{"id":"W2144095775","doi":"10.1109/icip.1998.723403","title":"Towards a telltale watermarking technique for tamper-proofing","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital watermarking; Computer science; Computer security; Tamper resistance; Artificial intelligence","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":[0.0002917078,0.0001911968,0.0001801238,0.0002000154,0.0002453519,0.0001563514,0.0009238632,0.0001005543,0.00002648975],"category_scores_gemma":[0.00002356978,0.0001563626,0.0001546371,0.0003366578,0.00005062273,0.0006670328,0.0002511412,0.0001225216,0.000007838636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000279013,"about_ca_system_score_gemma":0.000007484272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006978846,"about_ca_topic_score_gemma":0.000001123226,"domain_scores_codex":[0.9986817,0.00002973735,0.0002466497,0.0004364091,0.0001645437,0.0004409599],"domain_scores_gemma":[0.9991652,0.00006303596,0.00006669052,0.000560849,0.00007037511,0.00007385751],"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":[0.00001948784,0.0002546498,0.0006740922,0.0001986002,0.00005592695,0.00005249436,0.002029424,0.00002597217,0.1672026,0.2037171,0.01397179,0.6117979],"study_design_scores_gemma":[0.0002623075,0.0001711962,0.00004443015,0.00007174746,0.000005617332,0.00007071568,0.000009812149,0.02097036,0.8264072,0.07831179,0.07318572,0.0004891391],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003646705,0.00009182461,0.9801894,0.000521484,0.0001482425,0.0006266131,0.000002102306,0.001208292,0.01684736],"genre_scores_gemma":[0.4209472,0.0000245012,0.577808,0.0002914971,0.0000532713,0.0003329279,0.000001355079,0.00001349329,0.0005278206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6592045,"threshold_uncertainty_score":0.6376282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02719148503878248,"score_gpt":0.2538331052531291,"score_spread":0.2266416202143466,"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."}}