{"id":"W2031271477","doi":"10.1145/2507288.2507326","title":"Technical debt","year":2013,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software Engineering Research","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Technical debt; Pace; Debt; Confusion; Perspective (graphical); Risk analysis (engineering); Software; Computer science; Engineering; Business; Software development; 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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002859093,0.000374209,0.0003129044,0.0003490218,0.0001034276,0.0003581875,0.003051232,0.0002097814,0.0001279086],"category_scores_gemma":[0.3062171,0.0003723663,0.0001383505,0.0009513783,0.0000431146,0.0009282221,0.001223169,0.0005645534,0.001141586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001345141,"about_ca_system_score_gemma":0.00007455811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007039856,"about_ca_topic_score_gemma":0.000001153789,"domain_scores_codex":[0.9974359,0.00002312929,0.000353749,0.0006667862,0.0006144666,0.0009059293],"domain_scores_gemma":[0.8579109,0.1376922,0.00007606595,0.003404784,0.0003211396,0.0005948746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004089372,0.0001907719,0.8561776,0.0002814789,0.00007796416,0.0001298285,0.0003353483,0.004259108,0.03260894,0.007309744,0.01240382,0.08622131],"study_design_scores_gemma":[0.0004119832,0.0001342769,0.9791517,0.0001241117,0.000008733336,0.0001519067,0.000002575841,0.002996677,0.01135192,0.0003743302,0.004257462,0.001034356],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1553348,0.0005964263,0.8339949,0.001011433,0.0007808891,0.000528904,0.000004000945,0.007739235,0.000009393843],"genre_scores_gemma":[0.6562307,0.000008984113,0.343266,0.00009550983,0.0001147552,0.0001703183,0.000004543827,0.00005366756,0.00005548044],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5008959,"threshold_uncertainty_score":0.9998728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426900710345097,"score_gpt":0.2410429534031644,"score_spread":0.2267739462997134,"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."}}