{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000535542,0.00008208061,0.0001901192,0.0001578055,0.0001753207,0.0008827182,0.0001559261,0.00004661348,0.000001072298],"category_scores_gemma":[0.0000497067,0.00006338456,0.00005184423,0.0003344667,0.00002100361,0.00077067,0.00003891998,0.0001312759,4.764667e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002594435,"about_ca_system_score_gemma":0.00006010922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003429094,"about_ca_topic_score_gemma":0.000003270509,"domain_scores_codex":[0.9990766,0.00009127152,0.0003755078,0.0001300478,0.0002223308,0.000104243],"domain_scores_gemma":[0.999254,0.0001319093,0.0002284118,0.0001098626,0.000213244,0.00006253999],"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":[0.00002770211,0.00008333487,0.03685078,0.00158317,0.0004805484,0.000584116,0.01149048,0.4455489,0.001449274,0.009757149,0.01457699,0.4775675],"study_design_scores_gemma":[0.0002643904,0.00007777791,0.0002475789,0.001446607,0.00003719465,0.0008595457,0.0005566252,0.9945007,0.0001018707,0.0006058372,0.001152736,0.000149149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06466331,0.02448393,0.909381,0.0001165168,0.001243821,0.00004569732,0.000001311047,0.0000479498,0.00001651776],"genre_scores_gemma":[0.9448072,0.0002106521,0.05444455,0.0000479872,0.0003997405,9.0499e-7,0.000001125905,0.000009136711,0.00007874757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8801438,"threshold_uncertainty_score":0.8512072,"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."}}