{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001054646,0.0002583535,0.0001764071,0.0003401549,0.0002263938,0.0003728383,0.0003357859,0.0003320805,0.004495299],"category_scores_gemma":[0.0004048155,0.000127722,0.0003046287,0.0003187091,0.0004442893,0.0007225833,0.0003962407,0.0005251427,0.0008485621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002373346,"about_ca_system_score_gemma":0.0003108105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004117625,"about_ca_topic_score_gemma":0.0008670291,"domain_scores_codex":[0.9998782,0.00001095979,0.000004501972,0.00001980462,0.00006925609,0.00001724476],"domain_scores_gemma":[0.9998434,0.00004351485,0.00003300162,0.00003854996,0.00003290517,0.000008674581],"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":[0.0001122248,0.00006620916,0.0002518819,0.0005186718,0.00002008265,0.0003673541,0.000142058,0.006666865,0.7433243,0.03187926,0.001989669,0.2146614],"study_design_scores_gemma":[0.00003758798,0.0004655351,0.001667172,0.0001013685,0.00005604364,0.002291162,0.0001312156,0.09782984,0.820507,0.016483,0.06037097,0.00005911502],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1798218,0.01107567,0.7706642,0.001350146,0.000519723,0.0001912178,0.0002649798,0.001590801,0.03452155],"genre_scores_gemma":[0.8121014,0.005460131,0.1560947,0.0002699759,0.0001915965,0.00007675289,0.0002067009,0.000133959,0.02546473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004495299,"threshold_uncertainty_score":0.01503825,"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."}}