{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005542891,0.0001480402,0.0001292313,0.0002919651,0.0001771477,0.0001963308,0.001150883,0.00006347419,0.00001850486],"category_scores_gemma":[0.00001005598,0.0001183895,0.00006013925,0.0006580419,0.00002294993,0.0008038217,0.0004927552,0.000118392,0.00003637852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002711998,"about_ca_system_score_gemma":0.00001097094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001685319,"about_ca_topic_score_gemma":0.0000183176,"domain_scores_codex":[0.998642,0.00001855673,0.0002386032,0.0003840404,0.0002161446,0.0005006653],"domain_scores_gemma":[0.9991067,0.00005259026,0.0000445938,0.0005787149,0.0000594529,0.0001579152],"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":[0.00005710417,0.0001625255,0.02781441,0.00004580424,0.00003948093,0.0002571823,0.001853371,0.0007898814,0.01463795,0.088569,0.009588799,0.8561845],"study_design_scores_gemma":[0.0005664575,0.0003260625,0.02643541,0.0001745517,0.00001016625,0.0000988343,0.00005785569,0.00933187,0.6569872,0.02366461,0.2807807,0.001566255],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008640297,0.00001713439,0.9461665,0.0003574452,0.0002496559,0.0001386577,3.090096e-7,0.001026523,0.04340348],"genre_scores_gemma":[0.477954,0.000003872121,0.5204619,0.001025453,0.00005267125,0.000006486057,7.185488e-7,0.00000724594,0.000487701],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8546183,"threshold_uncertainty_score":0.4827784,"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."}}