{"id":"W2295130897","doi":"10.1109/lra.2016.2528294","title":"Design Principles for a Family of Direct-Drive Legged Robots","year":2016,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":318,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Laboratory; Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Robustness (evolution); Transparency (behavior); Legged robot; Simulation; Artificial intelligence; Computer security; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002119636,0.0003356548,0.0001841364,0.0003570964,0.0004396279,0.0005260394,0.0005333745,0.0004982376,0.002465635],"category_scores_gemma":[0.0003656827,0.0002423742,0.0002039115,0.0001297524,0.000594875,0.0005160263,0.0005989236,0.0004962069,0.0009332742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002210215,"about_ca_system_score_gemma":0.0002596655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001574172,"about_ca_topic_score_gemma":0.0002918758,"domain_scores_codex":[0.999863,0.00002005423,0.000007542881,0.00002657156,0.0000723773,0.00001042232],"domain_scores_gemma":[0.999884,0.00002358476,0.00002310209,0.00001853289,0.00003381891,0.00001685366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005937378,0.0000925869,0.001139876,0.0005143204,0.0000233242,0.0005082738,0.0005846707,0.06618906,0.1675102,0.5886546,0.004844514,0.1698792],"study_design_scores_gemma":[0.0000876364,0.0009882431,0.001560554,0.0002277142,0.00003151638,0.002675919,0.0002039079,0.4836508,0.03068804,0.2393123,0.24049,0.00008327363],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01837012,0.000640489,0.9579282,0.0003519056,0.00009613783,0.0001587656,0.00004647654,0.0002649107,0.0221429],"genre_scores_gemma":[0.4114241,0.0009791853,0.5687842,0.000317501,0.00006267661,0.0007661984,0.000099512,0.0001008926,0.01746562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002465635,"threshold_uncertainty_score":0.008248389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253485156345155,"score_gpt":0.2141682296624994,"score_spread":0.1916333780990479,"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."}}