{"id":"W2498033477","doi":"10.1109/biorob.2016.7523816","title":"Optimizing the Maximum Torque of bioinspired climbing robots in static equilibrium","year":2016,"lang":"en","type":"article","venue":"","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Robot; Climb; Linear programming; Torque; Differentiable function; Genetic algorithm; Mathematical optimization; Computer science; Genetic programming; Control theory (sociology); Algorithm; Mathematics; Artificial intelligence; 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":[0.0003163564,0.0003656461,0.0005043037,0.0002653246,0.0002775831,0.0003948576,0.000507707,0.0006048938,0.001111299],"category_scores_gemma":[0.0007606978,0.0002805991,0.0002825971,0.0002144442,0.0004890945,0.0003166403,0.0003849124,0.000248121,0.0002392606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003126999,"about_ca_system_score_gemma":0.0004155395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001193688,"about_ca_topic_score_gemma":0.001422348,"domain_scores_codex":[0.9999186,0.00001722041,0.000004341145,0.0000154293,0.00002846595,0.00001602372],"domain_scores_gemma":[0.9998651,0.00005477831,0.00002829551,0.00000951054,0.00002434222,0.00001803256],"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":[0.00009110239,0.00006711168,0.0006323214,0.000158582,0.00002548713,0.0001336424,0.00007668065,0.9230543,0.03338429,0.007145443,0.0004934426,0.03473759],"study_design_scores_gemma":[0.00001357176,0.00009005033,0.0002762118,0.00001010885,0.000004931757,0.00001940277,0.00001787719,0.9941454,0.002886427,0.002061345,0.0004694977,0.000005219694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2367018,0.0003080325,0.7526644,0.000233027,0.00003611564,0.00006684358,0.00003474903,0.0003121952,0.009642775],"genre_scores_gemma":[0.9486704,0.0001432447,0.04795646,0.0000337899,0.000009800484,0.00009918493,0.00002753903,0.00004656407,0.003012998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001193688,"threshold_uncertainty_score":0.003717661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0109244665298446,"score_gpt":0.203136878841863,"score_spread":0.1922124123120184,"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."}}