{"id":"W2155915714","doi":"10.1109/splc.2011.27","title":"Automatic Derivation of a Product Performance Model from a Software Product Line Model","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Unified Modeling Language; Model transformation; Programming language; Software product line; Software engineering; Software; Software development; Artificial intelligence","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":[0.001534033,0.001288119,0.0005323782,0.002039404,0.0004883366,0.002292234,0.001170626,0.0008480516,0.003201263],"category_scores_gemma":[0.005312669,0.0009659252,0.001832201,0.0009478186,0.0006178566,0.001319461,0.001239517,0.001314983,0.001880503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460175,"about_ca_system_score_gemma":0.002909763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006089626,"about_ca_topic_score_gemma":0.00458171,"domain_scores_codex":[0.9985661,0.0002438089,0.00009963325,0.000207871,0.0008093427,0.00007333216],"domain_scores_gemma":[0.9976431,0.0009818588,0.0002343881,0.0003896647,0.0006999605,0.00005100469],"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":[0.0001850493,0.0002074578,0.004484038,0.0007574927,0.0001063319,0.001269169,0.001077091,0.7053721,0.04267208,0.071207,0.005042999,0.1676192],"study_design_scores_gemma":[0.00002431174,0.00006748864,0.0006617772,0.0000933043,0.00005051842,0.0001771111,0.00008396247,0.9569395,0.01378614,0.009932192,0.01815299,0.00003068176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01283582,0.00006880819,0.9788342,0.00008472217,0.00002066517,0.0001786124,0.0007498338,0.004055972,0.00317146],"genre_scores_gemma":[0.1792173,0.0003729899,0.80939,0.00004569648,0.00001982621,0.0006210878,0.005672473,0.00151048,0.003150125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006089626,"threshold_uncertainty_score":0.01210839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048617323998261,"score_gpt":0.270819739072591,"score_spread":0.1659580066727649,"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."}}