{"id":"W2922342170","doi":"10.1016/j.tcs.2019.03.005","title":"Edit distance neighbourhoods of input-driven pushdown automata","year":2019,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"semigroups and automata theory","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Deterministic pushdown automaton; Pushdown automaton; Neighbourhood (mathematics); Embedded pushdown automaton; Context-free language; Automaton; Discrete mathematics; Nondeterministic algorithm; Nested word; Deterministic context-free grammar; Mathematics; Computer science; Combinatorics; Regular language; Theoretical computer science; Automata theory; Nondeterministic finite automaton; Quantum finite automata; Context-free grammar; Rule-based machine translation; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00117416,0.0004687548,0.001193066,0.001731868,0.001289538,0.002683211,0.001693013,0.001346746,0.004633462],"category_scores_gemma":[0.01220636,0.0004512696,0.0008753175,0.001186311,0.001563294,0.003819545,0.002423461,0.001383456,0.0007005549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007873995,"about_ca_system_score_gemma":0.0004737191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007363692,"about_ca_topic_score_gemma":0.0006807233,"domain_scores_codex":[0.9985555,0.0003791728,0.000125069,0.0003927192,0.0004295399,0.0001179752],"domain_scores_gemma":[0.9881617,0.007638594,0.000915747,0.001244023,0.001132242,0.0009075965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004520891,0.0001550128,0.001913361,0.0002549563,0.00006865321,0.0008047739,0.001446887,0.06127767,0.009621055,0.8856877,0.001531391,0.03678643],"study_design_scores_gemma":[0.00003959025,0.00009940097,0.0005322045,0.00002310372,0.00002969763,0.0002604284,0.0001467938,0.2418838,0.003254333,0.7515362,0.002159205,0.00003520484],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4888016,0.0008144685,0.4908805,0.0004313916,0.0001447589,0.0001121522,0.0006401314,0.0008812041,0.01729382],"genre_scores_gemma":[0.9510328,0.0002574404,0.03871734,0.00006872048,0.00008096519,0.0001202234,0.0004417397,0.0001700977,0.009110583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004633462,"threshold_uncertainty_score":0.01550043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004905713422251415,"score_gpt":0.2242470595699015,"score_spread":0.2193413461476501,"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."}}