{"id":"W4377988201","doi":"10.1002/col.22862","title":"Spectral reflectance estimation from non‐raw color images with nonlinearity correction","year":2023,"lang":"en","type":"article","venue":"Color Research & Application","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Color correction; Artificial intelligence; Computer science; Radiance; Computer vision; Nonlinear system; Color balance; Spectral signature; Spectral color; Color image; Mathematics; Algorithm; Image (mathematics); Color space; Remote sensing; Color model; Image processing; 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006376729,0.0001393094,0.0001534772,0.0001742113,0.000691985,0.000175597,0.0003793079,0.00004790716,0.0001025767],"category_scores_gemma":[0.00003320178,0.0001282479,0.00004426425,0.00232621,0.0002344802,0.0003090204,0.0000969609,0.0003732795,0.00131909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321193,"about_ca_system_score_gemma":0.0002003979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052169,"about_ca_topic_score_gemma":0.000218353,"domain_scores_codex":[0.9981337,0.00006750919,0.0002154321,0.0005849318,0.0005294777,0.0004689621],"domain_scores_gemma":[0.9985795,0.0003349207,0.0001015427,0.0005191706,0.0003337365,0.0001311475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004937417,0.001000515,0.02183953,0.00003384721,0.00009635081,0.000004733114,0.001343482,0.1847359,0.4427046,0.0163303,0.05894045,0.2724765],"study_design_scores_gemma":[0.0003407433,0.0001528847,0.0412803,0.00001944656,0.00001235262,5.212041e-7,0.0004429008,0.9057544,0.03828754,0.008147389,0.005380773,0.0001806798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403049,0.000005471905,0.05038547,0.00196605,0.00008277498,0.001420152,0.00005877901,0.0001919294,0.005584448],"genre_scores_gemma":[0.9925088,0.000007711909,0.003004047,0.00001999874,0.0003368649,0.00225994,0.0005489119,0.00002027875,0.001293443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7210186,"threshold_uncertainty_score":0.9994585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03503029299233091,"score_gpt":0.3942855578885286,"score_spread":0.3592552648961977,"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."}}