{"id":"W4416513631","doi":"10.1109/tifs.2025.3636020","title":"MantleMark: Migrating Watermarks From Multi-View Images to Radiance Fields via Frequency Modulation","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Information Forensics and Security","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Basic and Applied Basic Research Foundation of Guangdong Province","keywords":"Digital watermarking; Radiance; Watermark; Representation (politics); Iterative reconstruction; Key (lock); Modulation (music); Gaussian","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":[0.0003141841,0.0005044453,0.0003192249,0.0005094898,0.0002343073,0.0006647948,0.0006015595,0.0006493612,0.001304562],"category_scores_gemma":[0.001245742,0.0002131355,0.0003789719,0.0004007916,0.0007522581,0.001579213,0.001287243,0.0007171858,0.000629815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002045519,"about_ca_system_score_gemma":0.0002785691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004022422,"about_ca_topic_score_gemma":0.0005394976,"domain_scores_codex":[0.9997857,0.00002712705,0.000009493791,0.00004342752,0.000109159,0.00002503278],"domain_scores_gemma":[0.9995503,0.00007479169,0.00008429483,0.0002053699,0.00005536827,0.00002985408],"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":[0.0003099937,0.00008189425,0.0007096413,0.0001396866,0.0000334053,0.0003590288,0.0002580417,0.03371752,0.4710328,0.039912,0.002688985,0.4507569],"study_design_scores_gemma":[0.00006437174,0.0004413701,0.001153593,0.00006060686,0.00004917089,0.001580599,0.0001578157,0.5042517,0.4348592,0.02594353,0.03133871,0.000099314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03471221,0.0002969981,0.9619306,0.0001640097,0.00006899026,0.00004080067,0.00004322054,0.0009690945,0.001774062],"genre_scores_gemma":[0.4486075,0.0008115182,0.5433972,0.0002217129,0.00009813599,0.00007746762,0.0001979154,0.0002115454,0.006377006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001304562,"threshold_uncertainty_score":0.004364192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009249974885947842,"score_gpt":0.2437747784267723,"score_spread":0.2345248035408245,"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."}}