{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003825453,0.0003804153,0.0004364671,0.0003056615,0.0002579941,0.0005558366,0.0008614045,0.0008973518,0.008293308],"category_scores_gemma":[0.0007579026,0.0001533701,0.0002130628,0.0002156735,0.0003082052,0.0006953551,0.0004435325,0.0005395876,0.002107299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003037763,"about_ca_system_score_gemma":0.0002754907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002596858,"about_ca_topic_score_gemma":0.0003327428,"domain_scores_codex":[0.9995956,0.00006606009,0.00002019749,0.0000603857,0.0002331357,0.00002481876],"domain_scores_gemma":[0.9996855,0.00008428139,0.00003908963,0.000043959,0.0001247354,0.00002244367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005497013,0.0001349173,0.0006965293,0.000429965,0.0000419804,0.0004171164,0.0002613232,0.006790725,0.6433912,0.0133195,0.01137914,0.3225879],"study_design_scores_gemma":[0.0003253137,0.003286439,0.006206886,0.0001678832,0.0002074967,0.004778043,0.0002023049,0.3332113,0.3795652,0.009068755,0.2627313,0.0002490158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03186623,0.002189951,0.9365668,0.000550853,0.0004396598,0.0002988388,0.000182708,0.006320861,0.02158414],"genre_scores_gemma":[0.5652931,0.0009747274,0.4012505,0.0006878622,0.0002582157,0.0003788889,0.0003375791,0.0001530235,0.03066615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008293308,"threshold_uncertainty_score":0.02774388,"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."}}