{"id":"W2570857834","doi":"10.1145/2990497","title":"Generating API Call Rules from Version History and Stack Overflow Posts","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Software Engineering and Methodology","topic":"Software Engineering Research","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Android (operating system); Application programming interface; Cluster analysis; World Wide Web; Precision and recall; Set (abstract data type); Baseline (sea); Information retrieval; Operating system; Programming language; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0005656068,0.0002151385,0.0002749622,0.0001947087,0.0003157406,0.0001131905,0.0006934226,0.0001775526,0.00001857974],"category_scores_gemma":[0.003527179,0.0002276147,0.0000534092,0.00004483245,0.00008056818,0.0003516882,0.00009402209,0.0004369458,0.00001103555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001266278,"about_ca_system_score_gemma":0.00005059572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003573251,"about_ca_topic_score_gemma":0.00001034867,"domain_scores_codex":[0.9986622,0.0001162223,0.0001718737,0.0005254853,0.0001854658,0.0003387711],"domain_scores_gemma":[0.9948199,0.003759246,0.00005321233,0.001129336,0.00005377149,0.0001844918],"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":[0.0001347077,0.0001649221,0.01030045,0.0003514674,0.0005152538,0.0002408867,0.004927955,0.07871324,0.05878344,0.00105877,0.001221344,0.8435876],"study_design_scores_gemma":[0.006771334,0.001595649,0.4023952,0.0007732263,0.0002711784,0.0005486846,0.0001318719,0.4741397,0.04160165,0.002062429,0.06571651,0.003992602],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2449581,0.0009061289,0.7525883,0.000145679,0.0009735481,0.00006952114,0.0000163536,0.0003398684,0.000002505103],"genre_scores_gemma":[0.1242525,0.0002002048,0.8751961,0.00006892461,0.00008115394,0.00001951669,0.000004212949,0.00002861924,0.0001487393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.839595,"threshold_uncertainty_score":0.9281857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08205151378663754,"score_gpt":0.3089872292756147,"score_spread":0.2269357154889771,"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."}}