{"id":"W4410860181","doi":"10.1080/15376494.2025.2509259","title":"A pneumatic soft gripper with pre-deformed stiffener inspired by blowing dragon toys","year":2025,"lang":"en","type":"article","venue":"Mechanics of Advanced Materials and Structures","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Natural Science Foundation of China","keywords":"Soft robotics; Mechanical engineering; Structural engineering; Engineering; Computer science; Materials science; Artificial intelligence; Robot","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":[0.00004243546,0.0001605653,0.0002646188,0.00005072639,0.00006635235,0.00004252995,0.00009917965,0.00006671211,0.00001974291],"category_scores_gemma":[0.00001529839,0.0001240883,0.00001870901,0.0000913714,0.00001641981,0.00007735998,0.00003273033,0.00004789638,2.548319e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001573007,"about_ca_system_score_gemma":0.00001112622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009761629,"about_ca_topic_score_gemma":0.000007165653,"domain_scores_codex":[0.9993545,0.000007230116,0.0002359274,0.0001538075,0.00008593871,0.0001625793],"domain_scores_gemma":[0.9996735,0.00002863077,0.00004754008,0.0001839284,0.00003088238,0.00003553121],"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":[0.00002621923,0.000007425838,0.000005594981,0.0002886557,0.00004415897,3.12381e-7,0.0001062827,0.01654701,0.9690639,0.01011694,0.00008361747,0.003709833],"study_design_scores_gemma":[0.00061128,0.00005144232,0.0004577452,0.0001371413,0.00005022756,0.000002950786,0.00008529446,0.003552362,0.950619,0.04350235,0.0007044594,0.0002257833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613017,0.0004327836,0.03744197,0.00003854749,0.0002537799,0.0002730476,0.0000717467,0.0001111894,0.00007522009],"genre_scores_gemma":[0.993251,0.0001265743,0.006441823,0.00003519712,0.0000137031,0.00004694211,0.00002498044,0.00002320917,0.00003652159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03338542,"threshold_uncertainty_score":0.5060175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00286792414181794,"score_gpt":0.2003354688195601,"score_spread":0.1974675446777421,"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."}}