{"id":"W1987023923","doi":"10.1145/1569901.1570220","title":"Evolving java objects using a grammar-based approach","year":2009,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Programming language; Java; Executable; Object-oriented programming; Scala; Generics in Java; Grammar; Java annotation; Suite; Test suite; Real time Java; Genetic programming; Artificial intelligence; Test case","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":[0.001294708,0.000356995,0.0005362797,0.0008478848,0.0007417582,0.001935806,0.002288958,0.001233306,0.001654427],"category_scores_gemma":[0.002911212,0.0005150227,0.00110604,0.0007093533,0.001427255,0.001488395,0.001783906,0.001240453,0.0007625532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008780645,"about_ca_system_score_gemma":0.001266949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001943349,"about_ca_topic_score_gemma":0.002257186,"domain_scores_codex":[0.9992499,0.0001447218,0.0000554129,0.0001161853,0.0003788829,0.00005484378],"domain_scores_gemma":[0.9991167,0.000323457,0.0000539508,0.0002323838,0.0002132894,0.00006019467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000541234,0.0002260589,0.001896932,0.0002420647,0.00009678213,0.0005803651,0.001137472,0.2786677,0.03033748,0.4591274,0.004114104,0.2235195],"study_design_scores_gemma":[0.00006892842,0.00007693929,0.0005278214,0.00007053153,0.00008438258,0.0003978597,0.0001576898,0.7019154,0.0147854,0.2094108,0.07243771,0.00006663852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01080087,0.0001526617,0.980962,0.0002351092,0.00007096599,0.0001078069,0.00004411113,0.001289814,0.00633671],"genre_scores_gemma":[0.08879489,0.0003618025,0.9039691,0.0001987559,0.00002653624,0.0002608143,0.0002982644,0.0006130107,0.005476745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002288958,"threshold_uncertainty_score":0.006847143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424239627315119,"score_gpt":0.2548619523944566,"score_spread":0.2306195561213054,"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."}}