{"id":"W4224031880","doi":"10.3390/s22082967","title":"On Slip Detection for Quadruped Robots","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Robot; Slip (aerodynamics); Slippage; Robot locomotion; Legged robot; Inertial measurement unit; Artificial intelligence; Search and rescue; Computer science; Terrain; Computer vision; Engineering; Inertial frame of reference; Rescue robot; Simulation; Mobile robot; Control engineering; Robot control; Aerospace 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":[0.00005890394,0.00006004521,0.0000676244,0.00005090646,0.0001013053,0.000008449121,0.00004312958,0.00001758433,0.0001629968],"category_scores_gemma":[0.00001388405,0.00006483465,0.00005155185,0.00006970225,0.000003558896,0.00001273722,0.000005850629,0.00008530218,0.00004070828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000664004,"about_ca_system_score_gemma":0.000002784191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005491624,"about_ca_topic_score_gemma":0.00000748628,"domain_scores_codex":[0.9996186,0.00001914207,0.00007829587,0.00008045993,0.00008405065,0.0001194331],"domain_scores_gemma":[0.9998127,0.00004461135,0.000009861437,0.00009634505,0.000008347487,0.00002808904],"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":[0.00001688684,0.00001019597,0.00000315082,0.000006147403,0.00001199065,0.000001079821,0.00008141156,0.985915,0.002457924,0.0006489966,0.0006578956,0.01018929],"study_design_scores_gemma":[0.0008310586,0.0001322423,0.0003338244,0.000002131473,0.00001043095,0.000005029381,0.0001725665,0.9831911,0.003328921,0.0006348244,0.01121809,0.0001398218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9159266,0.00004539712,0.07270542,0.000374863,0.002488254,0.000626573,0.00001342687,0.000806982,0.007012438],"genre_scores_gemma":[0.998606,0.000001172021,0.0001447211,0.0001028403,0.00006679849,0.0000799597,0.000003239372,0.00002027591,0.0009750504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08267929,"threshold_uncertainty_score":0.264388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007566760680092184,"score_gpt":0.1942762904137575,"score_spread":0.1867095297336653,"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."}}