{"id":"W2010085093","doi":"10.1088/1748-3182/7/4/046016","title":"Optimally efficient swimming in hyper-redundant mechanisms: control, design, and energy recovery","year":2012,"lang":"en","type":"article","venue":"Bioinspiration & Biomimetics","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Chongqing University","keywords":"Fish locomotion; Kinematics; Propulsion; Biomimetics; Process (computing); Gait; Robot; Range (aeronautics); Efficient energy use; Computer science; Simulation; Control engineering; Engineering; Control theory (sociology); Control (management); Artificial intelligence; Aerospace engineering; Biology","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":[0.0005341475,0.0003538516,0.0003287084,0.0004456109,0.0001898166,0.0005395403,0.0006153127,0.000442766,0.0006882774],"category_scores_gemma":[0.0005668782,0.0003177426,0.0002805564,0.000186442,0.0004495783,0.0004287727,0.0005142547,0.0001962958,0.0001556727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000208957,"about_ca_system_score_gemma":0.000419832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004136297,"about_ca_topic_score_gemma":0.0005469879,"domain_scores_codex":[0.9998972,0.00002154085,0.00001052065,0.00002157806,0.00003161107,0.00001761032],"domain_scores_gemma":[0.9997502,0.00005409833,0.0001113416,0.00002712849,0.00003748812,0.0000197149],"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":[0.0001556468,0.0001349956,0.001520445,0.0004824729,0.00006333334,0.0003000586,0.0001679464,0.7011874,0.1832213,0.01836752,0.0003460504,0.09405274],"study_design_scores_gemma":[0.00003937928,0.0005714133,0.001026194,0.00003938079,0.00002959789,0.00008027576,0.00004001197,0.9838164,0.009856738,0.003059289,0.001418671,0.00002270007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3914551,0.001873732,0.5985065,0.0003036276,0.00004614373,0.0001584538,0.00004016852,0.0002671699,0.007349113],"genre_scores_gemma":[0.9597842,0.000499421,0.03824969,0.00002700692,0.000008418609,0.0001390829,0.00001826209,0.00001465582,0.001259172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006882774,"threshold_uncertainty_score":0.002824903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312606314505106,"score_gpt":0.1929260490111295,"score_spread":0.1797999858660785,"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."}}