{"id":"W3113990471","doi":"10.3390/info12010002","title":"The Spatial Analysis of the Malicious Uniform Resource Locators (URLs): 2016 Dataset Case Study","year":2020,"lang":"en","type":"article","venue":"Information","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Malware; Computer science; The Internet; Cluster (spacecraft); Phishing; Resource (disambiguation); Computer security; Population; World Wide Web; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003339329,0.00009032181,0.0001908956,0.00008010546,0.0001442311,0.00003370802,0.0002141387,0.00002742954,0.00003907604],"category_scores_gemma":[0.0002752311,0.00004921844,0.00008177859,0.000797539,0.00006840836,0.0002803724,0.0001383928,0.000104524,0.00006207603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003831812,"about_ca_system_score_gemma":0.00008673605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001386727,"about_ca_topic_score_gemma":0.0008293457,"domain_scores_codex":[0.9989043,0.00007160939,0.0004435656,0.00008127455,0.0003796355,0.0001195666],"domain_scores_gemma":[0.9988003,0.00007538458,0.0002730454,0.0006647918,0.0000952433,0.0000912042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001925119,0.000522274,0.3798814,0.0003637912,0.005417657,0.0004206514,0.03279751,0.008411614,0.00004514374,0.0001851594,0.4179052,0.1521245],"study_design_scores_gemma":[0.003043084,0.0004859169,0.2782946,0.00003698517,0.003403664,0.0001401343,0.02591756,0.07856116,0.0001778692,0.000004250859,0.6096579,0.0002769341],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897422,0.00003074278,0.0006424416,0.001625303,0.00007314294,0.0008921839,0.006103049,0.00005300434,0.0008379754],"genre_scores_gemma":[0.9953784,0.000004542572,0.00001125823,0.001169338,0.00003728101,0.00001127142,0.00337099,0.000004396569,0.00001255219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1917527,"threshold_uncertainty_score":0.2096325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324729539169537,"score_gpt":0.2677901795738267,"score_spread":0.2545428841821313,"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."}}