{"id":"W3104924517","doi":"10.48550/arxiv.2010.14094","title":"Abstracting Gradual Typing Moving Forward: Precise and Space-Efficient (Technical Report)","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Space (punctuation); Computer science; Typing; Artificial intelligence; Speech recognition; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005798403,0.0003472431,0.0004431224,0.0001773529,0.0002527472,0.0003339341,0.001069001,0.000334512,0.000005121731],"category_scores_gemma":[0.0001778336,0.0003756067,0.0002098274,0.0004242672,0.000106766,0.0002282867,0.002934875,0.0008291886,0.00003539928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001811745,"about_ca_system_score_gemma":0.0001876109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002249802,"about_ca_topic_score_gemma":0.00002577205,"domain_scores_codex":[0.9974009,0.0001104323,0.0003664031,0.001527475,0.0001496224,0.000445157],"domain_scores_gemma":[0.9978811,0.0001478913,0.0005619814,0.0009916923,0.0001259711,0.0002913714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005245702,0.0003090718,0.005950903,0.0006808789,0.0002928214,0.01123693,0.002025514,0.09032493,0.0003541658,0.867157,0.000587001,0.02102828],"study_design_scores_gemma":[0.0007144801,0.0001386325,0.002982271,0.0001399288,0.0001639572,0.000511631,0.0004280528,0.9100632,0.0002630052,0.07891092,0.004362096,0.001321838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06280304,0.0001390799,0.9306008,0.0001914751,0.0008187668,0.0004620778,0.000001778881,0.0005611309,0.00442188],"genre_scores_gemma":[0.9939781,0.00003966545,0.005334445,0.00002828426,0.000161842,0.000001931508,0.000008714261,0.00002190157,0.0004251177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9311751,"threshold_uncertainty_score":0.9998696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07572697157849342,"score_gpt":0.2139154288219637,"score_spread":0.1381884572434703,"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."}}