{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008374355,0.0001867007,0.0001686777,0.0002522431,0.0006183653,0.002193977,0.00093284,0.00005461822,0.00002214848],"category_scores_gemma":[0.00002150813,0.0001557092,0.00003768956,0.001132109,0.0006418743,0.001086068,0.0004319979,0.0001372019,0.0001153055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003866733,"about_ca_system_score_gemma":0.0001758285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001775915,"about_ca_topic_score_gemma":0.00004465525,"domain_scores_codex":[0.9978578,0.00003335888,0.0002751453,0.0008256985,0.0004839297,0.0005240834],"domain_scores_gemma":[0.9993237,0.0001460541,0.00005601129,0.0003010741,0.00004737608,0.000125741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003392302,0.00001913971,0.0003888326,0.00005844805,0.00001833878,0.00007184388,0.006415013,0.004450132,0.1993645,0.7520456,0.0003022451,0.03686253],"study_design_scores_gemma":[0.00005483553,0.0000587408,0.0001789855,0.0001203207,0.00001132643,0.0000617585,0.0020002,0.7299814,0.2363631,0.02899165,0.001726837,0.0004508141],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7012504,0.001301161,0.2901955,0.001234796,0.0007938021,0.0002467217,0.000001537265,0.0002674906,0.004708597],"genre_scores_gemma":[0.979622,0.00003055402,0.01925028,0.0007381107,0.0001488715,0.00001558266,4.107416e-7,0.0000098639,0.0001843072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7255313,"threshold_uncertainty_score":0.9988418,"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."}}