{"id":"W2982815418","doi":"10.1109/tim.2005.851422","title":"Intelligent Haptic Sensor System for Robotic Manipulation","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Haptic technology; Computer vision; Orientation (vector space); Computer science; Artificial intelligence; Context (archaeology); Telerobotics; Tactile sensor; Robot; Mobile robot","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":[0.0001700887,0.0001389285,0.0001157895,0.0001479408,0.0001694455,0.00005273825,0.00003162042,0.00004983625,0.0000475527],"category_scores_gemma":[0.000001942147,0.0001478272,0.00005466447,0.00008063871,0.00001108744,0.0001514869,2.409695e-7,0.00008991031,0.00004719478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003950527,"about_ca_system_score_gemma":0.000009740857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005614975,"about_ca_topic_score_gemma":0.00003704663,"domain_scores_codex":[0.9991366,0.00002407838,0.0002786291,0.0001543736,0.0002552476,0.0001510429],"domain_scores_gemma":[0.9997099,0.00001705548,0.00003619446,0.00009227841,0.00006820759,0.00007637805],"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":[0.00001973023,0.00002445408,0.00001181276,0.00009905628,0.00004356452,1.304466e-7,0.0002963222,0.9198158,0.006570447,0.0002054337,0.00002874419,0.07288449],"study_design_scores_gemma":[0.0008499777,0.00007263599,0.0003713356,0.00008954163,0.00006859748,0.000008394303,0.0007314958,0.9558206,0.04068556,0.000006526612,0.001104734,0.0001906185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01361634,0.0000393043,0.9842921,0.0001384195,0.0007282382,0.0004958342,9.481828e-7,0.0002763802,0.0004124435],"genre_scores_gemma":[0.9960862,0.00002767696,0.003516876,0.00006076586,0.00006291729,0.0001082496,0.000005190116,0.00002700899,0.0001050693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9824699,"threshold_uncertainty_score":0.6028218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06189781925611193,"score_gpt":0.2523816094337359,"score_spread":0.190483790177624,"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."}}