{"id":"W4387895087","doi":"10.1007/s10015-023-00908-5","title":"A data grid strategy for non-prehensile object transport by a multi-robot system","year":2023,"lang":"en","type":"article","venue":"Artificial Life and Robotics","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Robot; Computer science; Object (grammar); Grid; Distributed computing; Prehensile tail; Protocol (science); Field (mathematics); Human–computer interaction; Artificial intelligence; Simulation","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":[0.0003431351,0.0004902511,0.0008027221,0.0006262026,0.001074543,0.0009177419,0.001188044,0.0006153774,0.003556344],"category_scores_gemma":[0.0005212483,0.00020234,0.0004186476,0.0005843689,0.0004520883,0.001092458,0.001526935,0.0003530818,0.0005489445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006237176,"about_ca_system_score_gemma":0.0007820343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00710443,"about_ca_topic_score_gemma":0.005380927,"domain_scores_codex":[0.9998203,0.00003156352,0.00001688835,0.00004245618,0.0000405753,0.00004832417],"domain_scores_gemma":[0.9997192,0.00004999928,0.00002838573,0.00005591712,0.00009619514,0.00005033278],"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":[0.0007195284,0.0002850499,0.002073037,0.0001978696,0.0000887556,0.000488221,0.0003337448,0.7476054,0.02618976,0.03775554,0.005300153,0.178963],"study_design_scores_gemma":[0.00001475185,0.00005765974,0.0001639326,0.000003886182,0.000008345016,0.00002826318,0.00005084676,0.9940381,0.001543972,0.003303863,0.0007793528,0.00000700104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0739845,0.0001566425,0.9172812,0.0002972166,0.00008178658,0.0001006464,0.00008185073,0.0008408903,0.007175272],"genre_scores_gemma":[0.9419566,0.00006326675,0.05460066,0.00004346705,0.00001094701,0.00007789279,0.00007556514,0.00003918907,0.003132396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00710443,"threshold_uncertainty_score":0.01412612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102186576049942,"score_gpt":0.2939705705649544,"score_spread":0.1917839945150124,"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."}}