{"id":"W2792847425","doi":"10.1177/1729881418754477","title":"Parametric L-systems-based modeling self-reconfiguration of modular robots in obstacle environments","year":2018,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Control reconfiguration; Modular design; Computer science; Self-reconfiguring modular robot; Robot; Obstacle; Distributed computing; Parametric statistics; Formalism (music); Key (lock); Adaptability; Mobile robot; Artificial intelligence; Embedded system; Robot control; 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":[0.0003962996,0.0001779867,0.0003925492,0.0005649294,0.00002274428,0.00005219258,0.000422239,0.00009192939,0.00001428574],"category_scores_gemma":[0.00008540745,0.0001688321,0.00009747995,0.0002302048,0.00002783827,0.0003615256,0.0000161694,0.0001757726,0.00001379835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003573567,"about_ca_system_score_gemma":0.00004153847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004804263,"about_ca_topic_score_gemma":0.000004831856,"domain_scores_codex":[0.9977237,0.00006612145,0.001177171,0.0001556629,0.0006734037,0.0002039668],"domain_scores_gemma":[0.9989223,0.00008623126,0.000392709,0.0001882726,0.000329973,0.00008047457],"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":[0.00003047355,0.00007330559,0.0004980289,0.0000476373,0.0001189522,0.00002402166,0.0001514091,0.9903526,0.007044851,0.000236978,0.000008160555,0.001413578],"study_design_scores_gemma":[0.0006094385,0.0001199228,0.0003060228,0.0004386441,0.0000166904,0.0000758567,0.0001706308,0.9934767,0.00443005,0.00006665989,0.00013743,0.000151936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2666668,0.001419487,0.7273033,0.00001717803,0.004199138,0.0001925527,0.000003646314,0.00002220912,0.0001757544],"genre_scores_gemma":[0.994289,0.0001511531,0.005169708,0.000007695645,0.0003106225,0.000007991842,0.00000444021,0.00003065742,0.00002877071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7276222,"threshold_uncertainty_score":0.6884773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522673814652363,"score_gpt":0.2429313885469196,"score_spread":0.227704650400396,"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."}}