{"id":"W2100589960","doi":"10.1145/2499926.2499927","title":"SafeVchat","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Internet Technology","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Key (lock); Offensive; Computer security; Artificial intelligence; Human–computer interaction; Multimedia; Computer vision; World Wide Web; Operations research","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":[0.001298007,0.001608427,0.0009481193,0.002385636,0.0008213146,0.001983108,0.002990026,0.001658196,0.07129016],"category_scores_gemma":[0.005155549,0.0008242519,0.0007728294,0.001008663,0.0006824099,0.003376483,0.003452367,0.001246823,0.06181211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008369057,"about_ca_system_score_gemma":0.001252352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004596472,"about_ca_topic_score_gemma":0.006396932,"domain_scores_codex":[0.998368,0.0001707502,0.00007863634,0.0003499315,0.0008594833,0.0001732146],"domain_scores_gemma":[0.9969174,0.0006636892,0.0002543999,0.001137034,0.0007628042,0.0002646463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001693117,0.0003411536,0.008122311,0.0008651598,0.0001542531,0.0005867025,0.0006088338,0.003954338,0.01469648,0.008973293,0.5334462,0.4265582],"study_design_scores_gemma":[0.0002304626,0.0005409736,0.01117935,0.0002158243,0.00007247361,0.002289496,0.0003288169,0.07539184,0.05151877,0.009477399,0.8485301,0.0002244833],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.02983279,0.002084509,0.2027059,0.000766941,0.0008549613,0.00119102,0.02971316,0.6066306,0.1262202],"genre_scores_gemma":[0.3451917,0.001606816,0.2157175,0.001969788,0.0004183291,0.0009714559,0.1228403,0.04350746,0.2677767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07129016,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076984239509548,"score_gpt":0.2365056752800874,"score_spread":0.2257358328849919,"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."}}