{"id":"W179515692","doi":"10.1007/978-3-540-79567-4_31","title":"Data Hiding and Digital Watermarking","year":2012,"lang":"en","type":"book-chapter","venue":"Handbook of Visual Display Technology","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Digital watermarking; Discrete cosine transform; Computer science; Information hiding; Embedding; Steganography; Covert; SIGNAL (programming language); Information security; Theoretical computer science; Image (mathematics); Artificial intelligence; Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.0002305036,0.001323879,0.001372236,0.001851693,0.0007212284,0.002476858,0.001512276,0.001425867,0.04049145],"category_scores_gemma":[0.00055,0.0005495737,0.0003709212,0.002753282,0.001158863,0.00293977,0.00108125,0.002212484,0.03325672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006396524,"about_ca_system_score_gemma":0.0009314655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009634523,"about_ca_topic_score_gemma":0.002170974,"domain_scores_codex":[0.9996942,0.00002441571,0.00001387794,0.00005845863,0.0001846875,0.00002438615],"domain_scores_gemma":[0.9998331,0.00005573651,0.000009257111,0.00002618668,0.00006090827,0.00001475865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003869821,0.0001014869,0.0001257976,0.001082063,0.00001936756,0.0001591435,0.000447455,0.001257039,0.006670125,0.1406051,0.2073451,0.6421487],"study_design_scores_gemma":[0.000004066643,0.0000300641,0.0001981701,0.0002304876,0.000005755624,0.0003504578,0.00005547625,0.0004496188,0.0008586859,0.02706285,0.9707406,0.0000139667],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001375347,0.2915658,0.06985124,0.001473417,0.004139894,0.0001689819,0.0005525692,0.001182244,0.6296905],"genre_scores_gemma":[0.01061223,0.1382514,0.03704334,0.001111335,0.001441944,0.0001675401,0.0006617443,0.0003200005,0.8103904],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04049145,"threshold_uncertainty_score":0.1354575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836922431247405,"score_gpt":0.2854593577096807,"score_spread":0.2570901333972067,"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."}}