{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002150179,0.000594773,0.0004263318,0.0004909192,0.0002178631,0.0002259368,0.000851422,0.0005665174,0.0009932616],"category_scores_gemma":[0.0002094784,0.0003250517,0.0003849392,0.0002685896,0.0002707261,0.000739209,0.001022881,0.0002524858,0.0004941923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001534637,"about_ca_system_score_gemma":0.0002352311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002532853,"about_ca_topic_score_gemma":0.0003806725,"domain_scores_codex":[0.9996982,0.0000170568,0.00002103064,0.00008918674,0.0001284868,0.00004616827],"domain_scores_gemma":[0.9998174,0.00001890757,0.00006025229,0.00003088337,0.00002815272,0.00004440531],"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":[0.0001271335,0.00004518179,0.0008503311,0.0002090402,0.00003728384,0.0006387554,0.00003670795,0.004530685,0.9495023,0.001088865,0.0004601721,0.04247368],"study_design_scores_gemma":[0.0001105301,0.001901002,0.009089571,0.0000572958,0.0001318442,0.003654723,0.00004670914,0.1077698,0.857766,0.001045549,0.01827708,0.0001498519],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6182519,0.001566798,0.3678842,0.0001941884,0.0002476044,0.000154074,0.0002140743,0.0023103,0.009176961],"genre_scores_gemma":[0.8715882,0.000347582,0.1226262,0.0001367505,0.00003753876,0.000102948,0.0001254594,0.00004225554,0.004993181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009932616,"threshold_uncertainty_score":0.00332278,"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."}}