{"id":"W2807786268","doi":"10.24963/ijcai.2018/399","title":"Cutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC Optimization","year":2018,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Novelis (Canada)","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Outcome (game theory); Software; Event (particle physics); Code (set theory); Resource (disambiguation); Software engineering; Data science; Machine learning; Artificial intelligence; Set (abstract data type)","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":[0.004280068,0.002498175,0.00277469,0.001770835,0.0009133727,0.001640146,0.004064204,0.002648007,0.001749368],"category_scores_gemma":[0.01486543,0.001103971,0.001272566,0.001582158,0.001645366,0.003057728,0.002132864,0.003932487,0.001109735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00127846,"about_ca_system_score_gemma":0.002288633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007641851,"about_ca_topic_score_gemma":0.008041951,"domain_scores_codex":[0.9969316,0.0009973084,0.0002204107,0.0009884631,0.0005507623,0.0003114845],"domain_scores_gemma":[0.9855154,0.008777571,0.001294369,0.001322235,0.002354511,0.0007360157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000577574,0.0007223394,0.008013638,0.0003485461,0.000187398,0.0002202578,0.0002232149,0.6832829,0.00376077,0.002251607,0.01110382,0.289308],"study_design_scores_gemma":[0.00001115153,0.00004774276,0.0003421064,0.00000788497,0.000009362928,0.00002133407,0.000009994845,0.9975227,0.0005839359,0.001182293,0.0002541643,0.000007442343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08946797,0.001523291,0.8976964,0.000874787,0.0001207387,0.0002217463,0.0004279444,0.00753588,0.002131296],"genre_scores_gemma":[0.7871158,0.0003683057,0.2031048,0.000821767,0.0002897259,0.0005013961,0.002970239,0.0007334062,0.004094644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007641851,"threshold_uncertainty_score":0.0226354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235004194634493,"score_gpt":0.2650541921919011,"score_spread":0.2527041502455562,"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."}}