{"id":"W4402999964","doi":"10.4028/p-8acltz","title":"Design and Development of a Soft Pneumatic Gripper for Precise Grasping of Fragile Objects","year":2024,"lang":"en","type":"article","venue":"Engineering headway","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Algonquin College","funders":"","keywords":"Grippers; Computer science; Engineering drawing; 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":[0.0002569682,0.0004413568,0.0003528397,0.0003555503,0.0001927938,0.0003304686,0.0007791166,0.0007776913,0.0007654994],"category_scores_gemma":[0.000320062,0.0003381537,0.0003790751,0.0001906782,0.0002596727,0.000467137,0.0003558483,0.000374527,0.000497708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001651969,"about_ca_system_score_gemma":0.0003760126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001693589,"about_ca_topic_score_gemma":0.000228236,"domain_scores_codex":[0.9997545,0.00001594156,0.0000205897,0.0000496875,0.0001367128,0.00002253747],"domain_scores_gemma":[0.9997713,0.00003284427,0.00005550974,0.00003889548,0.00007385628,0.00002758287],"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":[0.00004600955,0.0000408935,0.0004086046,0.0002904052,0.00002281708,0.0004819027,0.00006114448,0.006521151,0.9248387,0.001764746,0.0004750674,0.0650486],"study_design_scores_gemma":[0.0000433205,0.001060974,0.003712561,0.00003596773,0.00005360817,0.002528238,0.00003142887,0.07567277,0.8928534,0.0007354157,0.02318978,0.00008254842],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1126568,0.0009655867,0.8785211,0.0002036561,0.0001654799,0.0003315951,0.00009152578,0.00146255,0.005601671],"genre_scores_gemma":[0.4768247,0.0004935077,0.5174162,0.0001684804,0.00002989763,0.0002180162,0.00009434163,0.00007166962,0.004683155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007791166,"threshold_uncertainty_score":0.002560854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01737845367903632,"score_gpt":0.224920506741351,"score_spread":0.2075420530623147,"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."}}