{"id":"W2183070429","doi":"10.5072/zenodo.309676","title":"STRATEGIES FOR MONITORING FAKE AV DISTRIBUTION NETWORKS","year":2011,"lang":"no","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Leverage (statistics); Computer science; Property (philosophy); Distribution (mathematics); Computer network; Artificial intelligence; Mathematics","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":[0.0003480043,0.0001819139,0.0001482555,0.00003424197,0.0003283251,0.0005521497,0.0004580813,0.000177839,0.00004759667],"category_scores_gemma":[0.0000212134,0.0001749154,0.0001129243,0.0002688724,0.00004148124,0.001040858,0.0001002273,0.000172135,0.00003666632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006573494,"about_ca_system_score_gemma":0.00006983145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004633802,"about_ca_topic_score_gemma":0.00003271342,"domain_scores_codex":[0.9987362,0.00004358906,0.0002456286,0.0004001246,0.0001557431,0.000418735],"domain_scores_gemma":[0.9991916,0.00008554773,0.0001054833,0.0003718688,0.0001424621,0.0001030584],"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":[0.0002397325,0.0003709578,0.01098396,0.0001661378,0.0001808779,0.00001503766,0.007701151,0.003410723,0.0004856732,0.6408696,0.01496928,0.3206069],"study_design_scores_gemma":[0.001036437,0.001268439,0.05858995,0.0002039493,0.0001048252,0.00002310581,0.001984348,0.8676244,0.01016933,0.03835387,0.01956137,0.00107999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009561527,0.0003090588,0.9770522,0.00007119201,0.008153513,0.0002483022,0.000006843793,0.0002378703,0.004359541],"genre_scores_gemma":[0.9901876,0.00005154604,0.007801208,0.00002427023,0.001145277,0.00003165189,0.0000112392,0.00001151973,0.0007356586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9806261,"threshold_uncertainty_score":0.7132842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06101789576228221,"score_gpt":0.2579133890427207,"score_spread":0.1968954932804385,"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."}}