{"id":"W2154467091","doi":"10.1002/smr.1565","title":"An approach for mining service composition patterns from execution logs","year":2012,"lang":"en","type":"article","venue":"Journal of Software Evolution and Process","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Web service; Service (business); Set (abstract data type); Database; Quality of service; Differentiated service; Data mining; Service delivery framework; World Wide Web; Service design; Computer network; Programming language","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":[0.002090227,0.001813632,0.001363812,0.01477813,0.001016012,0.0021058,0.001619474,0.001472363,0.0009385393],"category_scores_gemma":[0.009820671,0.0007727616,0.001550599,0.006659077,0.0007684979,0.001952488,0.001057062,0.001182733,0.0009123542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009504624,"about_ca_system_score_gemma":0.002344043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008017613,"about_ca_topic_score_gemma":0.007975256,"domain_scores_codex":[0.9969586,0.0004989272,0.0004391133,0.0007784899,0.001159343,0.0001654435],"domain_scores_gemma":[0.9920704,0.003369855,0.001506195,0.001028558,0.001744328,0.000280679],"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":[0.0007275826,0.001709903,0.08057849,0.001254501,0.0005695792,0.002533401,0.001337167,0.07587079,0.04531687,0.006991465,0.006198236,0.7769121],"study_design_scores_gemma":[0.00006701497,0.0001513095,0.008257314,0.00008427336,0.0001210068,0.001125726,0.0004129233,0.9587376,0.0166612,0.009294392,0.005017223,0.00007003845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1200628,0.0006960365,0.859264,0.0005045569,0.00006371162,0.001120989,0.003946758,0.01302967,0.001311627],"genre_scores_gemma":[0.2536234,0.0003291872,0.7364889,0.00009798601,0.00004463351,0.000681608,0.007549142,0.0001969522,0.0009882353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01477813,"threshold_uncertainty_score":0.01594186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409179947278424,"score_gpt":0.2602709917047297,"score_spread":0.2461791922319455,"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."}}