{"id":"W2339737717","doi":"10.5753/sbsi.2016.5969","title":"Does Technical Debt Lead to the Rejection of Pull Requests?","year":2016,"lang":"en","type":"preprint","venue":"Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI)","topic":"Software Engineering Research","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Technical debt; Convention; Debt; Documentation; Identification (biology); Technical documentation; Computer science; Focus (optics); Business; Risk analysis (engineering); Accounting; Finance; Software; Law; Software development; Political science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01761057,0.0005151505,0.0005640822,0.003370722,0.001930141,0.003148695,0.00115792,0.001841726,0.006085195],"category_scores_gemma":[0.169361,0.0005050754,0.0006091885,0.002566911,0.001351657,0.004573543,0.002566555,0.002320147,0.001246731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664862,"about_ca_system_score_gemma":0.002207035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00305749,"about_ca_topic_score_gemma":0.002669016,"domain_scores_codex":[0.9780799,0.007683089,0.002834904,0.001802566,0.007591403,0.002008147],"domain_scores_gemma":[0.6752589,0.1916589,0.08566026,0.01471041,0.02494463,0.007767057],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005864683,0.0003403951,0.8811144,0.0005104746,0.00009712779,0.001742836,0.0208238,0.0005300745,0.005477624,0.003446425,0.002448026,0.08288234],"study_design_scores_gemma":[0.00006328386,0.0005817215,0.8983642,0.0006496708,0.0001807581,0.003951575,0.04601878,0.008769494,0.005826943,0.009916686,0.02555283,0.0001240084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776534,0.0006131572,0.005882889,0.001443704,0.00004699491,0.0001069744,0.000188552,0.0001728939,0.01389149],"genre_scores_gemma":[0.9956537,0.0002341196,0.001446757,0.0003075604,0.0000590828,0.00005134069,0.0002142728,0.00006617761,0.001966781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9823895,"threshold_uncertainty_score":0.0931347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973705733955451,"score_gpt":0.2933060361890752,"score_spread":0.2735689788495207,"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."}}