{"id":"W2105492891","doi":"10.1145/2020976.2020979","title":"Managing technical debt in software development","year":2011,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software Engineering Research","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Technical debt; Engineering management; Software quality; Debt; Software engineering; Software development; Software; Computer science; Quality (philosophy); Software project management; Engineering; Value (mathematics); Business; Software construction; Finance","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000703495,0.0005097908,0.0004401398,0.0008687017,0.0001152827,0.0001340017,0.003279706,0.0002480895,0.00004856347],"category_scores_gemma":[0.1462448,0.0005544724,0.000114535,0.00144224,0.00004668376,0.0007162993,0.001656341,0.0007605997,0.0001880577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003497335,"about_ca_system_score_gemma":0.0001854034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006476398,"about_ca_topic_score_gemma":0.00001897383,"domain_scores_codex":[0.9965372,0.00003547589,0.0006165027,0.0009303875,0.0006849447,0.001195478],"domain_scores_gemma":[0.9597867,0.03749538,0.00008660642,0.002114475,0.0001395275,0.0003773423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001136571,0.0001553654,0.9321333,0.0002196992,0.00003986921,0.0003940074,0.001666615,0.001372144,0.0005674018,0.00100647,0.0001520996,0.06228167],"study_design_scores_gemma":[0.0004877054,0.00007575708,0.9854573,0.0003293609,0.000006261804,0.00009410366,0.000007470705,0.000458902,0.01057883,0.0002886096,0.001228405,0.0009872667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1624601,0.0006431857,0.8309865,0.0001107041,0.000600262,0.0003973421,0.000002632841,0.004788111,0.00001119026],"genre_scores_gemma":[0.5286171,0.00001226464,0.4710908,0.00004472927,0.00003806435,0.000110186,0.00000502482,0.00006135452,0.00002047973],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3661571,"threshold_uncertainty_score":0.9996907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03005410945615254,"score_gpt":0.2447899692817762,"score_spread":0.2147358598256237,"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."}}