{"id":"W2621263557","doi":"10.1177/0278364915587926","title":"Dynamics and trajectory optimization for a soft spatial fluidic elastomer manipulator","year":2015,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":199,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Soft robotics; Computer science; Fluidics; Actuator; Elastomer; Robot; Trajectory; Control engineering; Simulation; Engineering; Artificial intelligence; Aerospace engineering; Materials science","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":[0.0002095434,0.0003669199,0.0002890911,0.0002807664,0.0002996578,0.0003593508,0.0002455246,0.000476433,0.00172319],"category_scores_gemma":[0.0004879827,0.0002144937,0.000284946,0.0001365213,0.0006581873,0.0003784621,0.0006675234,0.0003508441,0.0002173719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004829651,"about_ca_system_score_gemma":0.000560726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003801573,"about_ca_topic_score_gemma":0.002559563,"domain_scores_codex":[0.9999214,0.0000152196,0.000003066004,0.00001619528,0.00003231541,0.00001173628],"domain_scores_gemma":[0.9998267,0.00006983936,0.00005479475,0.00001198138,0.00002130401,0.00001530569],"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":[0.00003365559,0.00001135709,0.0002606076,0.00002592263,0.000006636412,0.00005543458,0.0000436761,0.9811001,0.007686397,0.006051268,0.00009413467,0.004630833],"study_design_scores_gemma":[0.000007345502,0.00003171549,0.0001200359,0.000002754779,0.000001902913,0.000009956022,0.00001103452,0.9977768,0.0007609504,0.001023555,0.0002506246,0.000003305457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2185432,0.0001930053,0.7729368,0.00037237,0.00002132908,0.00005886436,0.00007976883,0.0002218329,0.007572822],"genre_scores_gemma":[0.9562325,0.0001154011,0.03795464,0.00003434183,0.000007323054,0.00008503431,0.00005153274,0.00002480821,0.005494467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003801573,"threshold_uncertainty_score":0.007558942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07757889251026731,"score_gpt":0.3453533066592719,"score_spread":0.2677744141490046,"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."}}