{"id":"W2518300910","doi":"10.1145/2951913.2951929","title":"Indexed codata types","year":2016,"lang":"en","type":"article","venue":"","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Guard (computer science); Computer science; Data type; Matching (statistics); Type (biology); Dual (grammatical number); Programming language; Theoretical computer science; Mathematics; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001515887,0.00005280531,0.00006533237,0.00002945706,0.00003542225,0.00006905133,0.0005626443,0.00003196534,0.00009371615],"category_scores_gemma":[0.00002581863,0.00002608732,0.00002103932,0.0001104957,0.00002123696,0.0002490389,0.0001656216,0.00001952363,0.00128703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001009908,"about_ca_system_score_gemma":0.00002264945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000039169,"about_ca_topic_score_gemma":0.00001975051,"domain_scores_codex":[0.9994475,0.00002088403,0.0000850024,0.0001828747,0.000113983,0.0001497177],"domain_scores_gemma":[0.999433,0.00003836185,0.00002696844,0.0004208084,0.00003143567,0.00004936154],"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":[6.262412e-7,0.00001111864,0.001551463,0.000001950712,0.000005304666,0.000005080745,0.0000452817,3.868588e-8,0.0003461173,0.881069,0.005449119,0.1115149],"study_design_scores_gemma":[0.0006001132,0.0001284329,0.003009866,0.000004822291,0.000003416386,0.00003946318,0.00001459827,0.0004317904,0.00580508,0.09565049,0.8940079,0.0003040079],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000512918,0.00005390541,0.9397323,0.0009118216,0.0004233859,0.00006574098,2.476048e-7,0.0002508391,0.05804881],"genre_scores_gemma":[0.9854694,0.000004638895,0.002961349,0.000165665,0.00006542808,0.000004344799,3.431625e-7,0.00000272158,0.01132612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9849565,"threshold_uncertainty_score":0.9994906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03022212442747627,"score_gpt":0.2485383866511031,"score_spread":0.2183162622236268,"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."}}