{"id":"W2739559489","doi":"10.1155/2017/1046161","title":"A Language and Preprocessor for User-Controlled Generation of Synthetic Programs","year":2017,"lang":"en","type":"article","venue":"Scientific Programming","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Qualcomm","keywords":"Preprocessor; Computer science; Code (set theory); Programming language; Range (aeronautics); Natural language processing; Code generation; Artificial intelligence; Key (lock); Operating system; Set (abstract data type)","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001581879,0.00009556948,0.0001832749,0.0001223729,0.0005241756,0.001857979,0.0009008969,0.00004094529,0.000001063731],"category_scores_gemma":[0.002013819,0.00008188859,0.00006286439,0.0001511282,0.0002089681,0.0004788995,0.0002593013,0.00005846542,0.000002153771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001731411,"about_ca_system_score_gemma":0.00007399422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001251741,"about_ca_topic_score_gemma":0.00001750003,"domain_scores_codex":[0.9986494,0.00001889771,0.000191463,0.0005006743,0.0003186913,0.0003208408],"domain_scores_gemma":[0.9984613,0.0001428227,0.0001504916,0.0009644191,0.0001992995,0.00008167427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001953853,0.0001013129,0.004282248,0.0001969047,0.00002659121,0.000003327397,0.002208502,0.00001792186,0.01718965,0.00228326,0.00004460398,0.9736261],"study_design_scores_gemma":[0.01169998,0.0009233266,0.008607007,0.0005671114,0.00009876419,0.00004970173,0.0005313446,0.7604211,0.1983069,0.001976554,0.01561632,0.001201923],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6630353,0.0003424055,0.3343385,0.0001517856,0.0005432922,0.001390089,0.000001714615,0.0001748482,0.0000221399],"genre_scores_gemma":[0.8925104,8.010623e-7,0.1064761,0.000001523897,0.00004557861,0.0003788685,0.000003471455,0.000008787174,0.0005744559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9724242,"threshold_uncertainty_score":0.9991782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03921889153440276,"score_gpt":0.3076258757506566,"score_spread":0.2684069842162538,"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."}}