{"id":"W4403335660","doi":"10.3390/app14209231","title":"Helping CNAs Generate CVSS Scores Faster and More Confidently Using XAI","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science","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":[0.003290347,0.001944541,0.0007464901,0.002667842,0.0005192762,0.002159316,0.001755037,0.001201439,0.01490031],"category_scores_gemma":[0.02720579,0.0003618117,0.001039107,0.001737696,0.0004676415,0.002754097,0.001629611,0.002326819,0.006206761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001951972,"about_ca_system_score_gemma":0.001476032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01282689,"about_ca_topic_score_gemma":0.01938545,"domain_scores_codex":[0.9979449,0.0004885585,0.0001242358,0.0006075476,0.0006647736,0.0001699751],"domain_scores_gemma":[0.9916112,0.002890779,0.0005968465,0.002512662,0.002012644,0.0003759143],"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":[0.0007511972,0.0006644689,0.05539382,0.0006293631,0.0002552314,0.0002422703,0.000684385,0.06049072,0.005274548,0.00952915,0.1590906,0.7069942],"study_design_scores_gemma":[0.0001788519,0.0002699005,0.01382494,0.0001019979,0.00005708534,0.0001287183,0.0002925663,0.9066516,0.01096855,0.01929526,0.04815186,0.000078597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.25815,0.00108391,0.3985555,0.003876006,0.001270267,0.00243896,0.03710883,0.2520523,0.04546424],"genre_scores_gemma":[0.5781801,0.0002336411,0.360305,0.0006207007,0.000124574,0.0008314742,0.04379183,0.004161594,0.01175121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01490031,"threshold_uncertainty_score":0.04984653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06350634013231286,"score_gpt":0.3158230643018585,"score_spread":0.2523167241695456,"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."}}