{"id":"W4312475219","doi":"10.1109/icsme55016.2022.00021","title":"Exploring the Notion of Risk in Code Reviewer Recommendation","year":2022,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; University of Waterloo","funders":"","keywords":"Computer science; Workload; Premise; Code review; Recommender system; Core (optical fiber); Code (set theory); Normalization (sociology); Source code; Empirical research; Set (abstract data type); Data science; Information retrieval; Risk analysis (engineering); Software","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":[0.012155,0.001211537,0.001246059,0.00306894,0.0009058205,0.002935807,0.001654006,0.001805622,0.0008465359],"category_scores_gemma":[0.0860903,0.0007621606,0.0009470233,0.002063137,0.0009892111,0.005732619,0.001577102,0.002175347,0.0004066518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312049,"about_ca_system_score_gemma":0.001450587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0058917,"about_ca_topic_score_gemma":0.007075923,"domain_scores_codex":[0.9874234,0.00538261,0.0009778193,0.002806769,0.003010833,0.0003986272],"domain_scores_gemma":[0.9026611,0.07197206,0.008738158,0.007471991,0.007901598,0.001255079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001124234,0.0006974704,0.2272394,0.0009381069,0.0009157315,0.0005705833,0.003902395,0.222647,0.0148662,0.01201564,0.005211549,0.5098715],"study_design_scores_gemma":[0.00006415003,0.0004818933,0.03436839,0.0001206646,0.0002357034,0.0006425473,0.0004446534,0.9403771,0.00537787,0.01384222,0.003881712,0.0001630186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3390143,0.004557584,0.646017,0.002435304,0.0001853672,0.0002447946,0.0004525571,0.001781292,0.00531176],"genre_scores_gemma":[0.9162028,0.0004000542,0.08184867,0.0001778929,0.0001215013,0.00006630398,0.0002655619,0.00007085579,0.0008464528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012155,"threshold_uncertainty_score":0.06428254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116844779262547,"score_gpt":0.300212604902923,"score_spread":0.1885281269766683,"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."}}