{"id":"W2163182982","doi":"10.1017/s0263574703005435","title":"A modular object-oriented framework for hierarchical multi-resolution robot simulation","year":2004,"lang":"en","type":"article","venue":"Robotica","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"Seoul National University","keywords":"Modular design; Computer science; Robot; Kinematics; Modularity (biology); Self-reconfiguring modular robot; Exploit; Set (abstract data type); Control engineering; Artificial intelligence; Robot control; Engineering; Mobile robot; Programming language","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":[0.0001250577,0.0002020659,0.0002110441,0.00008910176,0.0001349985,0.00003817864,0.0001436081,0.0002196138,0.0000298962],"category_scores_gemma":[0.0002416246,0.0002039771,0.0001167891,0.0002129491,0.00004525991,0.0001122232,0.00002546387,0.000287455,0.00006527611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001370643,"about_ca_system_score_gemma":0.00002409378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001405727,"about_ca_topic_score_gemma":0.00001128236,"domain_scores_codex":[0.9987945,0.00001950175,0.0002923324,0.0002835551,0.00019548,0.0004146093],"domain_scores_gemma":[0.9993137,0.0001295036,0.00002823878,0.0003168807,0.00007873747,0.0001329111],"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":[0.00001631249,0.00006253264,0.00001746059,0.00004445269,0.00002888648,0.000003197433,0.000225854,0.9580618,0.001223853,0.0384853,0.000008536771,0.001821879],"study_design_scores_gemma":[0.0003913026,0.00006739314,0.0007537972,0.00007943006,0.00002307824,0.000002816884,0.00001364439,0.9847891,0.001839132,0.01124814,0.0005443408,0.000247777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004340142,0.0001950002,0.9937847,0.0002139404,0.0005247963,0.0004677576,0.000007912845,0.00039141,0.00007433435],"genre_scores_gemma":[0.6394944,0.00001502677,0.3601964,0.00004445318,0.0001312356,0.0000351912,0.00002012087,0.00003772939,0.00002538543],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6351542,"threshold_uncertainty_score":0.8317944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02926821897710331,"score_gpt":0.2861767832669715,"score_spread":0.2569085642898682,"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."}}