{"id":"W4392191198","doi":"10.1002/9781119865667.ch17","title":"The Peculiar Case of Danger Modeling","year":2024,"lang":"en","type":"other","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","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":[0.003462091,0.001085083,0.0006315904,0.001368055,0.003404697,0.009026689,0.002307047,0.003866571,0.012728],"category_scores_gemma":[0.008074009,0.0006775626,0.002001796,0.001503327,0.01360037,0.01554806,0.007572459,0.004812392,0.003090351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002958156,"about_ca_system_score_gemma":0.002606291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004058763,"about_ca_topic_score_gemma":0.002915559,"domain_scores_codex":[0.996442,0.001553706,0.0002096575,0.0007165154,0.0008025817,0.0002754914],"domain_scores_gemma":[0.9967822,0.001329763,0.0002269567,0.001106434,0.0003424519,0.0002121511],"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":[0.000005783849,0.000003523452,0.00009369961,0.00002174402,0.000003511824,0.00005459476,0.0007896156,0.001087839,0.0001138478,0.9928323,0.001179889,0.003813597],"study_design_scores_gemma":[0.0000071709,0.00001128595,0.00006933264,0.00006209517,0.00001223465,0.0002533866,0.0005375358,0.01062399,0.0004078634,0.864554,0.1234394,0.00002163045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01086535,0.0013859,0.7101269,0.0158831,0.0005663328,0.000103812,0.0003356489,0.001134467,0.2595986],"genre_scores_gemma":[0.6165439,0.00241121,0.3096084,0.002556101,0.0005407286,0.000376112,0.0008430478,0.0009173182,0.06620312],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012728,"threshold_uncertainty_score":0.04257941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578464723896452,"score_gpt":0.2752511871725928,"score_spread":0.2594665399336283,"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."}}