{"id":"W3188230742","doi":"10.1109/rew53955.2021.00024","title":"Issue Link Label Recovery and Prediction for Open Source Software","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Task (project management); Software; Open source; Open source software; Focus (optics); Link (geometry); Machine learning; Data science; Selection (genetic algorithm); Feature selection; Artificial intelligence; Software engineering; Data mining; Systems engineering; Engineering","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":[0.009657288,0.00148029,0.0007796127,0.01185812,0.001699533,0.002336824,0.001797769,0.00243105,0.001005918],"category_scores_gemma":[0.04696382,0.0004794857,0.0008890387,0.005296117,0.0008926028,0.004415826,0.002379109,0.003975792,0.001363172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118891,"about_ca_system_score_gemma":0.001419805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00585584,"about_ca_topic_score_gemma":0.008002286,"domain_scores_codex":[0.9931777,0.002541615,0.0004855939,0.001493414,0.001878683,0.0004230594],"domain_scores_gemma":[0.9299383,0.04462734,0.009338371,0.007235683,0.007757086,0.001103115],"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":[0.0004431087,0.001709881,0.3163039,0.0006189055,0.0002254499,0.0006300496,0.001777484,0.1192738,0.00813385,0.004006255,0.02407244,0.5228048],"study_design_scores_gemma":[0.00002132041,0.0001197796,0.02714141,0.00007567731,0.00005573053,0.0001939927,0.0004801228,0.9471084,0.01107964,0.008175218,0.005496455,0.00005223898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6703168,0.001586232,0.3082612,0.001283649,0.0002725639,0.000266421,0.003012189,0.01229518,0.002705733],"genre_scores_gemma":[0.7979588,0.0003763347,0.1866257,0.0001302072,0.0001707417,0.0002073499,0.01145652,0.0005699212,0.002504384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01185812,"threshold_uncertainty_score":0.05107325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03474133248225599,"score_gpt":0.2999174149204027,"score_spread":0.2651760824381467,"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."}}