{"id":"W4376505229","doi":"10.1145/3597208","title":"An Empirical Study on GitHub Pull Requests’ Reactions","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Software Engineering and Methodology","topic":"Software Engineering Research","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; École de Technologie Supérieure","funders":"","keywords":"Computer science; Leverage (statistics); Source code; Set (abstract data type); Code review; Open source; Software; Empirical research; Code (set theory); Process (computing); Static program analysis; Software engineering; World Wide Web; Software development; Programming language; Artificial intelligence","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","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0237997,0.0007550073,0.0004951917,0.00381202,0.001500896,0.003521209,0.001188334,0.001712112,0.003011408],"category_scores_gemma":[0.1561728,0.0005733185,0.0004408941,0.002774784,0.00195586,0.003849947,0.002793472,0.0026893,0.001648409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002023267,"about_ca_system_score_gemma":0.001714405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955069,"about_ca_topic_score_gemma":0.002114036,"domain_scores_codex":[0.9676914,0.01803931,0.002211269,0.002386797,0.008037245,0.001634007],"domain_scores_gemma":[0.6519539,0.2472757,0.04651977,0.008552548,0.03959687,0.00610109],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008576161,0.001673997,0.5186204,0.002349668,0.0001092494,0.001955369,0.3588237,0.000538898,0.01121086,0.001994949,0.007592035,0.09427319],"study_design_scores_gemma":[0.00007704987,0.001434688,0.649215,0.001114759,0.00008664751,0.001204272,0.2966111,0.005372718,0.006959179,0.001175517,0.03650868,0.0002404212],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912498,0.0002052809,0.002869474,0.0006376542,0.00003363204,0.0002995548,0.0002997645,0.000120596,0.004284282],"genre_scores_gemma":[0.9920844,0.0003280859,0.00338754,0.0006443077,0.00005461203,0.000678525,0.0004967323,0.0001231231,0.002202734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.996188,"threshold_uncertainty_score":0.1258664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1680616754714322,"score_gpt":0.4087685822272296,"score_spread":0.2407069067557973,"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."}}