{"id":"W4403788260","doi":"10.1139/tcsme-2024-0063","title":"Comparisons of data-driven models for detecting slip occurrence and direction based on simulations of tactile sensing","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Slip (aerodynamics); Acoustics; Computer science; Tactile sensor; Geology; Physics; Engineering; Artificial intelligence; Aerospace engineering; Robot","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001065272,0.0009408367,0.000857908,0.0008985757,0.0002647677,0.0007258416,0.001062347,0.001152193,0.0008840784],"category_scores_gemma":[0.006768767,0.0004338574,0.000864982,0.0005617183,0.000485606,0.001090287,0.0004848853,0.0009467567,0.000229485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231234,"about_ca_system_score_gemma":0.001110476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01982734,"about_ca_topic_score_gemma":0.01478019,"domain_scores_codex":[0.9996019,0.00008120282,0.00003976732,0.0001082288,0.0001070111,0.00006184287],"domain_scores_gemma":[0.9976832,0.001430369,0.0001769553,0.0001662863,0.0004419434,0.0001012834],"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":[0.0002601824,0.0001000638,0.003120497,0.0001049815,0.00005523756,0.00004924883,0.00004434371,0.9753345,0.002030649,0.0006169213,0.0004754776,0.01780801],"study_design_scores_gemma":[0.000003366016,0.00002061512,0.0003194822,0.000004324387,0.000002844652,0.000005646199,0.000005125811,0.9989717,0.0004865428,0.0001387687,0.00003783436,0.000003772604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.824696,0.001499436,0.1662317,0.0006427483,0.0002089291,0.0001357408,0.0008533816,0.001937638,0.003794402],"genre_scores_gemma":[0.9805462,0.0002632368,0.01771869,0.00008295614,0.00001166936,0.00006673364,0.0006572159,0.00005007613,0.0006031321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01982734,"threshold_uncertainty_score":0.03942388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03814162213223057,"score_gpt":0.2666810362772123,"score_spread":0.2285394141449818,"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."}}