{"id":"W2074901471","doi":"10.1117/12.692733","title":"Full-field optical coherence tomography used for security and document identity","year":2006,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Optical coherence tomography; Image resolution; Software; Medical imaging; Pixel; Computer vision; Optics; Artificial intelligence; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005082256,0.0003683891,0.0004370461,0.000139323,0.000106603,0.0002202011,0.0007917135,0.0002543781,0.0000136012],"category_scores_gemma":[0.0002190503,0.0003422695,0.0006166144,0.000512002,0.0002906735,0.0007664778,0.0001309267,0.0003434492,0.000001185698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009281026,"about_ca_system_score_gemma":0.00001683538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001664986,"about_ca_topic_score_gemma":0.000002222514,"domain_scores_codex":[0.9977291,1.56948e-8,0.0007338992,0.0004278357,0.0006093197,0.0004998958],"domain_scores_gemma":[0.9982722,0.0003363327,0.0001748606,0.00008604515,0.0009676426,0.0001628666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005336034,0.00008649685,0.0006228735,0.0006181285,0.0002569071,4.690015e-8,0.00007734641,0.0001555262,0.3128894,0.6830061,0.0020532,0.0001806051],"study_design_scores_gemma":[0.004826966,0.001909963,0.006688166,0.0008156759,0.001005079,0.00004435859,0.002043852,0.1061047,0.6923494,0.1745766,0.007407578,0.002227726],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937916,0.0001927633,0.001063601,0.001079855,0.000171443,0.001100454,0.00007650594,0.000224037,0.002299774],"genre_scores_gemma":[0.8754863,0.00006124322,0.1233335,0.00004195317,0.0003016406,0.0006741379,0.00001236945,0.00006191232,0.00002692307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5084295,"threshold_uncertainty_score":0.9999029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007434129052402394,"score_gpt":0.2297814440142944,"score_spread":0.222347314961892,"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."}}