{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000160923,0.0003625401,0.0003035655,0.0003021971,0.0002229321,0.0004119614,0.0006246828,0.0007491055,0.003976387],"category_scores_gemma":[0.0006511702,0.000213805,0.0002350583,0.0004789049,0.0002710732,0.0008743244,0.0004072845,0.0004302621,0.002256726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541944,"about_ca_system_score_gemma":0.0002116875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001893139,"about_ca_topic_score_gemma":0.000316637,"domain_scores_codex":[0.9996833,0.00002481715,0.00001565071,0.0000565712,0.0001971199,0.00002268677],"domain_scores_gemma":[0.9997661,0.00004040086,0.00003862926,0.00003001091,0.0001095862,0.00001544949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001544321,0.00003339364,0.0003515568,0.0003224335,0.00002079435,0.0001791817,0.00005463216,0.001514609,0.8838017,0.01083964,0.003884483,0.09884322],"study_design_scores_gemma":[0.00005258141,0.0007002756,0.001305224,0.00003891074,0.00009383909,0.002819118,0.00003043553,0.02684272,0.8443881,0.003575636,0.1201101,0.00004317238],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1443636,0.01655961,0.7289409,0.002371219,0.001169016,0.000570093,0.001511966,0.007620798,0.09689281],"genre_scores_gemma":[0.6015476,0.004137964,0.3579153,0.0009979844,0.0004187099,0.0001724784,0.0005031875,0.0001172315,0.03418952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003976387,"threshold_uncertainty_score":0.01330233,"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."}}