{"id":"W1965772655","doi":"10.1109/msr.2013.6624048","title":"The MSR Cookbook: Mining a decade of research","year":2013,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Best practice; Scope (computer science); Artifact (error); Data science; Categorization; Theme (computing); Computer science; Library science; Political science; Public relations; World Wide Web","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":[0.001346071,0.00004993702,0.00006368497,0.0001257461,0.000146483,0.000184899,0.001495228,0.0000324482,0.00004880832],"category_scores_gemma":[0.001620799,0.00003133681,0.00002428498,0.0006205175,0.0001311632,0.0001975242,0.0005417932,0.000196603,0.0002026675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002857749,"about_ca_system_score_gemma":0.00008441228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001701062,"about_ca_topic_score_gemma":0.000006639159,"domain_scores_codex":[0.998539,0.00007970885,0.0001345868,0.0001736626,0.0006624904,0.0004105677],"domain_scores_gemma":[0.9943777,0.004497117,0.00001434927,0.0006657337,0.0003592142,0.00008585803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000110436,0.0001331805,0.05372307,0.0001154153,0.00009595322,0.00002782254,0.004802097,0.0004340189,0.01857696,0.2606503,0.2867571,0.374673],"study_design_scores_gemma":[0.001112369,0.0007264946,0.4321399,0.0002351692,0.000003016645,0.00006212981,0.001230153,0.3710668,0.07412788,0.02200769,0.09655532,0.0007331282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6356766,0.00073252,0.3355348,0.006649434,0.0003752939,0.0007726689,3.439393e-7,0.0005753313,0.0196831],"genre_scores_gemma":[0.9613294,0.00001534768,0.031916,0.00002484349,0.0000319028,0.0000571608,7.417473e-8,0.00000735089,0.006617943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3784168,"threshold_uncertainty_score":0.2778531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05897519482048948,"score_gpt":0.3519680068350489,"score_spread":0.2929928120145594,"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."}}