{"id":"W4407678448","doi":"10.3390/jcp5010008","title":"Chaotic Hénon–Logistic Map Integration: A Powerful Approach for Safeguarding Digital Images","year":2025,"lang":"en","type":"article","venue":"Journal of Cybersecurity and Privacy","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Qatar National Library","keywords":"Safeguarding; Logistic map; Chaotic; Computer science; Digital image; Computer security; Artificial intelligence; Computer vision; Data mining; Image (mathematics); Image processing; Medicine","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":[0.0002643205,0.0005266542,0.0003784555,0.0006286522,0.0003137405,0.0005306148,0.0006004849,0.0005070224,0.001175761],"category_scores_gemma":[0.0007229614,0.0002054439,0.0003670402,0.0004002626,0.0004537939,0.001099617,0.001034417,0.0005941871,0.0004516398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000355117,"about_ca_system_score_gemma":0.0003598318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000338907,"about_ca_topic_score_gemma":0.0003362329,"domain_scores_codex":[0.9996692,0.00005202453,0.00001972255,0.00005046032,0.0001793088,0.00002934403],"domain_scores_gemma":[0.9998185,0.00004514608,0.00003280613,0.00004119612,0.00004918887,0.00001321416],"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":[0.0004696764,0.000122704,0.00210682,0.0003243533,0.0001838369,0.0008301749,0.0003316328,0.1148133,0.3150244,0.0621403,0.002462375,0.5011904],"study_design_scores_gemma":[0.00003217336,0.0003617542,0.0009276596,0.00002837465,0.00005564802,0.001260862,0.00005703128,0.8448605,0.1222213,0.0119148,0.01821105,0.00006877659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03914764,0.0007802436,0.9534826,0.0001936564,0.00008646803,0.00008406905,0.00002387291,0.0006111754,0.005590302],"genre_scores_gemma":[0.7141137,0.0006965876,0.2774188,0.00011131,0.00007267108,0.0001032622,0.00007670503,0.00009805559,0.007308918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001175761,"threshold_uncertainty_score":0.003933311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559833353367179,"score_gpt":0.2696537229272543,"score_spread":0.2540553893935825,"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."}}