{"id":"W4394881831","doi":"10.1145/3625468.3647611","title":"FlexMark","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Robustness (evolution); Generality; Embedding; Discriminator; Digital watermarking; Image quality; Artificial intelligence; Image (mathematics); Computer engineering; Data mining; Computer vision","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":[0.00007029031,0.00004209547,0.0000313337,0.00007496584,0.00002934662,0.0001475468,0.0003022997,0.0000170186,0.00001611582],"category_scores_gemma":[0.000001661291,0.00003059534,0.000036911,0.0002652163,0.00001186452,0.0003881585,0.00007884827,0.00004823077,0.00004805275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004774063,"about_ca_system_score_gemma":0.000007678388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002035564,"about_ca_topic_score_gemma":2.627749e-7,"domain_scores_codex":[0.9996392,0.000007513201,0.00005022331,0.0001483763,0.00006081173,0.00009383922],"domain_scores_gemma":[0.9997453,0.00002269456,0.000003157387,0.0002003465,0.000006966911,0.00002153049],"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":[1.889557e-7,0.000002489901,0.00001890763,0.000005504815,0.000002875348,0.0000202663,0.00005395899,5.991582e-7,0.0003361825,0.8605581,0.007117186,0.1318837],"study_design_scores_gemma":[0.00001887561,0.00002958497,0.0001155504,0.00003237962,0.000001180837,0.00002847007,0.000001992436,0.0202947,0.02536546,0.4774445,0.4765345,0.0001328067],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001583161,0.0002657077,0.9257106,0.0006289671,0.0002303453,0.00002508031,1.49802e-7,0.002366536,0.07061432],"genre_scores_gemma":[0.6823958,0.00002377995,0.3156473,0.000266603,0.00003244598,0.000006702876,2.838065e-7,0.000003319381,0.001623797],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6822375,"threshold_uncertainty_score":0.1422797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146978046067611,"score_gpt":0.2603271930075415,"score_spread":0.2488574125468654,"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."}}