{"id":"W4402475025","doi":"10.1109/ccece59415.2024.10667271","title":"Grasp Approach Under Positional Uncertainty Using Compliant Tactile Sensing Modules and Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"GRASP; Reinforcement learning; Computer science; Tactile sensor; Artificial intelligence; Human–computer interaction; Grippers; Reinforcement; Robot; Engineering; Mechanical engineering; Software engineering; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009244547,0.0007172689,0.0007399375,0.0003401141,0.0003127246,0.0005017505,0.0008381858,0.0008056801,0.0009718543],"category_scores_gemma":[0.002729798,0.000308951,0.0004259702,0.0001709531,0.0008102857,0.0006909318,0.0009737334,0.0007040037,0.0001765474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005833488,"about_ca_system_score_gemma":0.001012726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003097502,"about_ca_topic_score_gemma":0.002245167,"domain_scores_codex":[0.9996691,0.00007192919,0.00002297697,0.00008100956,0.00009427794,0.00006074503],"domain_scores_gemma":[0.9986995,0.0005895564,0.0002848866,0.0001495641,0.0001657334,0.0001106603],"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":[0.00009881019,0.0001048128,0.00103496,0.00004892784,0.00004155914,0.0001454937,0.0001046047,0.9367304,0.01088263,0.003227989,0.0002384663,0.04734126],"study_design_scores_gemma":[0.00000903818,0.00004802594,0.0001037966,0.000002210799,0.000003691124,0.00001457263,0.000004260447,0.9979091,0.0008383744,0.0009949096,0.00006700953,0.0000049333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1458898,0.0001223466,0.8507078,0.0001593723,0.0000263884,0.00008085954,0.00001590457,0.0007014477,0.00229611],"genre_scores_gemma":[0.9642019,0.00002895398,0.0344688,0.00004982283,0.000009863176,0.0000625034,0.00001194745,0.00002083511,0.001145382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003097502,"threshold_uncertainty_score":0.006158948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0765473045771679,"score_gpt":0.3098137480812716,"score_spread":0.2332664435041037,"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."}}