{"id":"W4400266862","doi":"10.1145/3643991.3649106","title":"Mining Our Way Back to Incremental Builds for DevOps Pipelines","year":2024,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"DevOps; Computer science; Pipeline transport; Pipeline (software); Data science; Software engineering; Engineering; Software deployment; Programming language","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":[0.0003458993,0.0001132815,0.0001005056,0.0001297666,0.00006898848,0.0003097333,0.0005016486,0.000038988,0.000008356857],"category_scores_gemma":[0.0002023128,0.00009319211,0.0000547342,0.0003282758,0.000005166614,0.0002158238,0.000257046,0.00004711908,0.0001313933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000339217,"about_ca_system_score_gemma":0.00003985847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005815291,"about_ca_topic_score_gemma":0.00000976806,"domain_scores_codex":[0.9990934,0.00001261924,0.0001629786,0.0003598793,0.0001370987,0.0002340147],"domain_scores_gemma":[0.9993395,0.0002176459,0.00001416905,0.0002892428,0.00005736628,0.00008203123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000235896,0.00001463919,0.0006139874,0.00003880756,0.000008413698,0.000006789369,0.0003379335,0.000008326794,0.0005778037,0.005199582,0.8834525,0.1097389],"study_design_scores_gemma":[0.0004718642,0.0009470021,0.0008458997,0.000897576,0.00002641037,0.0001383883,0.0001463534,0.6505725,0.04591158,0.05951732,0.2391796,0.001345497],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004936573,0.00008647813,0.9782273,0.004185166,0.0005421557,0.0001881422,0.000002280727,0.01068349,0.00114847],"genre_scores_gemma":[0.2842176,7.147765e-7,0.713187,0.001036296,0.0001528215,0.00003596144,0.000001714085,0.00001126139,0.001356593],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6505642,"threshold_uncertainty_score":0.3800264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04457062577632592,"score_gpt":0.3248629375192195,"score_spread":0.2802923117428936,"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."}}