{"id":"W2401620832","doi":"10.1145/2901739.2903496","title":"The relationship between commit message detail and defect proneness in Java projects on GitHub","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Commit; Computer science; Explanatory power; Java; Code (set theory); Predictive power; Programming language; Database; Set (abstract data type)","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":[0.0009144241,0.00008710394,0.00008528544,0.0001129799,0.0001225775,0.0001269453,0.0005304579,0.0000473267,0.000001793632],"category_scores_gemma":[0.001984025,0.00004422794,0.00002059224,0.0003611853,0.00005565485,0.0002346813,0.0002137003,0.0001458362,0.00004770574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006005201,"about_ca_system_score_gemma":0.00005378886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002396834,"about_ca_topic_score_gemma":0.00005349658,"domain_scores_codex":[0.9989678,0.0001221738,0.0001259839,0.0002489446,0.0002651181,0.0002699528],"domain_scores_gemma":[0.9900586,0.009355351,0.00001988547,0.0004794622,0.00002820743,0.0000584864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002478163,0.000006951739,0.9645792,0.000007870993,0.000003937415,0.000003850275,0.00009350912,0.000003885555,0.00001500816,0.01369782,0.0001344201,0.0214511],"study_design_scores_gemma":[0.0002658825,0.0000552499,0.9963613,0.00005217793,9.725256e-7,0.000002132943,0.00000565921,0.0002103815,0.0005250755,0.002043429,0.0003923771,0.00008537717],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8817577,0.00008818056,0.1140893,0.002611312,0.00005884286,0.0003797461,7.887654e-7,0.0002156996,0.0007984165],"genre_scores_gemma":[0.9973699,0.00000442394,0.001608035,0.00001503668,0.00002002366,0.00004990216,1.884752e-7,0.00000817321,0.0009242699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1156122,"threshold_uncertainty_score":0.2375206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06137851503349717,"score_gpt":0.2916415823247079,"score_spread":0.2302630672912107,"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."}}