{"id":"W2994895683","doi":"10.1109/jsen.2019.2959311","title":"Soft Sensitive Skin for Safety Control of a Nursing Robot Using Proximity and Tactile Sensors","year":2019,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Key Research and Development Program of China","keywords":"Tactile sensor; Robot; Robotic arm; Proximity sensor; Computer science; Pressure sensor; Computer vision; Artificial intelligence; Piezoresistive effect; Computer hardware; Simulation; Engineering; Electrical engineering; Mechanical engineering","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":[0.0001911141,0.0004132322,0.0003365932,0.0002207402,0.0001587927,0.0003685919,0.0004067353,0.0004608239,0.001038375],"category_scores_gemma":[0.0004687593,0.0001724947,0.0003161565,0.0001165667,0.0003556835,0.0004792525,0.0004560504,0.000283214,0.0003065472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001314844,"about_ca_system_score_gemma":0.0001703506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008787226,"about_ca_topic_score_gemma":0.0001330492,"domain_scores_codex":[0.9996409,0.00006810524,0.00001913478,0.00007286467,0.000169499,0.0000294897],"domain_scores_gemma":[0.9997275,0.00008699791,0.0000610556,0.0000342088,0.00006281062,0.00002740583],"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":[0.00009956984,0.00004917125,0.0003173922,0.0002402645,0.00001359374,0.0003275788,0.00008228999,0.00445247,0.9439995,0.0008022613,0.0002493714,0.04936645],"study_design_scores_gemma":[0.00005526251,0.002007161,0.004400759,0.00005996944,0.00007898177,0.001975379,0.000176069,0.09500617,0.8813333,0.001293911,0.01354244,0.00007059478],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2618045,0.002716835,0.7279276,0.0002663067,0.0003570302,0.000163229,0.0000338038,0.0006811667,0.006049491],"genre_scores_gemma":[0.8937274,0.0007223625,0.1020188,0.000251889,0.00007467648,0.00006647117,0.00002336787,0.00003275833,0.003082353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001038375,"threshold_uncertainty_score":0.003473699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710224096327667,"score_gpt":0.2552580104555594,"score_spread":0.2381557694922827,"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."}}