{"id":"W4365211599","doi":"10.1145/3591269","title":"flap: A Deterministic Parser with Fused Lexing","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"European Research Council; Horizon 2020 Framework Programme; Isaac Newton Trust; European Commission","keywords":"Computer science; Security token; Parsing; Parser combinator; Programming language; Context (archaeology); LR parser; Modularity (biology); Ambiguity; Interface (matter); Theoretical computer science; Parallel computing; Operating system","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":[0.002599659,0.001675437,0.001245899,0.001745096,0.001008492,0.00343561,0.004235371,0.002172055,0.01514209],"category_scores_gemma":[0.008863979,0.002150722,0.002998195,0.001835152,0.00313166,0.007132077,0.005786314,0.003254775,0.009170741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002020492,"about_ca_system_score_gemma":0.004815814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005403544,"about_ca_topic_score_gemma":0.00646093,"domain_scores_codex":[0.9970113,0.0004430301,0.0003324531,0.0009353338,0.0009775606,0.0003002624],"domain_scores_gemma":[0.9960998,0.001315267,0.0002375763,0.001509525,0.0007141988,0.0001234623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001104212,0.0002932348,0.004604423,0.001015493,0.000232983,0.001244607,0.001249511,0.05615489,0.04779697,0.2789066,0.1074951,0.499902],"study_design_scores_gemma":[0.0003138926,0.0002095763,0.0009339934,0.0001937695,0.0001971974,0.001503949,0.0002454707,0.3991923,0.1527501,0.2860861,0.1579397,0.0004337945],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004520654,0.0001129237,0.8793535,0.000205978,0.0001214064,0.0001251879,0.001054539,0.1114556,0.003050248],"genre_scores_gemma":[0.1053763,0.0002209116,0.8508801,0.0006213465,0.00009173248,0.0003136017,0.003404559,0.02809672,0.01099463],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01514209,"threshold_uncertainty_score":0.05065531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751960330658922,"score_gpt":0.2787272433611151,"score_spread":0.2612076400545259,"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."}}