{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005268246,0.001076516,0.001308962,0.00243875,0.001860644,0.006788868,0.003742731,0.00204505,0.008045177],"category_scores_gemma":[0.01098278,0.001178963,0.002538187,0.003239387,0.005424831,0.01679159,0.005280978,0.00437,0.002231447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002822911,"about_ca_system_score_gemma":0.003889358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003372391,"about_ca_topic_score_gemma":0.002981788,"domain_scores_codex":[0.9938872,0.0009008093,0.001130436,0.001434737,0.002047148,0.0005996965],"domain_scores_gemma":[0.9913779,0.002045639,0.0008649932,0.003696252,0.001701382,0.0003138141],"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":[0.00005262553,0.00001476749,0.0008263078,0.00009978544,0.00001856678,0.0001166059,0.0002689717,0.0009990762,0.001270692,0.9806966,0.002406411,0.01322959],"study_design_scores_gemma":[0.00003573542,0.00004577147,0.0002438549,0.0001343037,0.00006983549,0.0004166965,0.0001805197,0.00888364,0.009722598,0.8755293,0.1046764,0.00006119633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00993808,0.0005748212,0.9641729,0.0006274745,0.0003817172,0.0001863784,0.001655072,0.002947501,0.01951607],"genre_scores_gemma":[0.2867057,0.001336373,0.6773955,0.001469193,0.0004570592,0.0008852431,0.003271649,0.002886028,0.02559318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008045177,"threshold_uncertainty_score":0.02786148,"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."}}