{"id":"W3090921718","doi":"10.1117/12.2583450","title":"Hyperspectral VIS/SWIR wide-field imaging for ink analysis","year":2020,"lang":"en","type":"article","venue":"","topic":"Currency Recognition and Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Photon Etc (Canada)","funders":"","keywords":"Hyperspectral imaging; Counterfeit; Inkwell; Reflectivity; Identification (biology); Remote sensing; Fidelity; Computer science; Field (mathematics); Camouflage; Artificial intelligence; Geology; Optics; Archaeology; Geography; Physics; Telecommunications; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.00006506209,0.00006736589,0.0001046615,0.0001061349,0.00007054031,0.000126641,0.0002050574,0.00001896006,0.0001653255],"category_scores_gemma":[0.00009444972,0.00006214319,0.000163492,0.0007952233,0.000006468821,0.0002955803,0.00004684111,0.00005993257,0.00005782863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001142328,"about_ca_system_score_gemma":0.00001757737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000218717,"about_ca_topic_score_gemma":0.00001734677,"domain_scores_codex":[0.9993578,0.00001260674,0.0001225196,0.000267842,0.00009991341,0.0001393824],"domain_scores_gemma":[0.9995803,0.00009934384,0.00003144156,0.0001339727,0.00006239954,0.00009251835],"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":[0.00008681272,0.000163421,0.0168055,0.00005761446,0.000543018,0.00001549621,0.003091375,0.0002723075,0.01010748,0.05177927,0.05414748,0.8629302],"study_design_scores_gemma":[0.0003832724,0.0001163971,0.001126304,0.000002384403,0.00008313784,0.000003255227,0.0001184836,0.9671712,0.02040414,0.002694989,0.00768953,0.0002069051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002955309,0.00002892048,0.9756514,0.01287374,0.0001608988,0.00008461295,0.000001201346,0.0002568651,0.007987003],"genre_scores_gemma":[0.9532039,0.000003934376,0.03943386,0.007137988,0.00009370175,0.00001234356,0.000002904492,0.000003385586,0.0001080527],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9668989,"threshold_uncertainty_score":0.2534126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651917348528195,"score_gpt":0.2668738780620624,"score_spread":0.2403547045767804,"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."}}