{"id":"W2285418831","doi":"10.7287/peerj.preprints.1771v1","title":"Judging a commit by its cover; or can a commit message predict build failure?","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Commit; Computer science; Code (set theory); Proxy (statistics); Source code; Computer security; Database; Programming language; Machine learning","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":[0.006642217,0.0006027412,0.0006151563,0.00307639,0.0005420878,0.00186438,0.0006497487,0.001139295,0.001636441],"category_scores_gemma":[0.08761615,0.0003250594,0.0003220313,0.002118037,0.001017206,0.003686262,0.001531739,0.001460345,0.001122287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004968196,"about_ca_system_score_gemma":0.0006983595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003849553,"about_ca_topic_score_gemma":0.009296868,"domain_scores_codex":[0.9959083,0.001061124,0.0004673988,0.0007818288,0.001354908,0.0004265375],"domain_scores_gemma":[0.9058462,0.0571371,0.01740227,0.006847434,0.009736785,0.003030185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004529085,0.0001061915,0.914763,0.0001647044,0.0001674036,0.000115454,0.001225023,0.004501176,0.005246272,0.000961023,0.003395058,0.06890175],"study_design_scores_gemma":[0.00002677884,0.000289697,0.8790768,0.0001015052,0.00008344834,0.0002817322,0.00211973,0.1016947,0.006087122,0.006521377,0.00359001,0.000126978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725789,0.0002673122,0.02135141,0.0009894891,0.00007506087,0.00004311707,0.001075489,0.0006266587,0.002992531],"genre_scores_gemma":[0.995007,0.00003860822,0.003699135,0.00006940997,0.0000397867,0.00001401464,0.0007017227,0.0000646418,0.0003657022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006642217,"threshold_uncertainty_score":0.03512788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01377722724391636,"score_gpt":0.245285266788623,"score_spread":0.2315080395447066,"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."}}