{"id":"W4387124006","doi":"10.1109/re57278.2023.00060","title":"Leveraging User Feedback for Requirements Through Trend and Narrative Analysis","year":2023,"lang":"en","type":"article","venue":"","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Narrative; Computer science; User story; Leverage (statistics); Perception; Work (physics); User requirements document; Plan (archaeology); Knowledge management; Data science; Software; Software development; Engineering; Psychology","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":[0.02757606,0.001273746,0.0005830259,0.01505869,0.001777432,0.006856241,0.001460016,0.001003423,0.002721145],"category_scores_gemma":[0.09549253,0.0006854555,0.0008157864,0.007477381,0.001658534,0.01313573,0.004240707,0.001768764,0.001081193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003410036,"about_ca_system_score_gemma":0.003114159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004119619,"about_ca_topic_score_gemma":0.006914658,"domain_scores_codex":[0.9788457,0.01120951,0.00197384,0.001944089,0.005466359,0.0005603885],"domain_scores_gemma":[0.8520488,0.1090175,0.009846008,0.007605798,0.02013829,0.001343623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004460609,0.000305332,0.06038067,0.002995272,0.0001561754,0.001464407,0.3972096,0.005009261,0.01373481,0.04011077,0.0112163,0.4669713],"study_design_scores_gemma":[0.000109978,0.0007362323,0.06670558,0.004617786,0.0002604874,0.001424976,0.4010488,0.1552498,0.02940933,0.1125388,0.2272921,0.0006062317],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3650853,0.0009768556,0.5846107,0.004766189,0.0002196032,0.00300366,0.007418854,0.002594986,0.03132385],"genre_scores_gemma":[0.5856137,0.0009142907,0.4002385,0.0003450923,0.00009593292,0.002217761,0.00480607,0.0006102588,0.005158452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02757606,"threshold_uncertainty_score":0.1458379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07008524265387796,"score_gpt":0.3358745192096667,"score_spread":0.2657892765557887,"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."}}