{"id":"W2533752877","doi":"10.1007/s11760-010-0164-x","title":"A combined just noticeable distortion model–guided image watermarking","year":2010,"lang":"en","type":"article","venue":"Signal Image and Video Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Watermark; Digital watermarking; Human visual system model; Just-noticeable difference; Artificial intelligence; Computer science; Distortion (music); Computer vision; Image (mathematics); Visibility; Optics; Bandwidth (computing)","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":[0.0004895267,0.0002364566,0.0002192118,0.0001679035,0.0005803803,0.000798498,0.0004914007,0.00009802454,0.00000621091],"category_scores_gemma":[0.00003106265,0.0002057807,0.00006964857,0.0002756743,0.0001831088,0.003239283,0.0002545508,0.0003770864,0.00000343926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001630486,"about_ca_system_score_gemma":0.00005457633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001259663,"about_ca_topic_score_gemma":0.000003136098,"domain_scores_codex":[0.9984779,0.00004166781,0.0003212286,0.0005069574,0.0002297637,0.0004225282],"domain_scores_gemma":[0.9991596,0.00004039224,0.0001605392,0.0003312113,0.000180361,0.0001279227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003554838,0.00008144201,0.0005613625,0.0002118535,0.00001027028,0.00005239826,0.001500763,0.00003237488,0.899496,0.001650305,0.0003609453,0.0960068],"study_design_scores_gemma":[0.0005339005,0.00007661748,0.000325296,0.0001760497,0.00003028849,0.00006225669,0.00003305583,0.5606558,0.3921851,0.04496134,0.0004032637,0.0005570424],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06517994,0.00006108219,0.9318296,0.0003120591,0.00009648122,0.0001520833,0.000001810969,0.0005339884,0.001832928],"genre_scores_gemma":[0.7263412,0.000009180278,0.2732557,0.0002081932,0.00005540676,0.00001965615,0.000004756811,0.00001600335,0.00008984953],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6611614,"threshold_uncertainty_score":0.8391493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799655984543852,"score_gpt":0.2746407809134084,"score_spread":0.2566442210679699,"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."}}