{"id":"W1984007424","doi":"10.1007/pl00013319","title":"Even faster generalized LR parsing","year":2001,"lang":"en","type":"article","venue":"Acta Informatica","topic":"semigroups and automata theory","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Parsing; LR parser; Parsing expression grammar; Computer science; Property (philosophy); Top-down parsing; Parser combinator; Constant (computer programming); Grammar; Theory of computation; Rule-based machine translation; Symbol (formal); Algorithm; Artificial intelligence; Natural language processing; Programming language; Context-free grammar; L-attributed grammar","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":[0.002974675,0.002422023,0.002472005,0.00156699,0.001626392,0.005929313,0.002896006,0.003651557,0.06876382],"category_scores_gemma":[0.01280018,0.001498247,0.002664708,0.002501512,0.002107461,0.01492674,0.005679809,0.004737345,0.03063398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342271,"about_ca_system_score_gemma":0.002279536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002236115,"about_ca_topic_score_gemma":0.004418231,"domain_scores_codex":[0.9935644,0.002466763,0.0004104605,0.001661813,0.001131847,0.000764785],"domain_scores_gemma":[0.9820886,0.005352348,0.000279265,0.01053472,0.00146078,0.0002844047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001299909,0.0003391422,0.001460897,0.001650022,0.0003061993,0.0009872202,0.001235764,0.01083635,0.04249352,0.282291,0.2236057,0.4334943],"study_design_scores_gemma":[0.0002349642,0.0001318617,0.001183155,0.0002247086,0.0004082722,0.001156602,0.0006420787,0.09833328,0.03783109,0.7239553,0.1356693,0.000229371],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07113798,0.003672008,0.6657683,0.0100623,0.003784771,0.0003251706,0.006118571,0.1227182,0.1164128],"genre_scores_gemma":[0.467121,0.001192416,0.4302823,0.005438549,0.001655709,0.0002200321,0.01186816,0.02583499,0.05638696],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06876382,"threshold_uncertainty_score":0.2300379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139724967697632,"score_gpt":0.2294504689361343,"score_spread":0.2154779721663711,"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."}}