{"id":"W4225333936","doi":"10.5267/j.ijdns.2022.2.011","title":"Understanding and predicting bugs fixed by API-migrations","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software bug; Computer science; Context (archaeology); Security bug; Schedule; Software engineering; Software; Computer security; Programming language; Biology; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001860849,0.00004739105,0.00006356058,0.0001580775,0.0003798125,0.0003952133,0.002327299,0.000008094225,0.000008272062],"category_scores_gemma":[0.0003546196,0.00004429429,0.000009391235,0.0004376984,0.0001268462,0.001625552,0.00200966,0.0002067006,2.193424e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001113738,"about_ca_system_score_gemma":0.0001466358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006769369,"about_ca_topic_score_gemma":0.000001928412,"domain_scores_codex":[0.998514,0.00002912189,0.0001751257,0.000199498,0.000923647,0.0001586108],"domain_scores_gemma":[0.9990379,0.0004561391,0.0001093858,0.0001955999,0.0001044597,0.00009658172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008753543,0.0002460557,0.527433,0.00002089457,0.0003083813,0.0003285974,0.00529619,0.04548857,0.009782643,0.06523962,0.2420326,0.1037359],"study_design_scores_gemma":[0.0007595175,0.0002414345,0.01714459,0.0000779007,0.00001006492,0.001476373,0.0005282838,0.9509346,0.0001443027,0.006032954,0.02241309,0.0002368758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08979904,0.0008916738,0.9054708,0.002524123,0.001158214,0.0000438385,0.00003988238,0.00002364643,0.00004881512],"genre_scores_gemma":[0.9855225,0.0001200329,0.01408441,0.00009980652,0.0001465243,9.592759e-7,0.000004589496,0.000002562651,0.00001861039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9054461,"threshold_uncertainty_score":0.432474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08412188676902072,"score_gpt":0.3226650559591267,"score_spread":0.238543169190106,"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."}}