{"id":"W4365448660","doi":"10.3390/act12040172","title":"A Modular Soft Gripper with Combined Pneu-Net Actuators","year":2023,"lang":"en","type":"article","venue":"Actuators","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Fundamental Research Funds for the Central Universities; Changzhou Science and Technology Bureau; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Actuator; Modular design; Lift (data mining); Grippers; Bending; Mechanical engineering; Deformation (meteorology); Soft robotics; GRASP; Pneumatic actuator; Computer science; Structural engineering; Engineering; Materials science; Artificial intelligence","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":[0.00006512417,0.0001841789,0.0001631143,0.0001190796,0.00009179267,0.00004217843,0.000185676,0.00007717746,0.00007246193],"category_scores_gemma":[0.00001774593,0.0001595031,0.00004940306,0.0006329454,0.0000365723,0.00008719134,0.00003268404,0.0001419147,0.0006332873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003700171,"about_ca_system_score_gemma":0.00002069823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082408,"about_ca_topic_score_gemma":0.00000905725,"domain_scores_codex":[0.9991311,0.0000062242,0.0001505614,0.0001969491,0.0001840562,0.0003311457],"domain_scores_gemma":[0.9993901,0.00006193884,0.00002143939,0.0003710077,0.00002634957,0.0001292013],"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":[0.00008968157,0.0004465255,0.04491067,0.000458573,0.0017529,0.0002006855,0.007184717,0.5133957,0.02322344,0.0489191,0.1785381,0.1808799],"study_design_scores_gemma":[0.003406361,0.0004151607,0.09645005,0.0001549189,0.0002920898,0.00003736116,0.00124056,0.6655712,0.01141065,0.01250026,0.2055911,0.002930318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717107,0.00002207409,0.0242877,0.0003332687,0.0002348069,0.0002776086,0.00001612237,0.001758105,0.001359649],"genre_scores_gemma":[0.998433,0.00002981653,0.0009285367,0.0000863184,0.00007063591,0.00008890816,0.00005069603,0.00007682947,0.0002352528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1779496,"threshold_uncertainty_score":0.8139838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00679678172783995,"score_gpt":0.1922046225612402,"score_spread":0.1854078408334002,"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."}}