{"id":"W3171774150","doi":"10.1088/1742-6596/1924/1/012021","title":"A Novel Terrain Adaptive Landing Gear Robot","year":2021,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Terrain; Kinematics; Robot; Computer science; Simulation; Computer vision; Artificial intelligence; Geography; Physics","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":[0.00008207603,0.0002815094,0.0002819583,0.0002567615,0.0002989789,0.0002722737,0.0004713869,0.0003763396,0.002102386],"category_scores_gemma":[0.00008669602,0.0001652968,0.0002209781,0.0001290248,0.0002239884,0.0003221428,0.0005028002,0.0002347998,0.000719099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010297,"about_ca_system_score_gemma":0.0002034865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005483318,"about_ca_topic_score_gemma":0.0004660242,"domain_scores_codex":[0.9999104,0.000007970446,0.00000463388,0.00002566899,0.00003883206,0.00001250129],"domain_scores_gemma":[0.9999568,0.000005184964,0.000006509296,0.00000793872,0.00001288058,0.00001060825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000363447,0.0001936774,0.006174077,0.0003706316,0.00007877524,0.002334922,0.0003121828,0.06640299,0.5436009,0.011659,0.005170616,0.3633387],"study_design_scores_gemma":[0.0003228791,0.001066823,0.005160891,0.00005783121,0.00007742745,0.002703659,0.000135152,0.901707,0.04403868,0.003755058,0.04090346,0.000071145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.208998,0.0006173995,0.7694974,0.0002808202,0.0003875766,0.0001552103,0.00008078078,0.003620066,0.01636273],"genre_scores_gemma":[0.7850346,0.0002836242,0.203182,0.0001130128,0.00007299308,0.0001327196,0.000123707,0.00003212809,0.01102518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002102386,"threshold_uncertainty_score":0.007033169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767191830366887,"score_gpt":0.2315252223393484,"score_spread":0.2038533040356795,"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."}}