{"id":"W3022352710","doi":"","title":"Predicting bug report fields using stack traces and categorical attributes.","year":2019,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Software Engineering Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Categorical variable; Stack (abstract data type); Computer science; Artificial intelligence; Natural language processing; Programming language; Machine learning","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":[0.00233217,0.0008740287,0.0005524544,0.01055677,0.0003825054,0.001288147,0.0008364075,0.001114549,0.001476221],"category_scores_gemma":[0.02204668,0.0003290774,0.000790332,0.005503709,0.0002801757,0.001886489,0.0009598759,0.0009594328,0.001252714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004864798,"about_ca_system_score_gemma":0.001126532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007959174,"about_ca_topic_score_gemma":0.01510984,"domain_scores_codex":[0.9981281,0.00035128,0.0002205995,0.0003479844,0.0007744662,0.0001775389],"domain_scores_gemma":[0.9733564,0.01239239,0.005727342,0.002227771,0.004855935,0.001440128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007858345,0.0006010802,0.7865041,0.0003952696,0.0002232117,0.000345943,0.000252322,0.01020271,0.006519268,0.0008500273,0.01501124,0.178309],"study_design_scores_gemma":[0.0001289769,0.001406668,0.6292436,0.0002546354,0.0003699115,0.00103343,0.0009059702,0.3376627,0.01144784,0.005345551,0.01206877,0.000131789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418685,0.001799658,0.02286163,0.0006493049,0.0001700279,0.0001370742,0.02336136,0.007392655,0.001759807],"genre_scores_gemma":[0.9505082,0.0004100485,0.02557007,0.00004453115,0.00007099816,0.00006019935,0.02208713,0.0001566422,0.001092109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055677,"threshold_uncertainty_score":0.01582575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1232029168967586,"score_gpt":0.4018137944970319,"score_spread":0.2786108776002734,"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."}}