{"id":"W2888095436","doi":"10.1002/spe.2624","title":"C: Adding modern programming language features to C","year":2018,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Programming language; Garbage collection; Software engineering; Third-generation programming language; Programming paradigm; Second-generation programming language; Garbage; Fifth-generation programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003227621,0.0001540657,0.0001387957,0.00006766428,0.0003589422,0.0005937094,0.0005340928,0.00006703076,0.000007357642],"category_scores_gemma":[0.0009840732,0.0001291659,0.00003022021,0.000365454,0.00009615011,0.00143259,0.0003560065,0.0001296834,0.00009044896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002329018,"about_ca_system_score_gemma":0.00003797275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000272354,"about_ca_topic_score_gemma":0.00003754537,"domain_scores_codex":[0.9985631,0.00006614513,0.0001581186,0.0005186376,0.0002887463,0.0004052518],"domain_scores_gemma":[0.998904,0.0001854567,0.00009834059,0.0004654962,0.000154152,0.0001925425],"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":[0.00002182024,0.00005253685,0.0006114776,0.00001848548,0.00001299183,0.00006571337,0.1611012,0.000001012062,0.0007648391,0.02209432,0.0004993571,0.8147562],"study_design_scores_gemma":[0.0005554704,0.001183568,0.001083227,0.0000481429,0.00002775757,0.000937617,0.03272944,0.0008065274,0.008208126,0.003526455,0.94975,0.001143679],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01830694,0.0012221,0.9756595,0.0006815428,0.0006084003,0.0003463989,4.509351e-7,0.0005666502,0.002608014],"genre_scores_gemma":[0.834487,0.00001079165,0.1636119,0.001202745,0.0002416359,0.00007874618,8.584172e-7,0.000009825829,0.0003564491],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9492506,"threshold_uncertainty_score":0.5725153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808132005625616,"score_gpt":0.3071433496998017,"score_spread":0.2890620296435455,"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."}}