{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000638721,0.0003541495,0.0003178453,0.0003500906,0.0000678159,0.0002245429,0.002975112,0.0002043098,0.00001250872],"category_scores_gemma":[0.477951,0.0003617119,0.0001160614,0.00106262,0.00004170645,0.0006302774,0.00132232,0.000535279,0.0003429717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002230458,"about_ca_system_score_gemma":0.0001905016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002716929,"about_ca_topic_score_gemma":0.000001675625,"domain_scores_codex":[0.9973784,0.00002885098,0.0003306063,0.0006413737,0.0008109884,0.000809758],"domain_scores_gemma":[0.9126027,0.08350126,0.00006230542,0.002728155,0.0003183538,0.0007872244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001984434,0.0002216033,0.9140959,0.0001967729,0.00007536108,0.0004457748,0.0008032137,0.01526118,0.005438877,0.01077853,0.01426506,0.03839782],"study_design_scores_gemma":[0.003082305,0.0009106031,0.888207,0.0004546597,0.0000472176,0.001073165,0.00002068616,0.01021964,0.03242294,0.001474588,0.0579471,0.004140058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06800541,0.0009370653,0.9216221,0.0006670107,0.001145251,0.0002721621,0.000005728783,0.007333424,0.00001183509],"genre_scores_gemma":[0.6427039,0.000005515906,0.3569143,0.00007021578,0.000152359,0.00005302621,0.0000056402,0.00005182334,0.0000432111],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5746985,"threshold_uncertainty_score":0.9998835,"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."}}