{"id":"W2950849703","doi":"","title":"Authorship Proof for Textual Document.","year":2007,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scheme (mathematics); Digital watermarking; Natural (archaeology); Information retrieval; Theoretical computer science; Computer security; Image (mathematics); Artificial intelligence; 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":[0.006083459,0.0006603461,0.0009312123,0.001905981,0.001808549,0.004203533,0.00146546,0.002480732,0.01308908],"category_scores_gemma":[0.04509749,0.0004086182,0.0008618449,0.001692896,0.004509606,0.01177714,0.003817182,0.003120843,0.003868441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014037,"about_ca_system_score_gemma":0.00157865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003392902,"about_ca_topic_score_gemma":0.0002414173,"domain_scores_codex":[0.9904276,0.003300705,0.001000813,0.001529234,0.003369107,0.0003724645],"domain_scores_gemma":[0.9305626,0.03948239,0.00708846,0.01481927,0.006875798,0.001171507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003650531,0.0001056849,0.0009410715,0.0009878404,0.00007080298,0.0007050384,0.0007993922,0.003728995,0.0093434,0.8125084,0.01410817,0.1563361],"study_design_scores_gemma":[0.0001162015,0.0001281031,0.0004176248,0.0004292466,0.00005920204,0.001489374,0.0002596222,0.04092621,0.02913153,0.8405886,0.08637667,0.00007761061],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02584226,0.002543035,0.9190337,0.009028894,0.001668903,0.0003019298,0.001162884,0.001771315,0.03864709],"genre_scores_gemma":[0.5517485,0.001957602,0.410787,0.001574467,0.001206229,0.0002955422,0.001759545,0.0003801709,0.03029098],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01308908,"threshold_uncertainty_score":0.04378736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805405024568698,"score_gpt":0.3158970230375547,"score_spread":0.2878429727918677,"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."}}