{"id":"W4411271062","doi":"10.1109/msr66628.2025.00066","title":"Characterizing Packages for Vulnerability Prediction","year":2025,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Vulnerability (computing); Computer science; Vulnerability assessment; Computer security","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":[0.001167891,0.001335145,0.0006139471,0.005070218,0.0005953707,0.00104705,0.000911033,0.00128499,0.001421246],"category_scores_gemma":[0.009292845,0.0003745406,0.001296921,0.002830062,0.0005446409,0.002609975,0.001395247,0.00139319,0.001942765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007127068,"about_ca_system_score_gemma":0.0008253853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005865778,"about_ca_topic_score_gemma":0.008369614,"domain_scores_codex":[0.9987441,0.0001652187,0.000102711,0.0003513485,0.0004503035,0.0001861918],"domain_scores_gemma":[0.9937856,0.002196054,0.001403627,0.001059016,0.001212621,0.0003431005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006079875,0.0004920372,0.5968572,0.0006846773,0.0002231029,0.001597854,0.00101753,0.03167943,0.01549929,0.004484506,0.07743035,0.269426],"study_design_scores_gemma":[0.0000578142,0.0005784875,0.3810042,0.0002854119,0.0003301395,0.00454751,0.001169931,0.4625145,0.02270537,0.01934214,0.1072905,0.0001739559],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8208495,0.003112026,0.1103601,0.001167002,0.0002335563,0.0003896547,0.04225998,0.01251929,0.009108863],"genre_scores_gemma":[0.8619935,0.0008235484,0.06732871,0.000244716,0.0001139965,0.0003476105,0.06400736,0.0009853506,0.004155226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005865778,"threshold_uncertainty_score":0.01166326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02003681168579495,"score_gpt":0.2963769135390605,"score_spread":0.2763401018532656,"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."}}