{"id":"W1989186026","doi":"10.1109/malware.2008.4690859","title":"Image spam &amp;#x2014; ASCII to the rescue!","year":2008,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"ASCII; Computer science; Artificial intelligence; Image (mathematics); Computer vision; Software; Computer security; Operating system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002663481,0.00008537668,0.00007794168,0.00005430584,0.0002431476,0.0001048709,0.001111218,0.00003087361,0.0001003245],"category_scores_gemma":[0.00007462084,0.00005040597,0.00005322063,0.0004846318,0.00006108714,0.0002786098,0.0002504355,0.00009163228,0.001980043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000022374,"about_ca_system_score_gemma":0.0000462701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005746082,"about_ca_topic_score_gemma":0.0000134095,"domain_scores_codex":[0.9990944,0.000044346,0.0001425956,0.0002537285,0.0002702855,0.0001946886],"domain_scores_gemma":[0.9988893,0.00004168868,0.00002426915,0.0008468475,0.0001164994,0.00008143235],"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":[0.00001394987,0.0001764549,0.0004178805,0.00001033567,0.00001825842,0.00001650546,0.002166328,0.000001994138,0.08816778,0.1558387,0.6331338,0.120038],"study_design_scores_gemma":[0.00006771382,0.00004583672,0.004208222,0.000005135893,0.000001544287,0.00005804007,0.00001335885,0.00102427,0.06730834,0.001173576,0.9259164,0.000177592],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009868328,0.00004067948,0.9559152,0.01835942,0.0001079203,0.0001630806,7.739873e-7,0.0004971122,0.02392896],"genre_scores_gemma":[0.1352924,0.0001301152,0.8165169,0.006110671,0.0001813108,0.00005336256,0.000001971467,0.0000137652,0.04169949],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2927825,"threshold_uncertainty_score":0.9987971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03805835588664958,"score_gpt":0.2773107251829836,"score_spread":0.239252369296334,"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."}}