{"id":"W4399362212","doi":"10.1007/s10664-024-10448-6","title":"VulNet: Towards improving vulnerability management in the Maven ecosystem","year":2024,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Concordia University","funders":"Indian Institute of Technology Gandhinagar","keywords":"Vulnerability (computing); Ecosystem; Environmental resource management; Environmental science; Business; Computer science; Ecology; Computer security; 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":[0.0007284058,0.0001887472,0.0001554253,0.0001951682,0.00006205574,0.0002496915,0.0008130928,0.00007306413,0.000008255354],"category_scores_gemma":[0.0001651194,0.0001442016,0.00008724877,0.0009091447,0.000009374739,0.0004307086,0.0003057747,0.0004268379,0.00002639202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002768786,"about_ca_system_score_gemma":0.00002221087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001373672,"about_ca_topic_score_gemma":0.000005851019,"domain_scores_codex":[0.9984888,0.00006168565,0.0002906958,0.0004966492,0.0003176681,0.0003444426],"domain_scores_gemma":[0.9990456,0.0002806262,0.00002211231,0.0005738253,0.00002025947,0.00005761404],"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":[0.000006853875,0.0001088206,0.001858401,0.001454603,0.00007052168,0.0009470136,0.002200429,0.0306453,0.0002285008,0.01170086,0.001676579,0.9491021],"study_design_scores_gemma":[0.0003957449,0.0002188286,0.03931242,0.0005005558,0.00002821234,0.00032579,0.0001066204,0.6872747,0.005285345,0.009802249,0.2553804,0.001369157],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01165682,0.000304382,0.9839826,0.0005052598,0.0005401231,0.0003376138,0.000002730177,0.002517055,0.0001533804],"genre_scores_gemma":[0.8511752,0.000007190424,0.1482802,0.0001595796,0.00009901525,0.0002117084,0.000001157831,0.00002196375,0.00004401852],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.947733,"threshold_uncertainty_score":0.5880371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655092419775144,"score_gpt":0.2847365155113277,"score_spread":0.2681855913135763,"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."}}