{"id":"W3203221575","doi":"10.3390/a14100289","title":"Comparing Commit Messages and Source Code Metrics for the Prediction Refactoring Activities","year":2021,"lang":"en","type":"article","venue":"Algorithms","topic":"Software Engineering Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Code refactoring; Computer science; Commit; Java; Code smell; Metric (unit); Source code; Code (set theory); Class (philosophy); Software; Software metric; Data mining; Programming language; Machine learning; Artificial intelligence; Software quality; Software development; Set (abstract data type); Database","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":[0.003147343,0.001580099,0.001032269,0.007957292,0.000409162,0.001064126,0.0008654515,0.001219829,0.0006259615],"category_scores_gemma":[0.02044155,0.0003205249,0.000671418,0.004550218,0.0002809638,0.001858784,0.0006666378,0.001297687,0.001079365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005361067,"about_ca_system_score_gemma":0.0009537348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006976449,"about_ca_topic_score_gemma":0.01048078,"domain_scores_codex":[0.996972,0.0005871729,0.0002833491,0.0008796433,0.00105309,0.0002247512],"domain_scores_gemma":[0.978779,0.01128675,0.003175976,0.001953389,0.004048913,0.0007559512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004713031,0.000676918,0.4537446,0.0004904721,0.0002991487,0.0001700392,0.00035556,0.03528194,0.008451591,0.0006946002,0.009362284,0.4900016],"study_design_scores_gemma":[0.00004316084,0.00057918,0.2191421,0.0001306279,0.0001237929,0.0003532119,0.0003201749,0.758829,0.01250793,0.002369249,0.00552767,0.00007388229],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8263209,0.00308252,0.1523479,0.0005066537,0.0002091005,0.000240664,0.008193599,0.006855818,0.002242872],"genre_scores_gemma":[0.8916025,0.0005732886,0.09043286,0.00005555272,0.0000969315,0.0001607698,0.01551393,0.0002811946,0.001283005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007957292,"threshold_uncertainty_score":0.01664495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05110975156882941,"score_gpt":0.2871362250593349,"score_spread":0.2360264734905055,"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."}}