{"id":"W4387574420","doi":"10.1115/1.4063763","title":"Bistable Stopper Design and Force Prediction for Precision and Power Grasps of Soft Robotic Fingers for Industrial Manipulation","year":2023,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"GRASP; Grippers; Finite element method; Bistability; Kinematics; Artificial neural network; Engineering; Power (physics); Computer science; Control engineering; Artificial intelligence; Mechanical engineering; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009347228,0.00008728586,0.0002007805,0.0001207669,0.00006152107,0.00002689586,0.00006163302,0.0001275364,0.000003023727],"category_scores_gemma":[0.0003170148,0.00007801173,0.00005665534,0.0001412241,0.00001187173,0.0001188049,0.00001155538,0.00009668618,3.411727e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002963914,"about_ca_system_score_gemma":0.00002247155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.206607e-7,"about_ca_topic_score_gemma":1.552516e-7,"domain_scores_codex":[0.9992187,0.00002704475,0.0003834498,0.0001001554,0.0001354514,0.0001352034],"domain_scores_gemma":[0.998723,0.0009019122,0.0001205231,0.00007325324,0.0001074428,0.00007392327],"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":[0.0002345936,0.00002426055,0.00002141064,0.00004927464,0.00005832367,4.886242e-7,0.00006193861,0.9355396,0.05119239,0.001494176,0.006267835,0.005055679],"study_design_scores_gemma":[0.001238164,0.000638354,0.0001871061,0.00008100767,0.00009728174,0.00001062595,0.00003993034,0.97016,0.008853739,0.01835446,0.0002548523,0.00008447077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01079681,0.00008570003,0.9880461,0.0001336785,0.0002624314,0.0006346181,0.000007063134,0.00003132088,0.000002330264],"genre_scores_gemma":[0.9067151,0.00008452592,0.09295586,0.000009877195,0.0001193578,0.00004112695,0.00000489142,0.00003099926,0.00003825569],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8959183,"threshold_uncertainty_score":0.3181226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.085992562442232,"score_gpt":0.2681463374911779,"score_spread":0.1821537750489459,"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."}}