364,"about_ca_system_score_gemma":0.002085096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000427,"about_ca_topic_score_gemma":0.009507786,"domain_scores_codex":[0.9994772,0.0001383569,0.00002441418,0.0001231282,0.000181847,0.00005509843],"domain_scores_gemma":[0.998457,0.0009806171,0.0001173146,0.00009215134,0.0002762475,0.00007666276],"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":[0.0000287325,0.0000250408,0.0004594323,0.00007523599,0.00002728854,0.00001927472,0.00002603183,0.9430322,0.0008797485,0.01850086,0.000926442,0.03599977],"study_design_scores_gemma":[0.000001990363,0.00001043499,0.00003657775,0.000005328,0.000001860905,0.000004082791,0.000002421508,0.9965953,0.000185117,0.002822755,0.0003326987,0.000001437835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02828006,0.001623786,0.9617105,0.001139206,0.0001076246,0.00006127255,0.0001108974,0.0005599296,0.006406806],"genre_scores_gemma":[0.7756992,0.001936924,0.2143441,0.0006276424,0.0001319024,0.0001790017,0.0003328475,0.000177512,0.006570975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01000427,"threshold_uncertainty_score":0.0198921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04084636305808762,"score_gpt":0.2844883742557219,"score_spread":0.2436420111976343,"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."}}