{"id":"W4405602349","doi":"10.1109/icsme58944.2024.00082","title":"Take Loads Off Your Developers: Automated User Story Generation using Large Language Model","year":2024,"lang":"en","type":"article","venue":"","topic":"Persona Design and Applications","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada); University of Saskatchewan","funders":"","keywords":"Computer science; Programming language; Software engineering; Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002182164,0.001731929,0.0006621002,0.001536066,0.0005287151,0.001349722,0.001834664,0.001355309,0.005802505],"category_scores_gemma":[0.0148395,0.0005944071,0.0009875317,0.0005382893,0.0004407409,0.003138199,0.002450434,0.001151099,0.003728088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004297536,"about_ca_system_score_gemma":0.0006036029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001577258,"about_ca_topic_score_gemma":0.002814293,"domain_scores_codex":[0.9969006,0.001701489,0.0001514079,0.0005830266,0.0005530162,0.0001105902],"domain_scores_gemma":[0.9896847,0.007083402,0.0005709522,0.001423548,0.0008583244,0.0003791228],"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":[0.001529628,0.0008128695,0.006211217,0.001055011,0.0001281775,0.002759518,0.01056891,0.009363881,0.04080572,0.003855498,0.05205608,0.8708534],"study_design_scores_gemma":[0.0004919746,0.00100181,0.006585599,0.000257932,0.0001563405,0.003548036,0.006537659,0.7975472,0.07930885,0.0128195,0.09149161,0.000253458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1481917,0.0005685466,0.7472928,0.0009578134,0.000157067,0.0008256552,0.003207863,0.09317326,0.005625343],"genre_scores_gemma":[0.2911955,0.0002039176,0.6913602,0.0003452339,0.00005268355,0.0005182694,0.009188323,0.002953853,0.004182066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005802505,"threshold_uncertainty_score":0.01941133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0662054946242433,"score_gpt":0.3207182229715905,"score_spread":0.2545127283473472,"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."}}