{"id":"W4409219403","doi":"10.32920/28745414","title":"Color Accuracy of Corporate Colors in Expanded Gamut Print Reproduction","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":"Toronto Metropolitan University","funders":"","keywords":"Gamut; Reproduction; Color space; Computer vision; Mathematics; Artificial intelligence; Computer science; Biology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029115,0.0003969998,0.0002708717,0.0008184451,0.0003491324,0.002064639,0.0009181424,0.0006499881,0.004635439],"category_scores_gemma":[0.01803862,0.0003794565,0.0002570753,0.001090173,0.0007616782,0.001004521,0.0007961122,0.0007119855,0.001444246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006160699,"about_ca_system_score_gemma":0.0002462737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002216108,"about_ca_topic_score_gemma":0.001610754,"domain_scores_codex":[0.9930984,0.001089377,0.0002659672,0.0007456325,0.004533495,0.0002670051],"domain_scores_gemma":[0.9843466,0.007629467,0.001181718,0.00211192,0.004606393,0.0001237834],"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":[0.002778203,0.0003301101,0.04107297,0.0006131957,0.0001017419,0.0008957077,0.002534649,0.03108654,0.4366068,0.006929504,0.006391205,0.4706593],"study_design_scores_gemma":[0.00004954762,0.001285684,0.07414941,0.0001586639,0.0001212049,0.001139907,0.0009548053,0.05538633,0.8492877,0.001333668,0.01596148,0.0001717258],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.880886,0.002894632,0.07462632,0.0003810131,0.0004092212,0.000129133,0.0004624008,0.00107082,0.03914048],"genre_scores_gemma":[0.9749777,0.000364339,0.0179844,0.00007724462,0.0000180736,0.00003078748,0.0002169909,0.0002939638,0.006036496],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004635439,"threshold_uncertainty_score":0.01550716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04458570066663844,"score_gpt":0.320756651143143,"score_spread":0.2761709504765045,"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."}}