{"id":"W4402516515","doi":"10.1145/3695995","title":"Deep API Sequence Generation via Golden Solution Samples and API Seeds","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Software Engineering and Methodology","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Sequence (biology); Programming language; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006018077,0.000150073,0.0001878779,0.0002796247,0.0001440072,0.0001310579,0.0002161024,0.0001123776,0.000007216563],"category_scores_gemma":[0.0002476705,0.0001451471,0.00005072703,0.0003394577,0.00003875736,0.0003247487,0.00002161547,0.0002164492,0.000006564708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002911596,"about_ca_system_score_gemma":0.00002327742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008190503,"about_ca_topic_score_gemma":0.0000179481,"domain_scores_codex":[0.998959,0.000133576,0.0001648427,0.0004427337,0.00009375791,0.0002060999],"domain_scores_gemma":[0.9985656,0.0009253141,0.00001925914,0.0003786686,0.00002686985,0.00008431875],"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":[0.000003497795,0.00001544935,0.00004243393,0.00009399525,0.0001400669,0.0000161186,0.001112866,0.02983086,0.03185176,0.001831086,0.00004477908,0.9350171],"study_design_scores_gemma":[0.0001212209,0.0001010189,0.0003168703,0.00004861384,0.00009737802,0.0002413069,0.00002606092,0.9906324,0.004585893,0.0007573586,0.002807489,0.0002643584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008110547,0.00132521,0.9890715,0.000429275,0.0005226523,0.00004497954,0.00001095762,0.0004833619,0.000001553404],"genre_scores_gemma":[0.2072585,0.0003357485,0.7921507,0.00006135036,0.00007634948,0.00001996139,0.00001365965,0.00001217453,0.00007151783],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9608015,"threshold_uncertainty_score":0.5918928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1355813693896089,"score_gpt":0.316032012399771,"score_spread":0.1804506430101621,"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."}}