{"id":"W3004640575","doi":"10.1016/j.tcs.2020.01.035","title":"A computational complexity analysis of tunable type inference for Generic Universe Types","year":2020,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Type inference; Inference; Theoretical computer science; Reduction (mathematics); Time complexity; Type (biology); Boolean satisfiability problem; Programmer; Computational complexity theory; Mathematics; Algorithm; Programming language; Artificial intelligence","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":[0.000594519,0.0001377048,0.0003482859,0.0002090879,0.0002131533,0.000171378,0.001622368,0.00004043299,0.00004020476],"category_scores_gemma":[0.0001357358,0.0001143715,0.0001203516,0.003803892,0.001522604,0.0003169168,0.000715494,0.00007988472,0.00002333114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003203537,"about_ca_system_score_gemma":0.0002159771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001197604,"about_ca_topic_score_gemma":0.000001348408,"domain_scores_codex":[0.9982563,0.00007462644,0.0002848117,0.0005591004,0.0004803786,0.0003447998],"domain_scores_gemma":[0.9984161,0.0002909311,0.0001270996,0.0003677939,0.0005617047,0.0002364008],"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":[0.00001376926,0.00003894416,0.0002716476,0.00001707069,0.000054803,0.000002137993,0.0005887524,0.0166247,0.00009934694,0.9775264,0.00003621399,0.004726223],"study_design_scores_gemma":[0.0001506089,0.0002824704,0.0007599722,0.000001545856,0.00004746757,0.000001357186,0.000008989307,0.8225996,0.000212309,0.1755659,0.0002458065,0.0001239954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00733439,0.00002389483,0.9905106,0.0005332814,0.0002117546,0.0001936269,0.000003772193,0.0001110404,0.00107758],"genre_scores_gemma":[0.8387729,0.000001165553,0.1607876,0.0003747301,0.00004678061,0.000002682271,0.000005860556,0.000003583563,0.000004684622],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8314385,"threshold_uncertainty_score":0.5610098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05368918681418559,"score_gpt":0.2856643271098364,"score_spread":0.2319751402956508,"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."}}