{"id":"W2023809115","doi":"10.1145/1011508.1011510","title":"Polymorphic specialization for ML","year":2004,"lang":"en","type":"article","venue":"ACM Transactions on Programming Languages and Systems","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Soundness; Computer science; Semantics (computer science); Programming language; Type inference; Functional programming; Recursion (computer science); Linear logic; Inference; Lambda calculus; Theoretical computer science; Operational semantics; Artificial intelligence","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":[0.0003438074,0.0001831489,0.0002243553,0.0001398465,0.0003573433,0.0005078339,0.0004227235,0.0001163227,0.000002750946],"category_scores_gemma":[0.00003125643,0.0001529755,0.00009916613,0.0002940629,0.0000426944,0.000260712,0.00001086437,0.00009854416,0.00001462321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005353554,"about_ca_system_score_gemma":0.00004185599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00051335,"about_ca_topic_score_gemma":0.00008268636,"domain_scores_codex":[0.9986823,0.00004667656,0.0002878988,0.0004188574,0.000220657,0.00034365],"domain_scores_gemma":[0.9990598,0.00007778955,0.0001077778,0.0005630153,0.0000788219,0.000112774],"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":[0.00001849336,0.0002343005,0.0001137884,0.0002577255,0.00009063385,0.00002322726,0.003126541,0.000890499,0.0002770406,0.4036014,0.0000362481,0.5913301],"study_design_scores_gemma":[0.01995071,0.0092215,0.001578783,0.0007127002,0.0005847103,0.002286155,0.0222501,0.01972096,0.01276157,0.0993723,0.8055215,0.00603901],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001619874,0.001248564,0.9943117,0.0004335662,0.0008725725,0.0008948388,0.000003607881,0.0003733886,0.0002418838],"genre_scores_gemma":[0.9845093,0.00003236402,0.01421627,0.00006405527,0.0002207375,0.0002824032,0.000009416517,0.00002055408,0.0006448273],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9828895,"threshold_uncertainty_score":0.6238161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675059458321067,"score_gpt":0.2806556860792817,"score_spread":0.253905091496071,"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."}}