{"id":"W2771651905","doi":"10.1109/esem.2017.46","title":"Which Version Should Be Released to App Store?","year":2017,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Mobile apps; Computer science; Analytics; Predictive analytics; Random forest; Open source; Analogical reasoning; App store; Smartphone app; Mobile device; Data science; Artificial intelligence; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002693383,0.00007681591,0.000077298,0.00008716605,0.0002306423,0.0003272901,0.001893306,0.0000482591,0.00006275185],"category_scores_gemma":[0.001320078,0.00006870688,0.00002407226,0.0001568588,0.00001315714,0.000349132,0.0007414757,0.0001337202,0.0005166949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005809369,"about_ca_system_score_gemma":0.00005356835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001580112,"about_ca_topic_score_gemma":0.00003678594,"domain_scores_codex":[0.9989296,0.00001256479,0.00006706339,0.0002984256,0.0004262362,0.0002660843],"domain_scores_gemma":[0.9980522,0.0001781917,0.00001670824,0.001464365,0.0000953936,0.0001931592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003777369,0.0001359568,0.05220326,0.00005575379,0.00003917239,0.00007526838,0.0008251185,0.001357902,0.006700279,0.02432987,0.8502854,0.06395426],"study_design_scores_gemma":[0.001004731,0.0003250861,0.4538061,0.00006047664,0.000004345731,0.00001101444,0.00002653294,0.06565498,0.02578902,0.0002999181,0.4523286,0.0006892012],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09970929,0.0000155364,0.8504241,0.02896481,0.0008108371,0.0002825441,0.000002133066,0.001081919,0.01870888],"genre_scores_gemma":[0.960516,0.000001236036,0.0356763,0.0003606185,0.00006356226,0.000009229764,8.911032e-7,0.00000926424,0.003362912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8608067,"threshold_uncertainty_score":0.664124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04474050663246724,"score_gpt":0.3137634228131647,"score_spread":0.2690229161806975,"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."}}