{"id":"W3005147209","doi":"10.1145/2775051.2676992","title":"Principal Type Schemes for Gradual Programs","year":2015,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Type inference; Computer science; Inference; Programming language; Correctness; Static analysis; System F; Type (biology); Type theory; Modular design; Theoretical computer science; Subtyping; Artificial intelligence; Lambda calculus","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":[0.000479339,0.0001503944,0.0001818511,0.00005109928,0.00009415143,0.0003213886,0.001329217,0.00008178671,0.000002290222],"category_scores_gemma":[0.0004058384,0.0001159618,0.00005423151,0.0002394919,0.00004986121,0.0003772389,0.000297316,0.00008041566,0.0001546806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002355554,"about_ca_system_score_gemma":0.0001135457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007259764,"about_ca_topic_score_gemma":0.00005996406,"domain_scores_codex":[0.9987167,0.0000424278,0.0002019466,0.0003619349,0.000294692,0.0003822928],"domain_scores_gemma":[0.9986941,0.0001211953,0.0001223916,0.0006745866,0.0002049457,0.0001828293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007669356,0.0003293405,0.02750912,0.000174767,0.0001179404,0.00004199484,0.005643891,0.00002229391,0.0001081784,0.7272767,0.006317505,0.2323816],"study_design_scores_gemma":[0.001027455,0.001263145,0.0006131211,0.000009710539,0.0000273324,0.00002580948,0.0002706845,0.004734312,0.0008256104,0.0322022,0.9585447,0.0004558769],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3618617,0.004155885,0.5775871,0.004639448,0.01460239,0.005089331,0.000007759088,0.003719748,0.02833664],"genre_scores_gemma":[0.962451,0.000001700716,0.03630156,0.0001054989,0.0003510369,0.00005241715,0.0000199615,0.0000120059,0.0007048208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9522272,"threshold_uncertainty_score":0.4728787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119697619469658,"score_gpt":0.310158053476333,"score_spread":0.1981882915293672,"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."}}