{"id":"W4385987058","doi":"10.32920/23989437.v1","title":"Aerial Continuum Manipulation: A New Platform for Compliant Aerial Manipulation","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rigidity (electromagnetism); Computer science; Adaptability; Control engineering; Manipulator (device); Set (abstract data type); Artificial intelligence; Robot; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009546489,0.0003167219,0.0003670542,0.0001126186,0.00009607075,0.0001913656,0.0002575366,0.0003624085,0.0001580113],"category_scores_gemma":[0.00002805344,0.0003468009,0.0001863167,0.0001073807,0.00001458436,0.00006358049,0.0001680524,0.000227519,0.000193694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215259,"about_ca_system_score_gemma":0.00005835283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001826461,"about_ca_topic_score_gemma":0.0004682907,"domain_scores_codex":[0.99862,0.000003688059,0.0005211262,0.0003725681,0.0001719079,0.0003106803],"domain_scores_gemma":[0.9991228,0.00009362756,0.000127966,0.0004597571,0.0000714391,0.0001243908],"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":[0.00005449207,0.00003244508,0.0001511732,0.0004166064,0.0002298799,0.00000204248,0.0002460989,0.7866414,0.001445783,0.05052111,0.157591,0.002667969],"study_design_scores_gemma":[0.001662452,0.00003324489,0.007023516,0.0001412254,0.000159886,0.00000487278,0.00005277903,0.8716013,0.001001784,0.07980558,0.03753462,0.000978685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01918634,0.00005121386,0.9625286,0.0005179184,0.008356456,0.002623482,0.0001744106,0.002403687,0.004157874],"genre_scores_gemma":[0.8841884,0.00006700079,0.08775535,0.00008423186,0.01232003,0.001230407,0.005740665,0.0004212829,0.008192612],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8747733,"threshold_uncertainty_score":0.9998984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220731744783663,"score_gpt":0.2973534090795674,"score_spread":0.1752802346012011,"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."}}