{"id":"W2796461266","doi":"10.1016/j.jss.2018.03.053","title":"Characterizing and predicting blocking bugs in open source projects","year":2018,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Software Engineering Research","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Concordia University","funders":"","keywords":"Blocking (statistics); Software bug; Computer science; Software; Open source; Code (set theory); Source lines of code; Operating system; Programming language; Computer network","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":[0.00463813,0.0006976517,0.0004528979,0.006505345,0.0007210806,0.00149542,0.001202915,0.001505011,0.0008704897],"category_scores_gemma":[0.07078826,0.0007603383,0.0006158559,0.002930777,0.000823041,0.002705868,0.001431849,0.001227709,0.0003839252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007430441,"about_ca_system_score_gemma":0.002061869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00771757,"about_ca_topic_score_gemma":0.01236126,"domain_scores_codex":[0.9942275,0.0009814366,0.0008335884,0.001101979,0.002250342,0.0006051739],"domain_scores_gemma":[0.8539932,0.08335532,0.0380932,0.006812878,0.01339729,0.004348129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002552969,0.000264368,0.9475374,0.0001373289,0.00009596367,0.0002194223,0.0004528313,0.005451977,0.004048738,0.0007676029,0.001102343,0.03966687],"study_design_scores_gemma":[0.00008355399,0.001009666,0.7460967,0.0001994939,0.0004386722,0.001688374,0.001455061,0.2270661,0.009413183,0.009078528,0.003373108,0.00009746333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929427,0.0003640307,0.00509082,0.0001052673,0.00002035978,0.00002782906,0.0003212964,0.0005446867,0.000583027],"genre_scores_gemma":[0.9914445,0.0001400699,0.007045032,0.00003059184,0.0000181774,0.00002377633,0.0008218343,0.00008447549,0.0003914423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00771757,"threshold_uncertainty_score":0.0245291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894337871990336,"score_gpt":0.2765328254276833,"score_spread":0.2475894467077799,"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."}}