{"id":"W2046040805","doi":"10.1145/2735399.2735419","title":"Technical Debt","year":2015,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software Engineering Research","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Technical debt; Maturity (psychological); Debt; Capability Maturity Model; Software; Software engineering; Computer science; Engineering management; Engineering; Business; Software development; Political science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006916165,0.0004181066,0.0004743519,0.002625505,0.003457982,0.008069057,0.001479264,0.001687576,0.08922569],"category_scores_gemma":[0.04095152,0.0002652796,0.0004473186,0.00431098,0.001077188,0.007958448,0.005745074,0.00362904,0.01758327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003438447,"about_ca_system_score_gemma":0.003895561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002575396,"about_ca_topic_score_gemma":0.002533343,"domain_scores_codex":[0.9925061,0.001324248,0.000605905,0.0007726272,0.003510915,0.001280264],"domain_scores_gemma":[0.9689132,0.005312146,0.004725646,0.004114802,0.01140093,0.005533361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001382516,0.0002006912,0.02471697,0.0004429322,0.00004014289,0.001395558,0.005519968,0.0006040707,0.0008586424,0.2706258,0.410833,0.284624],"study_design_scores_gemma":[0.00001296404,0.00005309519,0.008036932,0.000310616,0.00001364161,0.0009215143,0.00208377,0.0002573604,0.0003043616,0.0307098,0.9572718,0.00002420703],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06071372,0.007658794,0.01786648,0.0484833,0.004723429,0.0003657834,0.004314844,0.0007252984,0.8551482],"genre_scores_gemma":[0.5185717,0.008614138,0.006249187,0.0179016,0.003148123,0.0004204576,0.009281796,0.0008519412,0.4349611],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08922569,"threshold_uncertainty_score":0.2984897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03198492910553311,"score_gpt":0.2696576586162741,"score_spread":0.2376727295107409,"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."}}