{"id":"W1540115833","doi":"10.14279/tuj.eceasst.3.33","title":"Optimizing Pattern Matching Compilation by Program Transformation","year":2024,"lang":"en","type":"article","venue":"","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; Rewriting; Pattern matching; Programming language; Program transformation; Compiler; Matching (statistics); Transformation (genetics); Implementation; Automaton; Functional programming; Code (set theory); Layer (electronics); Theoretical computer science; Set (abstract data type)","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":[0.0006573714,0.0005598136,0.0005016212,0.0005077922,0.0002769439,0.0008186326,0.0006790749,0.0003836654,0.002341492],"category_scores_gemma":[0.002701229,0.0003014633,0.000740118,0.0006775958,0.0005361141,0.0008236985,0.0008197337,0.0007233236,0.00126755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003985862,"about_ca_system_score_gemma":0.0009401651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000759449,"about_ca_topic_score_gemma":0.0007804969,"domain_scores_codex":[0.9990537,0.0001935161,0.00008121092,0.0002134469,0.0003023202,0.0001559372],"domain_scores_gemma":[0.9986972,0.000438737,0.0001046603,0.0005259098,0.0002098747,0.00002367557],"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":[0.0004351245,0.0004418726,0.005021757,0.0007748911,0.0001595079,0.0006402673,0.0004347827,0.1566885,0.1962663,0.07962005,0.009205233,0.5503117],"study_design_scores_gemma":[0.0001111919,0.0003192799,0.001723688,0.00006018478,0.0001524455,0.0005760809,0.0001240812,0.6543653,0.2663943,0.04838755,0.02773047,0.00005548189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04981226,0.0001297807,0.9320461,0.0001319628,0.00006886844,0.0001160376,0.0001076579,0.01284593,0.004741429],"genre_scores_gemma":[0.337572,0.000235497,0.6529365,0.0001618285,0.00003728553,0.0002346635,0.0005394535,0.003238546,0.005044053],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002341492,"threshold_uncertainty_score":0.007833004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019121461857135,"score_gpt":0.2651811129121465,"score_spread":0.2449898982935752,"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."}}