{"id":"W2134144777","doi":"10.1364/josaa.28.001954","title":"Planckian regression temperature for least spectral error and least CIELAB error","year":2011,"lang":"en","type":"article","venue":"Journal of the Optical Society of America A","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Standard illuminant; Metric (unit); Mathematics; Approximation error; Spectral power distribution; Spectrum (functional analysis); Algorithm; Optics; Physics; Quantum mechanics","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":[0.0001158824,0.00008299766,0.000184432,0.000009304536,0.0001617436,0.00001865582,0.0002413385,0.00003247042,0.0000757462],"category_scores_gemma":[0.000009740975,0.00004721079,0.0002805293,0.0001625596,0.0002926229,0.00009444849,0.00005126784,0.0002124177,0.000001283154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001162186,"about_ca_system_score_gemma":0.00006954683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000145194,"about_ca_topic_score_gemma":3.164533e-7,"domain_scores_codex":[0.9993803,0.0000113895,0.0002087661,0.00009519779,0.000151013,0.000153346],"domain_scores_gemma":[0.9993865,0.00004350406,0.0002548615,0.0001214002,0.0001013061,0.00009241102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001139877,0.004069701,0.0834008,0.0002052213,0.001302405,0.00000292144,0.03567849,0.0003216671,0.4404212,0.05095101,0.2385633,0.1439434],"study_design_scores_gemma":[0.01154333,0.006350705,0.4608593,0.001722851,0.001623841,0.0002431847,0.145536,0.03006655,0.1601772,0.0559783,0.1233859,0.002512872],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810368,0.00007775804,0.006326591,0.009552154,0.0001618965,0.0002485151,0.00003363889,0.000005493945,0.002557109],"genre_scores_gemma":[0.9718827,0.000006075307,0.02742412,0.0001690866,0.0002123158,0.000004201755,6.82874e-7,0.000005688974,0.0002951293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3774585,"threshold_uncertainty_score":0.19252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0222125875637003,"score_gpt":0.2720674035743493,"score_spread":0.249854816010649,"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."}}