{"id":"W2002732647","doi":"10.1109/mmsp.2005.248660","title":"Steganalysis of Degraded Document Images","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Steganalysis; Steganography; Computer science; Artificial intelligence; Embedding; Pixel; Distortion (music); Noise (video); Pattern recognition (psychology); Statistic; Computer vision; Process (computing); Binary number; Image (mathematics); Mathematics; Bandwidth (computing); Statistics; Telecommunications; Arithmetic","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":[0.0001336745,0.00007739176,0.000124466,0.0001478963,0.00003735549,0.0000339684,0.0005467336,0.00002410632,0.00001969586],"category_scores_gemma":[0.000004564701,0.00005871128,0.00009982699,0.0003522678,0.00003422719,0.0005058859,0.0001196015,0.00004436363,0.000005096139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001136817,"about_ca_system_score_gemma":0.000007694132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270018,"about_ca_topic_score_gemma":0.000004101239,"domain_scores_codex":[0.99932,0.00002581452,0.0001868457,0.0001739606,0.0001565946,0.0001368404],"domain_scores_gemma":[0.9994066,0.00002761738,0.00006645419,0.0004201843,0.00004350551,0.00003557554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008551036,0.0001502184,0.003227043,0.00002074581,0.000108454,0.00000672721,0.0005435189,0.0001449778,0.01222536,0.3154922,0.002772114,0.6653001],"study_design_scores_gemma":[0.0001500667,0.00005611807,0.001174925,0.00001189641,0.00001206211,0.000004495114,0.00001321452,0.001892172,0.9541264,0.03378143,0.008612707,0.0001645001],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004425092,0.000171713,0.985831,0.0008631205,0.00002053245,0.00005194123,4.514949e-7,0.0002880346,0.008348165],"genre_scores_gemma":[0.6026424,0.00002414827,0.3969012,0.00008787797,0.000009852442,0.000003790113,3.229163e-7,0.00000177439,0.0003286596],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.941901,"threshold_uncertainty_score":0.2394177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009348192072816432,"score_gpt":0.2519655190449504,"score_spread":0.242617326972134,"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."}}