{"id":"W4405564895","doi":"10.1016/j.jss.2024.112307","title":"COMET: Generating commit messages using delta graph context representation","year":2024,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Commit; Comet; Context (archaeology); Representation (politics); Computer science; Graph; Delta; Theoretical computer science; Engineering; Astrobiology; Geology; Physics; Database; Aerospace engineering; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008102711,0.001305665,0.0005127982,0.003009026,0.0006185203,0.0008516244,0.001545682,0.001059364,0.002016197],"category_scores_gemma":[0.00911322,0.0004293362,0.0008052073,0.001634286,0.0004132757,0.001819989,0.00153481,0.001455914,0.0008862359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009228575,"about_ca_system_score_gemma":0.00191019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017908,"about_ca_topic_score_gemma":0.02095597,"domain_scores_codex":[0.9990996,0.0001919681,0.00005553384,0.0002298581,0.0003641627,0.00005888259],"domain_scores_gemma":[0.9963287,0.001360632,0.0003697838,0.0007694042,0.0009826546,0.0001889394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000681964,0.0003786063,0.01165022,0.001011632,0.0001930025,0.000864015,0.001268562,0.1146552,0.02795864,0.01816068,0.06864987,0.7545276],"study_design_scores_gemma":[0.00007712752,0.0002066797,0.002544699,0.00006791147,0.00008149881,0.0002585496,0.0003156142,0.9294383,0.01947366,0.02399329,0.02348816,0.00005462155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04877818,0.000720325,0.8970129,0.0007043215,0.0003049225,0.0008351519,0.005204067,0.04339277,0.003047343],"genre_scores_gemma":[0.4087309,0.0004732666,0.5600345,0.0004356036,0.0001080312,0.0008907394,0.02036919,0.002597286,0.006360441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01017908,"threshold_uncertainty_score":0.02023965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387842812472382,"score_gpt":0.2861078364238319,"score_spread":0.2522294082991081,"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."}}