{"id":"W4378373692","doi":"10.1109/icst57152.2023.00018","title":"Embedding Context as Code Dependencies for Neural Program Repair","year":2023,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; ENCODE; Embedding; Source code; Code (set theory); Graph; Dependency graph; Artificial intelligence; Programming language; Theoretical computer science; Representation (politics); Natural language processing","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":[0.0004202954,0.00009454378,0.0001039542,0.0001397132,0.0001022211,0.000183319,0.0006544074,0.0000421192,0.00001450648],"category_scores_gemma":[0.001248492,0.00008372185,0.00009360717,0.0005701272,0.00002426222,0.0002783401,0.0003066152,0.00009937127,0.0002320197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003405374,"about_ca_system_score_gemma":0.00005694163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000382039,"about_ca_topic_score_gemma":0.00001915488,"domain_scores_codex":[0.9987521,0.00001678991,0.0001303192,0.0003293568,0.0003170054,0.0004544588],"domain_scores_gemma":[0.9983252,0.001037312,0.0000157873,0.0004156119,0.0001057332,0.0001003134],"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":[0.00003682653,0.0001799342,0.0181533,0.0003326568,0.000153278,0.0003104962,0.002977777,0.0171031,0.001094567,0.08195748,0.2423469,0.6353537],"study_design_scores_gemma":[0.0001919263,0.000184016,0.002500071,0.000009147691,0.000001354223,0.00001666376,0.00009166561,0.9791799,0.001019048,0.0005288416,0.0161495,0.0001278244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5395449,0.0001504902,0.4106159,0.002569427,0.001396939,0.002013412,0.000006533592,0.04266838,0.001034046],"genre_scores_gemma":[0.8836315,0.000003380538,0.1094651,0.0001329589,0.00006851604,0.0003869374,0.000003534879,0.00001970262,0.006288347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9620768,"threshold_uncertainty_score":0.3414078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04859496328150169,"score_gpt":0.3578197693393004,"score_spread":0.3092248060577987,"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."}}