{"id":"W4417336871","doi":"10.1109/tase.2025.3644808","title":"TEXterity: Tactile Extrinsic deXterity","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Magna International (Canada)","funders":"","keywords":"Pose; Kinematics; Object (grammar); Estimator; Robot; 3D pose estimation; Articulated body pose estimation; Sequence (biology); Tactile sensor","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000691807,0.000354762,0.0003013181,0.001452665,0.0007759937,0.0006118297,0.0002744397,0.0001717854,0.0002383322],"category_scores_gemma":[0.00005835907,0.000427521,0.00008510177,0.00257498,0.0001847196,0.001357849,0.000005480763,0.0005785461,0.00008486288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004096659,"about_ca_system_score_gemma":0.0001869592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002588209,"about_ca_topic_score_gemma":0.000004592353,"domain_scores_codex":[0.9977968,0.00002844577,0.0005132651,0.0005495527,0.0005596721,0.0005522942],"domain_scores_gemma":[0.9990231,0.0001243391,0.00006031371,0.0003954079,0.0001813743,0.0002154423],"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":[0.00000709435,0.00003899433,0.00001320682,0.0001985398,0.00002853911,0.000002102343,0.0004429263,0.8494961,0.04034499,0.0004979733,0.00004957149,0.10888],"study_design_scores_gemma":[0.0003663042,0.00003696791,0.01014712,0.0003350301,0.00004551005,0.00001256568,0.0001401619,0.966028,0.02019308,0.00002134287,0.002305534,0.0003684344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08470956,0.0001742039,0.9088212,0.0002920129,0.002801374,0.0002859968,0.000002818853,0.0007144602,0.002198379],"genre_scores_gemma":[0.9968769,0.0001882736,0.002121408,0.0001370886,0.00004371432,0.00003973474,8.092335e-7,0.00003089693,0.0005612065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9121673,"threshold_uncertainty_score":0.9998177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01402369062943533,"score_gpt":0.249382270679118,"score_spread":0.2353585800496827,"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."}}