{"id":"W2146648240","doi":"10.1109/icpc.2009.5090025","title":"Automatic classication of large changes into maintenance categories","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Waterloo","funders":"","keywords":"Commit; Computer science; Metadata; Categorization; Software maintenance; Task (project management); Programming language; Information retrieval; Software; Artificial intelligence; Database; Software system; World Wide Web; Engineering","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":[0.0002185851,0.00005728788,0.00008600422,0.0000948649,0.00002831582,0.0000314202,0.0004923005,0.00002675405,0.00001660392],"category_scores_gemma":[0.0002701165,0.00004713552,0.00001626771,0.0003756624,0.00001775656,0.0001709217,0.00006881721,0.00005452845,0.00002721015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003493924,"about_ca_system_score_gemma":0.00003238301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001323425,"about_ca_topic_score_gemma":0.00001280932,"domain_scores_codex":[0.9993512,0.00001429673,0.00009517893,0.0001431809,0.0002092445,0.0001869178],"domain_scores_gemma":[0.999324,0.0001305487,0.00002982958,0.0003889367,0.00008686786,0.00003982454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001942694,0.0001343528,0.002431377,0.0000992222,0.00001266975,0.000006556302,0.00311857,0.00004964304,0.00686457,0.6677464,0.007405798,0.3121289],"study_design_scores_gemma":[0.0005885458,0.0004991672,0.3799311,0.00009565822,0.000004434381,0.00001420099,0.0001262532,0.4948995,0.07534457,0.04047682,0.007603203,0.0004166026],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06428909,0.00009625124,0.9280586,0.00633452,0.0001024461,0.0001069069,3.435091e-7,0.00047416,0.0005377218],"genre_scores_gemma":[0.9406384,0.000008188727,0.05882395,0.0001242584,0.00001634678,0.000007095802,7.359809e-7,0.000002718751,0.0003782631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8763493,"threshold_uncertainty_score":0.1922131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189253959451926,"score_gpt":0.2734799224548978,"score_spread":0.2615873828603786,"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."}}