{"id":"W2783470107","doi":"10.4018/ijrat.2017070104","title":"Kinova Modular Robot Arms for Service Robotics Applications","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics Applications and Technologies","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kinova (Canada); Université Laval","funders":"","keywords":"Robotics; Artificial intelligence; Modular design; Teleoperation; Robot; Service (business); Grippers; Computer science; Human–computer interaction; Rehabilitation robotics; Engineering; Control engineering; Mechanical engineering; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001298195,0.0007405582,0.0002389995,0.0004814852,0.0003398818,0.0004599622,0.0005583775,0.0005269173,0.007961558],"category_scores_gemma":[0.0002671551,0.0002200536,0.0003668741,0.00026913,0.0002733928,0.0005988882,0.0008154817,0.0004635922,0.002504431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004088374,"about_ca_system_score_gemma":0.0004565992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006108715,"about_ca_topic_score_gemma":0.001469059,"domain_scores_codex":[0.9998353,0.00001420339,0.00000867878,0.00003086635,0.00008100572,0.00002995754],"domain_scores_gemma":[0.9998846,0.00001401598,0.00002297511,0.0000210556,0.00003983266,0.00001748016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004223497,0.00008585433,0.001249968,0.0008826321,0.0000408209,0.0005291141,0.0002800753,0.0130657,0.4043656,0.03950216,0.01261254,0.5269631],"study_design_scores_gemma":[0.00013255,0.001768045,0.01067227,0.0004398596,0.0001366789,0.004520304,0.0001842817,0.07715427,0.1492085,0.01549405,0.7401279,0.0001611889],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08386434,0.008500601,0.7686061,0.0007208369,0.001170476,0.0003202159,0.0003772313,0.006491914,0.1299483],"genre_scores_gemma":[0.6769617,0.002587587,0.2408631,0.0003969472,0.0001523194,0.0003964078,0.0005030254,0.0003229658,0.07781614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007961558,"threshold_uncertainty_score":0.0266341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02198431236471237,"score_gpt":0.2754995299243294,"score_spread":0.253515217559617,"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."}}