{"id":"W1993598446","doi":"10.1142/s0129054102000960","title":"AN EFFICIENT ALGORITHM FOR CONSTRUCTING MINIMAL COVER AUTOMATA FOR FINITE LANGUAGES","year":2002,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"semigroups and automata theory","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cover (algebra); Nondeterministic finite automaton; DFA minimization; Deterministic finite automaton; Quantum finite automata; Nested word; Regular language; Finite-state machine; Automaton; Deterministic automaton; ω-automaton; Computer science; Time complexity; Algorithm; Formal language; Timed automaton; Mathematics; Theoretical computer science; Automata theory; Two-way deterministic finite automaton","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001045567,0.0001047482,0.0001747623,0.0004686546,0.0001610412,0.0004716069,0.002604987,0.00002704171,0.00001778873],"category_scores_gemma":[0.0001894199,0.00009395926,0.0001315299,0.00030494,0.0002852047,0.001382656,0.0001687915,0.00006669148,0.000003804887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006829335,"about_ca_system_score_gemma":0.0001586937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002070376,"about_ca_topic_score_gemma":2.309884e-7,"domain_scores_codex":[0.9983245,0.00002653421,0.0005342991,0.0002425447,0.000671914,0.0002002672],"domain_scores_gemma":[0.9968221,0.0006336209,0.0005903002,0.000289866,0.001570313,0.00009383453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001196648,0.0003379331,0.00006251855,0.000008961214,0.00006025287,0.000006298727,0.001070872,0.0158556,0.003070371,0.06234862,0.0004068219,0.9167598],"study_design_scores_gemma":[0.0007968201,0.0003031675,0.0002091067,0.00005241596,0.000007765319,0.0001517075,0.00005412672,0.9905261,0.004742849,0.001913791,0.001136528,0.0001056559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02976299,0.00004121162,0.967342,0.0006098791,0.00194528,0.0001349539,0.00003526027,0.00003132327,0.00009706555],"genre_scores_gemma":[0.4162287,0.000003210903,0.583382,0.0001146303,0.0002521708,0.000003291613,0.000002110713,0.000003752228,0.00001009473],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9746705,"threshold_uncertainty_score":0.4840757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962646832423218,"score_gpt":0.3115234385093699,"score_spread":0.2918969701851377,"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."}}