{"id":"W4399851446","doi":"10.1145/3656445","title":"SpEQ: Translation of Sparse Codes using Equivalences","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Translation (biology); Computer science; Biology; Genetics","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":[0.001905465,0.001694476,0.0007823581,0.001213564,0.0007332119,0.001829445,0.00213958,0.001088863,0.0238858],"category_scores_gemma":[0.01175155,0.0009659791,0.001841205,0.001002686,0.001990945,0.003869713,0.005012284,0.002353366,0.008214493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009650964,"about_ca_system_score_gemma":0.00212854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00305742,"about_ca_topic_score_gemma":0.002955346,"domain_scores_codex":[0.9963367,0.0007076068,0.0003923765,0.0006314971,0.001516385,0.0004154107],"domain_scores_gemma":[0.9952595,0.001444134,0.000304257,0.001673168,0.001198788,0.0001202517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000979453,0.0003872716,0.004051105,0.001291876,0.0001402947,0.0008511477,0.001235531,0.06562177,0.03036562,0.3046194,0.1203593,0.4700972],"study_design_scores_gemma":[0.0003862084,0.0004729078,0.0009655372,0.0003192867,0.00006735739,0.0003921587,0.0004180108,0.4013331,0.1011861,0.3185058,0.1758119,0.0001416513],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01427856,0.000163614,0.9009535,0.0003402045,0.0003852242,0.0002209045,0.001617233,0.06929653,0.01274412],"genre_scores_gemma":[0.2133484,0.0002550917,0.7300268,0.0009808516,0.000233613,0.0008552083,0.007830638,0.03169438,0.014775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0238858,"threshold_uncertainty_score":0.07990599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05207368916312324,"score_gpt":0.3068119067114592,"score_spread":0.254738217548336,"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."}}