{"id":"W4388704353","doi":"10.1007/s11042-023-17547-4","title":"Blind image—variant based authentication method","year":2023,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia; Concordia University","funders":"","keywords":"Computer science; Digital watermarking; Robustness (evolution); Watermark; Computer vision; Artificial intelligence; Image (mathematics); DICOM; JPEG; Authentication (law); Image processing; Computer security","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":[0.0002727195,0.0005060172,0.0005172182,0.000715043,0.0004352906,0.0005933766,0.0007156347,0.0009287365,0.004733852],"category_scores_gemma":[0.0007837027,0.0001671627,0.0004399459,0.0005812077,0.000549236,0.00104072,0.0007169914,0.0004788355,0.002471814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143538,"about_ca_system_score_gemma":0.000371076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005505781,"about_ca_topic_score_gemma":0.0005747618,"domain_scores_codex":[0.9995408,0.0000807659,0.00002783648,0.0001219508,0.000184124,0.0000444917],"domain_scores_gemma":[0.9996152,0.00005856225,0.00003797843,0.0001301922,0.0001367317,0.00002132047],"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":[0.001180351,0.00009802863,0.0009362118,0.0002186917,0.00008552526,0.0003195333,0.0001003347,0.01239575,0.450325,0.03624502,0.004453166,0.4936425],"study_design_scores_gemma":[0.00009438326,0.000702822,0.003037196,0.00002975736,0.0001722479,0.003892901,0.00007021806,0.574737,0.3774964,0.01319516,0.02642927,0.0001426424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03024693,0.0006335959,0.9616799,0.0001657748,0.0002963001,0.00006565264,0.0001014199,0.0009918472,0.00581851],"genre_scores_gemma":[0.6391479,0.0008529484,0.3263009,0.0001886747,0.0002383955,0.00006763512,0.0003570603,0.0001070629,0.03273935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004733852,"threshold_uncertainty_score":0.01583636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334246775586076,"score_gpt":0.3209093727767106,"score_spread":0.287484695218103,"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."}}