{"id":"W3208836193","doi":"10.1109/robot.2010.5509397","title":"Hybrid aerial and scansorial robotics","year":2010,"lang":"en","type":"article","venue":"","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency","keywords":"Climbing; Robot; Robotics; Computer science; Aerospace engineering; Drone; Plane (geometry); Artificial intelligence; Simulation; Aeronautics; Engineering; Structural engineering; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003036381,0.00005810233,0.0000684769,0.00001827762,0.00002118931,0.00003391057,0.00004103809,0.00002980884,0.0003069533],"category_scores_gemma":[0.0000096494,0.00005174144,0.00001569866,0.0000160004,0.00001766839,0.0000436079,0.000007878799,0.00009721619,0.00004915131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003274912,"about_ca_system_score_gemma":0.000004641139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000756023,"about_ca_topic_score_gemma":0.0000235855,"domain_scores_codex":[0.9997164,0.000003133139,0.00007261229,0.00005790591,0.0000490499,0.0001008871],"domain_scores_gemma":[0.9998248,0.00001188743,0.00000409698,0.00008688195,0.000009655726,0.00006264503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006211032,0.00009926003,0.0009831002,0.00007336546,0.0001675891,0.00003146555,0.000260051,0.1749085,0.2398859,0.3961715,0.04430281,0.1430543],"study_design_scores_gemma":[0.004935731,0.00006581398,0.002440018,0.000006920802,0.00004854119,0.0001009992,0.00003300729,0.91463,0.01619264,0.004646469,0.0562301,0.0006697824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.61933,0.00006404996,0.2255824,0.00141083,0.0229627,0.0004274204,0.00000688587,0.001579822,0.1286358],"genre_scores_gemma":[0.9950097,0.000005378293,0.00379871,0.0000459186,0.0007684914,0.000002642474,0.000001240501,0.00001066914,0.0003572691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7397215,"threshold_uncertainty_score":0.3360924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003699120006639486,"score_gpt":0.1773589366541898,"score_spread":0.1736598166475503,"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."}}