{"id":"W2101103348","doi":"10.1109/cgiv.2009.49","title":"A Locatable Zero Watermarking Scheme and Visualization for 3D Mesh Models","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Digital watermarking; Computer science; T-vertices; Octree; Watermark; Algorithm; Visualization; Singular value decomposition; Polygon mesh; Mesh generation; Theoretical computer science; Embedding; Artificial intelligence; Computer graphics (images); Image (mathematics)","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":[0.000181351,0.0001136083,0.0001169387,0.0001101704,0.0001600518,0.0001472265,0.0002763449,0.00005160413,7.238864e-7],"category_scores_gemma":[0.000005632835,0.00009518659,0.0000335838,0.0001887109,0.00001990806,0.001206121,0.00007742,0.00003870652,3.899007e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001021557,"about_ca_system_score_gemma":0.000009167677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003557056,"about_ca_topic_score_gemma":4.304089e-7,"domain_scores_codex":[0.9992051,0.00001499276,0.0001503708,0.000293966,0.0001002011,0.0002354239],"domain_scores_gemma":[0.9995599,0.00002453494,0.0000438918,0.0002591837,0.00006309278,0.00004937244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001539757,0.00005081373,0.00005624091,0.00002096324,0.000006846104,0.00000244464,0.0003449451,0.0001321092,0.004668455,0.9320571,0.0006133483,0.06203133],"study_design_scores_gemma":[0.0001978252,0.0001198617,0.00002768282,0.00002629638,0.000002435717,0.000009308451,0.00000272149,0.6360438,0.0407474,0.3203123,0.002348536,0.0001617953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001236626,0.0001154561,0.9960609,0.0001894293,0.0000375458,0.0002273259,6.974383e-7,0.0005459997,0.001586038],"genre_scores_gemma":[0.5164423,0.00002446569,0.482976,0.0004198013,0.00001151949,0.00001454297,0.000003332396,0.000004056522,0.0001039291],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6359117,"threshold_uncertainty_score":0.3881597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02136133383053756,"score_gpt":0.2735929194616782,"score_spread":0.2522315856311406,"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."}}