{"id":"W2137394636","doi":"10.1109/tmm.2005.843357","title":"Comments on \"An SVD-based watermarking scheme for protecting rightful Ownership\"","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":189,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Watermark; Digital watermarking; Singular value decomposition; Computer science; Image (mathematics); Artificial intelligence; Scheme (mathematics); Detector; Singular value; Value (mathematics); Algorithm; Pattern recognition (psychology); Computer vision; Mathematics; Machine learning; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004289016,0.0002901927,0.0002096522,0.0003592273,0.0006808134,0.0001245568,0.0006991783,0.0001421881,0.00001170314],"category_scores_gemma":[0.000008902058,0.0002457748,0.000189376,0.0002719158,0.0000636542,0.0006835609,0.000002866736,0.0004772689,0.0000210513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001031627,"about_ca_system_score_gemma":0.00002957003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001236644,"about_ca_topic_score_gemma":0.00002147076,"domain_scores_codex":[0.998192,0.0001333784,0.0003146052,0.0005675498,0.0002976682,0.0004948463],"domain_scores_gemma":[0.9986767,0.0003076559,0.0001156062,0.0006616333,0.00007768645,0.00016068],"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":[0.0003542005,0.001260061,0.00004231639,0.00006439783,0.00006988737,0.00001236157,0.001999369,0.01625515,0.02294931,0.0001819469,0.0001328808,0.9566781],"study_design_scores_gemma":[0.001012321,0.0003944387,0.00002520246,0.0001048227,0.000009907114,0.00000379231,0.00001266034,0.4060546,0.5872041,0.0003322093,0.004520025,0.0003259305],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01306671,0.000004590907,0.9835987,0.0009291995,0.0004498965,0.0008631786,0.00001890178,0.000952174,0.0001166587],"genre_scores_gemma":[0.615446,0.000001558297,0.3834788,0.000591072,0.00008038204,0.0003264151,0.000004834403,0.00002180209,0.00004917103],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9563522,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136254584442519,"score_gpt":0.2897016967318364,"score_spread":0.2583391508874112,"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."}}