{"id":"W4248497488","doi":"10.1145/2914770.2837670","title":"Abstracting gradual typing","year":2016,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Subtyping; Programming language; Exception handling; Typing; Type theory; Consistency (knowledge bases); Syntax; Type inference; Sophistication; Type safety; Language construct; Abstract interpretation; Artificial intelligence; Type (biology)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003372708,0.000111889,0.0001228411,0.00005416216,0.0001307489,0.0001894423,0.001084041,0.00005573607,0.00002220226],"category_scores_gemma":[0.000322509,0.00006877475,0.00004255708,0.0001202333,0.00003234717,0.0005886593,0.0002440865,0.00006912142,0.0006125497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001899344,"about_ca_system_score_gemma":0.00002738455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000961998,"about_ca_topic_score_gemma":0.00004167387,"domain_scores_codex":[0.9989845,0.00004404354,0.000187192,0.0003038035,0.0001709791,0.0003095029],"domain_scores_gemma":[0.9986573,0.0004816112,0.00014183,0.0005985778,0.00004202625,0.00007865649],"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":[0.000009898848,0.00007291575,0.02563173,0.00006273685,0.00006264618,0.00008961938,0.002008049,0.00000956084,0.005287576,0.34502,0.002117353,0.619628],"study_design_scores_gemma":[0.004047845,0.001058771,0.107173,0.0002640396,0.0001028986,0.0004101238,0.001342697,0.002947605,0.03801306,0.2543089,0.5868099,0.003521198],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3471828,0.00103885,0.5757047,0.008690319,0.006625106,0.0006207862,0.000003448592,0.002047117,0.05808686],"genre_scores_gemma":[0.9946305,0.000005137255,0.004421425,0.000115638,0.0002821675,0.000005429589,7.741952e-7,0.000007490256,0.0005314745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6474476,"threshold_uncertainty_score":0.7873292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04552239643461935,"score_gpt":0.2721415908594423,"score_spread":0.226619194424823,"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."}}