{"id":"W4225138414","doi":"10.1145/3527320","title":"Effects, capabilities, and boxes: from scope-based reasoning to type-based reasoning and back","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Deutsche Forschungsgemeinschaft","keywords":"Soundness; Computer science; Lift (data mining); Class (philosophy); Scope (computer science); Type (biology); Artificial intelligence; Programming language; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008588449,0.00106367,0.001093805,0.002585455,0.001708904,0.006425862,0.003032306,0.002465854,0.006103214],"category_scores_gemma":[0.01526043,0.001611421,0.002482227,0.001790467,0.01012539,0.0197639,0.009817996,0.005083207,0.001267828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001825036,"about_ca_system_score_gemma":0.002461982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006092336,"about_ca_topic_score_gemma":0.005009859,"domain_scores_codex":[0.9952375,0.001438094,0.0004238228,0.000855615,0.001579679,0.0004652772],"domain_scores_gemma":[0.9898371,0.00520788,0.0005290579,0.00334339,0.0006843997,0.0003981734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001548174,0.00005761851,0.001587894,0.0002518289,0.00006198967,0.0002839376,0.002023431,0.01227742,0.002419436,0.8673545,0.003944972,0.1095822],"study_design_scores_gemma":[0.00004142031,0.00004444174,0.0003208162,0.0002298256,0.0001010026,0.0001953355,0.0003533362,0.06116342,0.006558619,0.9012274,0.02970121,0.0000632527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008889156,0.0005024016,0.9818118,0.001162757,0.00008985858,0.00007678985,0.0001164186,0.001983092,0.005367685],"genre_scores_gemma":[0.2840705,0.001553899,0.7036898,0.001135132,0.0002404039,0.0002296237,0.0003425878,0.001412954,0.007325028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008588449,"threshold_uncertainty_score":0.04542059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065062732676612,"score_gpt":0.2381885877176644,"score_spread":0.2275379603908982,"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."}}