{"id":"W2132607812","doi":"10.1109/iscas.2005.1465838","title":"CMOS Image Sensor with Watermarking Capabilities","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"CMC Microsystems","keywords":"Digital watermarking; Computer science; Image sensor; Pixel; CMOS; Chip; Process (computing); Image (mathematics); Artificial intelligence; Computer vision; Electronic engineering; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001375774,0.0001497571,0.0001258587,0.0001003255,0.0001395136,0.0001542047,0.0005146633,0.00003658052,0.00002021271],"category_scores_gemma":[0.000004425604,0.000099788,0.00005036089,0.0001836417,0.0001015305,0.001115478,0.0001317757,0.000103425,0.00001992662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002339947,"about_ca_system_score_gemma":0.00001366893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001469326,"about_ca_topic_score_gemma":0.00001146305,"domain_scores_codex":[0.9990004,0.00003464578,0.0001531602,0.0003200298,0.0001750252,0.0003167579],"domain_scores_gemma":[0.9992564,0.00004278475,0.00004070718,0.0005377691,0.00006052307,0.00006176511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001434803,0.0004593999,0.01593317,0.0001924709,0.0001590063,0.0002192557,0.01381195,0.0003902196,0.04326339,0.2665655,0.008126092,0.650736],"study_design_scores_gemma":[0.001078035,0.0004989746,0.002372099,0.000155671,0.00001859921,0.0004479227,0.0003341245,0.02918471,0.7220628,0.02978199,0.2123872,0.001677915],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0322943,0.00002220441,0.9439445,0.001361834,0.00006075274,0.0001397801,9.250708e-7,0.001273195,0.02090251],"genre_scores_gemma":[0.5083348,0.000005580594,0.4905331,0.0003044238,0.00004200286,0.0000133059,6.24963e-7,0.000006496883,0.0007597253],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6787994,"threshold_uncertainty_score":0.4069236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007792986081207364,"score_gpt":0.2240632311406573,"score_spread":0.2162702450594499,"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."}}