{"id":"W4246443804","doi":"10.1109/icse.2001.919194","title":"Holmes: an intelligent system to support software product line development","year":2005,"lang":"en","type":"article","venue":"Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Software product line; Computer science; Software engineering; Software development; Blackboard (design pattern); Product line; Software; Blackboard system; Software architecture; Feature (linguistics); Product (mathematics); Software system; Resource-oriented architecture; Software construction; Programming language; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008091268,0.0004566582,0.00040409,0.0003360005,0.0001020911,0.0001916083,0.003319902,0.0001112868,0.00003268986],"category_scores_gemma":[0.003122436,0.0003831622,0.0001189623,0.0005412969,0.00004360082,0.0008724342,0.0007925894,0.000424486,0.00007142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005814298,"about_ca_system_score_gemma":0.0001918148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003854045,"about_ca_topic_score_gemma":0.000002205103,"domain_scores_codex":[0.9970413,0.00001330477,0.0006942108,0.0007708484,0.0009205873,0.000559722],"domain_scores_gemma":[0.997715,0.000159393,0.0002714309,0.0005187048,0.001077225,0.0002582401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001768761,0.0007150116,0.003208662,0.0007582091,0.000376704,0.00001436994,0.005290836,0.5518188,0.009796522,0.1778425,0.004825505,0.245176],"study_design_scores_gemma":[0.002113371,0.002339855,0.01137148,0.0042362,0.00008940342,0.0004820213,0.0008535819,0.2031001,0.647251,0.002366456,0.1205951,0.005201497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04647864,0.00003466645,0.9491591,0.00060637,0.001537263,0.0004947032,0.00001726977,0.001465328,0.0002066069],"genre_scores_gemma":[0.2543059,0.00001639757,0.7445225,0.0001636828,0.0002671686,0.0001052809,0.000006559,0.00004674091,0.0005657991],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6374545,"threshold_uncertainty_score":0.999862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06818995543559302,"score_gpt":0.306293051461658,"score_spread":0.238103096026065,"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."}}