{"id":"W4408903106","doi":"10.1145/3676641.3711998","title":"<i>Velosiraptor</i> : Code Synthesis for Memory Translation","year":2025,"lang":"en","type":"article","venue":"","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Programming language; Translation (biology); Parallel computing","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":[0.0005325505,0.0009970645,0.0003476199,0.0009940256,0.0007434528,0.00142141,0.001278697,0.0007945263,0.02501504],"category_scores_gemma":[0.003296113,0.0004045002,0.0006489816,0.0007164143,0.0007094409,0.001341648,0.001387469,0.001119311,0.008884836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007188884,"about_ca_system_score_gemma":0.001476866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059901,"about_ca_topic_score_gemma":0.002772219,"domain_scores_codex":[0.999404,0.00009722203,0.00004029201,0.0001126866,0.0002467168,0.00009909835],"domain_scores_gemma":[0.9989187,0.000294801,0.00007882751,0.0002794084,0.0003854681,0.00004284944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000462249,0.0002707044,0.002722677,0.0009130551,0.0001069476,0.0009409009,0.0006740933,0.04914211,0.09669866,0.138712,0.1480681,0.5612885],"study_design_scores_gemma":[0.0001534292,0.0002476514,0.0007886844,0.0003395948,0.00008627366,0.0005933283,0.0002376258,0.3601144,0.320731,0.04576503,0.2708352,0.0001076808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0204969,0.0004616891,0.8801394,0.0009887489,0.0009722608,0.0003031556,0.001279008,0.04505791,0.050301],"genre_scores_gemma":[0.1981381,0.0004637773,0.7519695,0.000836432,0.0001466742,0.0005323897,0.002754983,0.01698185,0.0281764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02501504,"threshold_uncertainty_score":0.08368373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03925621224727617,"score_gpt":0.2908344221348566,"score_spread":0.2515782098875805,"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."}}