{"id":"W2162552936","doi":"10.1115/1.3023137","title":"Wireless Swimming Microrobot: Design, Analysis, and Experiments","year":2008,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Propulsion; Wireless; Fin; Robot; Range (aeronautics); Power (physics); Power consumption; Head (geology); Simulation; Computer science; Acoustics; Engineering; Marine engineering; Mechanical engineering; Aerospace engineering; Physics; Artificial intelligence; Telecommunications; Geology","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":[0.0007062412,0.0001675779,0.0005465512,0.0001815555,0.0001551718,0.00005629041,0.00009474941,0.00003770933,0.000008980707],"category_scores_gemma":[0.000004351961,0.0001330863,0.000141254,0.0001311854,0.00003981681,0.000116412,0.0000132111,0.0001140089,0.00000113308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005582449,"about_ca_system_score_gemma":0.00007508213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000720512,"about_ca_topic_score_gemma":0.000002534647,"domain_scores_codex":[0.9986142,0.0001358587,0.0005459468,0.0001393405,0.0003689183,0.0001957425],"domain_scores_gemma":[0.9989834,0.00003912632,0.0004802448,0.0001063946,0.000266836,0.0001240435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002988784,0.0003799616,0.3390386,0.00006976862,0.008198812,0.00004751262,0.001464769,0.001457626,0.6403899,0.0002374377,0.0002510524,0.008165718],"study_design_scores_gemma":[0.09632216,0.003952324,0.4183523,0.00339851,0.02869945,0.001852127,0.01657751,0.3466166,0.07430774,0.0007034055,0.003228526,0.005989311],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4726726,0.006301568,0.5204982,0.00003510845,0.0002276514,0.0002030771,0.000003710269,0.000004482269,0.00005358338],"genre_scores_gemma":[0.9993067,0.00007406239,0.0003613659,0.00001320041,0.0001396787,0.000004663467,9.203825e-7,0.00001103295,0.00008835789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5660821,"threshold_uncertainty_score":0.54271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02337122099780378,"score_gpt":0.2263323649821543,"score_spread":0.2029611439843506,"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."}}