{"id":"W4382203557","doi":"10.1109/tse.2023.3289808","title":"Self-Admitted Technical Debt in Ethereum Smart Contracts: A Large-Scale Exploratory Study","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Technical debt; Computer science; Workaround; Context (archaeology); Code (set theory); Implementation; Data science; Software engineering; Software development; Programming language; Software","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":[0.013577,0.000291534,0.0003829021,0.003940326,0.001612993,0.002202905,0.001104641,0.001118001,0.00191367],"category_scores_gemma":[0.06309479,0.0004168069,0.0003790516,0.004521567,0.002413594,0.00478376,0.002953448,0.001814272,0.0005646621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001878527,"about_ca_system_score_gemma":0.00225109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003903917,"about_ca_topic_score_gemma":0.005776921,"domain_scores_codex":[0.9886846,0.00575933,0.0007454485,0.0008313319,0.003170978,0.0008082095],"domain_scores_gemma":[0.8547771,0.1081161,0.0211558,0.006113904,0.00784668,0.001990322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000374355,0.001498446,0.72252,0.001211755,0.0001106633,0.004418137,0.1598577,0.002111031,0.004312989,0.01367691,0.006131999,0.08377606],"study_design_scores_gemma":[0.00005917586,0.0005178616,0.6908379,0.001197531,0.00007134222,0.002228824,0.2327184,0.01807417,0.00335782,0.005932309,0.04485564,0.0001491144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951236,0.0001890499,0.002090955,0.0002596253,0.00000422023,0.0001091438,0.0003723318,0.00002010788,0.001830851],"genre_scores_gemma":[0.9944218,0.0002262228,0.003084624,0.0001513541,0.000009770882,0.0002038775,0.0007831472,0.00003572268,0.001083628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.013577,"threshold_uncertainty_score":0.07180291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009701457661906625,"score_gpt":0.2289408710523694,"score_spread":0.2192394133904628,"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."}}