{"id":"W4284889893","doi":"10.55417/fr.2022047","title":"NeBula: TEAM CoSTAR's Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge","year":2022,"lang":"en","type":"article","venue":"Field Robotics","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Robot; Autonomy; Computer science; Artificial intelligence; Modular design; Systems engineering; Engineering","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":[0.001399507,0.0007272318,0.0004236163,0.000342692,0.0009132387,0.0009597163,0.001047932,0.0009901645,0.003808646],"category_scores_gemma":[0.001711505,0.0002906575,0.0004343246,0.0001848824,0.0007201054,0.001272202,0.002268625,0.002075812,0.001513681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009282265,"about_ca_system_score_gemma":0.002289761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009477437,"about_ca_topic_score_gemma":0.01430345,"domain_scores_codex":[0.9993744,0.00009944723,0.00001286405,0.0001226078,0.0002578872,0.0001327268],"domain_scores_gemma":[0.9994596,0.0000789709,0.00002163908,0.00007596759,0.0001644277,0.0001994445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001198881,0.0006379758,0.004350018,0.0003300549,0.0001675661,0.0007039734,0.001248018,0.1224375,0.0603179,0.05102912,0.2057924,0.5517866],"study_design_scores_gemma":[0.0005563183,0.001522878,0.003197421,0.00008113608,0.00005343954,0.0003974239,0.0004683906,0.5550362,0.02842717,0.01923104,0.3909319,0.00009674068],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1440733,0.001687314,0.7206373,0.00682682,0.002318771,0.001160476,0.001742969,0.0323616,0.08919153],"genre_scores_gemma":[0.4771579,0.0005785353,0.4707821,0.001235344,0.0002043523,0.0006651856,0.00428647,0.001569357,0.0435208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009477437,"threshold_uncertainty_score":0.01884454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932778403605732,"score_gpt":0.2381606962197692,"score_spread":0.2088329121837119,"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."}}