{"id":"W2018862503","doi":"10.1007/s10515-011-0099-7","title":"Decision support for the software product line domain engineering lifecycle","year":2012,"lang":"en","type":"article","venue":"Automated Software Engineering","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Athabasca University","funders":"","keywords":"Domain engineering; Feature-oriented domain analysis; Computer science; Domain analysis; Domain (mathematical analysis); Software engineering; Domain model; Software product line; Feature model; Feature (linguistics); Software development; Domain knowledge; Data mining; Software; Data science; Programming language; Software construction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001728425,0.0006151959,0.0005244788,0.0003130642,0.000280877,0.0001813293,0.001607511,0.0002013124,0.000009233397],"category_scores_gemma":[0.01224399,0.0005117289,0.0002439574,0.0009809763,0.00003673071,0.001352178,0.0005453107,0.0004858074,0.00005058992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002312006,"about_ca_system_score_gemma":0.00008033136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003697992,"about_ca_topic_score_gemma":4.411974e-7,"domain_scores_codex":[0.9966859,0.00004413788,0.0006362761,0.0006723343,0.0005100645,0.001451326],"domain_scores_gemma":[0.9906082,0.007271682,0.0001486891,0.001479217,0.0001790899,0.0003131462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001181099,0.00005281071,0.0004702336,0.0001749341,0.0001135376,0.00001032423,0.0005677961,0.9630677,0.001325337,0.001437713,0.001102902,0.03166495],"study_design_scores_gemma":[0.001861761,0.0003193779,0.02067704,0.0004305294,0.000125697,0.0004441013,0.00005015517,0.8813741,0.01851198,0.00103799,0.07231338,0.002853845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004659533,0.002206062,0.9707102,0.0001042128,0.004516936,0.0007915084,0.00001989519,0.01698987,0.000001840568],"genre_scores_gemma":[0.04656082,0.00004254414,0.9520571,0.00009306251,0.0006292218,0.0003845011,0.00001882655,0.0001560416,0.00005782942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08169352,"threshold_uncertainty_score":0.9997334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364243358208102,"score_gpt":0.2833247450238875,"score_spread":0.2596823114418065,"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."}}