{"id":"W2055823824","doi":"10.4108/icst.immerscom2007.2117","title":"3D Watermarking Robust to Accessible Attacks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital watermarking; Polygon mesh; Computer science; Field (mathematics); Robustness (evolution); Watermarking attack; Computer graphics (images); Image (mathematics); Artificial intelligence; Computer vision; Computer security; Cryptography; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004839897,0.0007418031,0.0007436901,0.001107548,0.0005097067,0.001041844,0.0005853483,0.001534022,0.001940278],"category_scores_gemma":[0.003778803,0.0003705166,0.0007155116,0.0006398286,0.0009756009,0.001513548,0.001753708,0.001062804,0.001041381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002364995,"about_ca_system_score_gemma":0.0001939544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002009202,"about_ca_topic_score_gemma":0.0001893363,"domain_scores_codex":[0.9987446,0.0001588144,0.00006507413,0.000151602,0.0007799745,0.00009991883],"domain_scores_gemma":[0.9981914,0.0005216917,0.0003415447,0.0006729459,0.0002195056,0.00005291251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003570076,0.00005622349,0.001026575,0.0002497641,0.0001041928,0.001355591,0.0002303086,0.1453453,0.5526238,0.03501859,0.001648013,0.2619847],"study_design_scores_gemma":[0.00003718073,0.0002319164,0.001429843,0.00007267731,0.00008199313,0.002515329,0.00009171506,0.6632047,0.2922642,0.01697009,0.02299762,0.0001026443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06161255,0.001136606,0.9272142,0.0003618928,0.0002770315,0.00005707771,0.00007259569,0.001129938,0.008138098],"genre_scores_gemma":[0.7757885,0.002090758,0.2100291,0.0002234775,0.0003076747,0.0001013898,0.0002424518,0.0002988888,0.01091767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001940278,"threshold_uncertainty_score":0.006490886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581957473162176,"score_gpt":0.290006722436568,"score_spread":0.2641871477049462,"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."}}