{"id":"W2522081129","doi":"10.1016/j.protcy.2016.08.105","title":"Reversible Data Hiding in Videos for Better Visibility and Minimal Transfer","year":2016,"lang":"en","type":"article","venue":"Procedia Technology","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal College of Physicians and Surgeons of Canada","funders":"","keywords":"Computer science; Visibility; Quality (philosophy); Video quality; Information hiding; Computer vision; Artificial intelligence; Contrast (vision); Transmission (telecommunications); Video processing; File size; Image quality; Video tracking; Internet video; The Internet; Multimedia; Telecommunications; 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":[0.0003134233,0.0001159604,0.0001661234,0.0003446956,0.00005749087,0.00001972706,0.001109244,0.000165834,0.000001100175],"category_scores_gemma":[0.0001369179,0.00008515734,0.00002107052,0.0003867652,0.0001451068,0.0007223274,0.0004623201,0.0001009947,9.953029e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001968231,"about_ca_system_score_gemma":0.00002172051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001799916,"about_ca_topic_score_gemma":0.00001158102,"domain_scores_codex":[0.9987949,0.00001282403,0.0001962322,0.0006261988,0.0000644002,0.0003055102],"domain_scores_gemma":[0.9990409,0.0001227941,0.0000269476,0.0007443979,0.00003633733,0.00002860611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000812852,0.0001006526,0.123605,0.0001791931,0.00002090583,0.00001721937,0.000302849,8.67912e-8,0.07350978,0.06103044,0.0009492717,0.7402033],"study_design_scores_gemma":[0.001768413,0.0004340143,0.004492224,0.0002508642,0.00001377343,0.00006083273,0.00003199702,0.001710546,0.2798407,0.6860023,0.02480699,0.0005874042],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1570192,0.0001530326,0.833537,0.008269334,0.00005406123,0.0003640901,0.00002037445,0.0005472245,0.00003570236],"genre_scores_gemma":[0.77107,0.00005698075,0.2286375,0.000121417,0.00001572027,0.00008109365,0.000001595961,0.000006532664,0.000009082283],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7396159,"threshold_uncertainty_score":0.3472615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03002208305453358,"score_gpt":0.2750115338011579,"score_spread":0.2449894507466243,"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."}}