{"id":"W4409218967","doi":"10.32920/28745420.v1","title":"Flexographic Expanded gamut printing with Proprietary and Nonproprietary Characterization Charts","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gamut; Characterization (materials science); Computer science; Computer graphics (images); Materials science; Artificial intelligence; Nanotechnology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002637278,0.001040367,0.0003903946,0.00310022,0.0003469581,0.001554275,0.0009848544,0.0005171882,0.01932872],"category_scores_gemma":[0.01038921,0.0004116682,0.0003923732,0.001728703,0.0005140635,0.001469888,0.0008517096,0.0005246018,0.002886144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006079626,"about_ca_system_score_gemma":0.0005610264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486621,"about_ca_topic_score_gemma":0.002072368,"domain_scores_codex":[0.9972806,0.0004431907,0.0002306878,0.0002904468,0.001648383,0.0001067649],"domain_scores_gemma":[0.9904723,0.003965472,0.0007501877,0.001584888,0.00306897,0.0001581032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002538561,0.0006590958,0.01667515,0.000791044,0.00007499936,0.0009949118,0.0008444854,0.02243362,0.1769678,0.008711551,0.02381402,0.7454947],"study_design_scores_gemma":[0.0002076366,0.00251849,0.04689491,0.0001730661,0.0001639681,0.002824811,0.000482544,0.1458622,0.7218132,0.002188883,0.07643887,0.0004313113],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4875285,0.00119263,0.3966964,0.0004099106,0.0004237906,0.001480918,0.004785312,0.03215837,0.07532407],"genre_scores_gemma":[0.7303017,0.0005101011,0.235051,0.0001803927,0.00008175473,0.0007479497,0.00224608,0.003856838,0.02702426],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01932872,"threshold_uncertainty_score":0.06466097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007988875025649753,"score_gpt":0.2348697064585515,"score_spread":0.2268808314329017,"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."}}