{"id":"W3110571569","doi":"10.1016/j.ipl.2021.106133","title":"Weighted automata are compact and actively learnable","year":2021,"lang":"en","type":"preprint","venue":"Information Processing Letters","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University; James S. McDonnell Foundation","keywords":"ω-automaton; Generalization; Quantum finite automata; Automaton; Mathematics; Discrete mathematics; Deterministic automaton; Time complexity; Deterministic finite automaton; Automata theory; Timed automaton; Mobile automaton; DFA minimization; Nondeterministic finite automaton; Algorithm; Computer science; Finite-state machine; Theoretical computer science","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002954705,0.0002641524,0.000294832,0.0002505295,0.0003014768,0.002982855,0.0006342444,0.0001434158,0.000008173],"category_scores_gemma":[0.00006506718,0.0002535426,0.00005978551,0.0002643357,0.00005203522,0.003253743,0.0004767238,0.000843514,0.00002261186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007568843,"about_ca_system_score_gemma":0.0001872969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008150635,"about_ca_topic_score_gemma":7.648632e-7,"domain_scores_codex":[0.9985461,0.00006583067,0.0003821645,0.0003144252,0.0004153183,0.0002761742],"domain_scores_gemma":[0.9986159,0.00003834061,0.000674972,0.0004101826,0.0001628381,0.00009782975],"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":[0.00001315462,0.0000675435,0.001958131,0.002661466,0.0001093547,0.00004745961,0.01674898,0.02007113,0.0004260233,0.0002610777,0.009113311,0.9485224],"study_design_scores_gemma":[0.0004266104,0.00001428654,0.01492559,0.0008188269,0.00001527776,0.00006532456,0.000275122,0.9700893,0.0004750084,0.0001746622,0.01219207,0.0005279271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1333061,0.0002389843,0.8377506,0.02476113,0.0006443241,0.0002182113,0.000008991988,0.0009545873,0.002117149],"genre_scores_gemma":[0.9270968,0.00003410352,0.06382603,0.008578006,0.0001468113,0.00001867999,0.0001559247,0.00002025782,0.0001233165],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9500182,"threshold_uncertainty_score":0.9999917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027833315074606,"score_gpt":0.2392107649562038,"score_spread":0.2289324318054577,"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."}}