{"id":"W4410237108","doi":"10.1007/s10845-025-02612-6","title":"A proposed adaptive navigation architecture to improve safety of self-guided vehicles in dynamic manufacturing environments","year":2025,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Architecture; Engineering; Computer science; Systems engineering; Manufacturing engineering; Geography","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":[0.0007690316,0.0002693979,0.0004709682,0.0007509199,0.00007155358,0.00006314529,0.001036416,0.000109224,0.000003188826],"category_scores_gemma":[0.00005545638,0.0002333861,0.0001622547,0.0002078137,0.00003198094,0.0003208906,0.0003320392,0.0005845004,0.000007708206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006358098,"about_ca_system_score_gemma":0.0001184341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002778777,"about_ca_topic_score_gemma":0.00000268792,"domain_scores_codex":[0.9974148,0.0001402275,0.001158488,0.0003625448,0.0005480158,0.0003759685],"domain_scores_gemma":[0.9985707,0.0001979001,0.0006409004,0.000409612,0.00004951622,0.0001313291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002996587,0.000386038,0.0005643218,0.0002464268,0.0003515507,0.0002708026,0.006400344,0.6947111,0.04326924,0.0002225359,0.00003816183,0.2532398],"study_design_scores_gemma":[0.0005940595,0.000260269,0.01676445,0.001039204,0.00002786131,0.00007998917,0.0001826654,0.03101668,0.9477728,0.001774008,0.0002534493,0.0002345654],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4319831,0.00007485573,0.5667965,0.0003039044,0.0004152805,0.0003111931,0.000002128723,0.0000217323,0.00009128274],"genre_scores_gemma":[0.8214857,0.00002801865,0.178257,0.00007965253,0.00003116672,0.000003591375,0.000001079369,0.00001243249,0.0001012978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9045036,"threshold_uncertainty_score":0.9517208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00999067057834677,"score_gpt":0.2540874847875332,"score_spread":0.2440968142091864,"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."}}