{"id":"W2027801472","doi":"10.1115/detc2009-87067","title":"Self-Adaptive Compliant Grippers Capable of Pinch Preshaping","year":2009,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Grippers; Finite element method; Software; Compliant mechanism; Stiffness; Computer science; GRASP; Engineering; Structural engineering; Mechanical 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":[0.00004899695,0.00006932636,0.0001025863,0.00005015699,0.00002839066,0.000009867725,0.00005935858,0.00003115018,0.0001938674],"category_scores_gemma":[0.000004279229,0.00006728929,0.00002963498,0.00009444566,0.000005521171,0.00008335967,0.000005555777,0.00007979917,0.00004054741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002638554,"about_ca_system_score_gemma":0.000004794947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001664795,"about_ca_topic_score_gemma":0.000003772052,"domain_scores_codex":[0.9995813,0.000008890138,0.0001315484,0.00007100082,0.00008168976,0.0001255469],"domain_scores_gemma":[0.9998245,0.00001296085,0.00001741642,0.00008846483,0.00002177915,0.00003493048],"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":[0.000003674757,0.00001885666,0.0002743614,0.00003238765,0.00002784174,0.000001554274,0.0007675115,0.9814269,0.004416676,0.00934177,0.001689297,0.001999196],"study_design_scores_gemma":[0.0001641375,0.00003813929,0.01059073,0.0000224008,0.000006021606,0.000002354952,0.0001814427,0.9843591,0.001854714,0.00009342129,0.0025774,0.0001101548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05568394,0.0005794039,0.2355413,0.000215402,0.0002564112,0.0003205862,5.087839e-7,0.001545176,0.7058573],"genre_scores_gemma":[0.9872261,0.00001018976,0.01234462,0.00006410405,0.00002389455,9.566586e-7,0.000001604753,0.000008408232,0.0003201726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9315421,"threshold_uncertainty_score":0.2743978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195609550486972,"score_gpt":0.2201167519705849,"score_spread":0.1981606564657152,"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."}}