{"id":"W2996265823","doi":"10.1109/tac.2020.3044284","title":"Actuator Placement Under Structural Controllability Using Forward and Reverse Greedy Algorithms","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Army Research Office","keywords":"Controllability; Greedy algorithm; Cardinality (data modeling); Matroid; Submodular set function; Metric (unit); Constraint (computer-aided design); Actuator; Set (abstract data type)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003601539,0.000394166,0.0006707643,0.0001120315,0.0003204504,0.0002918241,0.0005383064,0.0001290097,0.0001009294],"category_scores_gemma":[0.00004065382,0.0003569688,0.0002173856,0.0003553253,0.0000930058,0.0005653555,0.000007010678,0.0002279071,0.0000536455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002584128,"about_ca_system_score_gemma":0.000155648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009474477,"about_ca_topic_score_gemma":0.00001695586,"domain_scores_codex":[0.9971962,0.0002901845,0.0007031175,0.0007166499,0.0005868648,0.0005069569],"domain_scores_gemma":[0.9981505,0.0004022454,0.0002470124,0.0006331809,0.0001325622,0.0004344529],"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":[0.001319126,0.001082339,0.0003840018,0.001008362,0.005008516,0.0002073618,0.009213315,0.4886734,0.07013319,0.003465883,0.0009076439,0.4185969],"study_design_scores_gemma":[0.007578323,0.0002247707,0.0003693852,0.00003715211,0.0001668339,0.00002741398,0.0001797821,0.9903441,0.0005068667,0.0001334509,0.00009110093,0.0003408009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05462822,0.00004489182,0.9385528,0.003982788,0.0007088002,0.001413857,0.0001418857,0.0005065477,0.00002022693],"genre_scores_gemma":[0.9881576,0.000001865883,0.009862359,0.001770332,0.00006683596,0.000090858,0.000001735384,0.00002351668,0.0000248488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9335294,"threshold_uncertainty_score":0.9998882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641665605921367,"score_gpt":0.2597774176327807,"score_spread":0.233360761573567,"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."}}