{"id":"W1989186026","doi":"10.1109/malware.2008.4690859","title":"Image spam — 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004955371,0.00143544,0.0006626677,0.002224822,0.001205362,0.00278362,0.0009970203,0.001564729,0.3965364],"category_scores_gemma":[0.003089519,0.0004943353,0.0004084354,0.001188775,0.0006069269,0.002140899,0.001679795,0.0009728021,0.3819784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005724102,"about_ca_system_score_gemma":0.0003165446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001726982,"about_ca_topic_score_gemma":0.003426322,"domain_scores_codex":[0.9996111,0.00003466391,0.00001696614,0.0000545138,0.0002289075,0.00005397106],"domain_scores_gemma":[0.9985495,0.0001740093,0.00007114646,0.0003805217,0.0006613148,0.0001633895],"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":[0.0001322508,0.0000331953,0.0004348736,0.0001383552,0.000007669378,0.0002901126,0.00007410791,0.0001199916,0.007316668,0.001378433,0.8457113,0.144363],"study_design_scores_gemma":[0.00002824455,0.00008111381,0.002301979,0.000104861,0.000008774815,0.0008099762,0.00009122654,0.005104015,0.02373585,0.002383287,0.9653215,0.00002926587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01883576,0.002008489,0.1058739,0.01124408,0.008055884,0.0009522557,0.02053855,0.1573703,0.6751208],"genre_scores_gemma":[0.04271814,0.000924453,0.04343504,0.002015458,0.001525999,0.0002292524,0.01270517,0.01128284,0.8851636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3965364,"threshold_uncertainty_score":0.8607676,"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."}}