{"id":"W4386742716","doi":"10.1007/s10207-023-00744-5","title":"Pepal: Penalizing multimedia breaches and partial leakages","year":2023,"lang":"en","type":"article","venue":"International Journal of Information Security","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"National Science Foundation","keywords":"Computer science; Communication source; Computer security; Oblivious transfer; Cryptocurrency; Cryptography; Protocol (science); Computer network; Public-key cryptography; Key (lock); Adversarial system; Encryption","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":[0.004775864,0.0009310916,0.0007966153,0.001248019,0.0008438753,0.001793517,0.001622857,0.002019505,0.009336791],"category_scores_gemma":[0.02720241,0.000307115,0.0004149962,0.0006072604,0.001401942,0.002691793,0.003523526,0.001869012,0.001685664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006677006,"about_ca_system_score_gemma":0.001521102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006151511,"about_ca_topic_score_gemma":0.0009718644,"domain_scores_codex":[0.9962398,0.001137968,0.0001788183,0.0004199987,0.001433751,0.0005896445],"domain_scores_gemma":[0.9877456,0.005234959,0.0009269762,0.003136071,0.002359481,0.0005968948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002798253,0.000838519,0.009520794,0.000697576,0.000243096,0.001036461,0.000225459,0.2533126,0.02586952,0.07241001,0.04288515,0.5901626],"study_design_scores_gemma":[0.0001999008,0.0009908492,0.002683174,0.0001431076,0.0001140929,0.001429453,0.00022579,0.8945354,0.0374804,0.03929651,0.02284396,0.00005748068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1859702,0.001563675,0.7507051,0.003509035,0.0008973531,0.0004649918,0.0009172351,0.01385195,0.04212054],"genre_scores_gemma":[0.9005502,0.0002299201,0.08192599,0.0004794867,0.00008188785,0.00009372958,0.000357549,0.0003954962,0.01588565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009336791,"threshold_uncertainty_score":0.03123468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01379885153005691,"score_gpt":0.2807438770143954,"score_spread":0.2669450254843385,"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."}}