{"id":"W4398239325","doi":"10.1145/3639478.3643126","title":"Recovering Traceability Links between Release Notes and Related Software Artifacts","year":2024,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Global Institute for Water Security, University of Saskatchewan","keywords":"Traceability; Software engineering; Computer science; Requirements traceability; Transparency (behavior); Software evolution; Software development; Upgrade; Software; Process (computing); Software bug; Software maintenance; Code (set theory); Risk analysis (engineering); Software construction; Computer security; Programming language; Operating system; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01211221,0.002083004,0.0007683084,0.01122774,0.001734299,0.005283732,0.002449172,0.001879535,0.004180568],"category_scores_gemma":[0.09947615,0.001176762,0.0006851142,0.007026229,0.0008881312,0.006786939,0.006313781,0.0032298,0.002986019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002241933,"about_ca_system_score_gemma":0.005581069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0141646,"about_ca_topic_score_gemma":0.01288178,"domain_scores_codex":[0.9815173,0.00315811,0.001929015,0.002947633,0.009873415,0.00057462],"domain_scores_gemma":[0.8580101,0.04665177,0.02596644,0.03893268,0.02882004,0.001619023],"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":[0.001041082,0.001075551,0.07668961,0.002116036,0.0003606565,0.003702702,0.01152109,0.01661523,0.02154527,0.01943156,0.02047103,0.8254302],"study_design_scores_gemma":[0.0003950703,0.002398197,0.205633,0.004710956,0.001123877,0.004535168,0.01422978,0.2344443,0.1069081,0.1073103,0.3173216,0.0009895355],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2266592,0.003245569,0.7155551,0.002161348,0.00125587,0.001922976,0.01487729,0.01444155,0.01988114],"genre_scores_gemma":[0.4763505,0.001915354,0.4739125,0.0004547264,0.0003220704,0.001065448,0.02845312,0.002326464,0.01519973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0141646,"threshold_uncertainty_score":0.06405628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209240958948676,"score_gpt":0.2697056708987591,"score_spread":0.2476132613092723,"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."}}