{"id":"W3090289035","doi":"10.1145/3365438.3410964","title":"<i>mel</i> - model extractor language for extracting facts from models","year":2020,"lang":"en","type":"article","venue":"","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Extractor; Code (set theory); Programming language; Software; Software engineering; Code generation; KPI-driven code analysis; Base (topology); Artificial intelligence; Natural language processing; Software development; Software construction; Engineering; Operating system; Key (lock)","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":[0.002663446,0.002514739,0.001083086,0.00320437,0.0009442614,0.003759978,0.003241888,0.001816745,0.09293851],"category_scores_gemma":[0.01081734,0.001867692,0.002805442,0.002350815,0.001345707,0.007130889,0.003392141,0.003870255,0.04573211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443004,"about_ca_system_score_gemma":0.002077052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474121,"about_ca_topic_score_gemma":0.007429786,"domain_scores_codex":[0.9980943,0.0003923836,0.0004939329,0.0003663689,0.0005438721,0.0001091758],"domain_scores_gemma":[0.9949634,0.002593645,0.0004179498,0.001095306,0.0008230592,0.0001066111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006639452,0.0001696335,0.00257253,0.003815556,0.0002494961,0.001328948,0.001574584,0.009103943,0.01887431,0.3136095,0.4602128,0.1878247],"study_design_scores_gemma":[0.0001498266,0.00008987569,0.0004970533,0.000543398,0.00007726091,0.000809714,0.0002221545,0.06452461,0.03412247,0.05850597,0.8403262,0.0001312927],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0006927007,0.0000722793,0.8267225,0.0006598718,0.0001568206,0.0002973822,0.02357515,0.1382509,0.009572293],"genre_scores_gemma":[0.02179492,0.0003128237,0.8721468,0.0009305045,0.0001347241,0.001151736,0.05345229,0.03680547,0.01327073],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.09293851,"threshold_uncertainty_score":0.3109103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05637311964648813,"score_gpt":0.2619832851241646,"score_spread":0.2056101654776765,"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."}}