{"id":"W2898647080","doi":"10.1115/detc2018-85905","title":"Optimizing Cable Arrangement in Cable-Driven Parallel Robots to Improve the Range of Available Wrenches","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Surface Polishing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Wrench; Knapsack problem; Workspace; Range (aeronautics); Parallel manipulator; Mathematical optimization; Computer science; Robot; Point (geometry); Set (abstract data type); Optimization problem; Control theory (sociology); Topology (electrical circuits); Mathematics; Engineering; Artificial intelligence; Mechanical engineering; Control (management); Electrical engineering","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":[0.000359832,0.001021339,0.0005145965,0.0004835125,0.000347605,0.0003217496,0.0007400823,0.0003830726,0.001485406],"category_scores_gemma":[0.000799808,0.0004531131,0.0003520454,0.0004892768,0.0003789961,0.0007321729,0.000710451,0.000480013,0.0003406069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003532316,"about_ca_system_score_gemma":0.000594517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008045201,"about_ca_topic_score_gemma":0.001394679,"domain_scores_codex":[0.9997267,0.00004597669,0.0000116862,0.00006504525,0.0001183621,0.00003221614],"domain_scores_gemma":[0.9997485,0.00008056035,0.00006280188,0.00003308328,0.00005418959,0.00002075385],"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":[0.00009498121,0.00008606531,0.0006463103,0.0001841942,0.00003027788,0.0001537478,0.0001099141,0.7679582,0.09123161,0.005954868,0.0007461869,0.1328038],"study_design_scores_gemma":[0.00003992895,0.0003306921,0.0004768763,0.00001301024,0.00001906882,0.0001432958,0.0000535476,0.9660067,0.02595686,0.003908334,0.003027772,0.00002390778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04847342,0.0001053898,0.949064,0.00003091007,0.00001011704,0.00002952614,0.0000152381,0.0003005856,0.001970656],"genre_scores_gemma":[0.5495015,0.000212101,0.4462512,0.00002837366,0.00001509768,0.0001278192,0.00007836461,0.0001648931,0.003620588],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001485406,"threshold_uncertainty_score":0.00496918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02589087745639686,"score_gpt":0.2465619789749559,"score_spread":0.2206711015185591,"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."}}