{"id":"W2120083670","doi":"10.1080/07038992.2015.1040876","title":"Optimizing the Heliosat-II Method for Surface Solar Irradiation Estimation with GOES Images","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"National Oceanic and Atmospheric Administration","keywords":"Albedo (alchemy); Satellite; Environmental science; Turbidity; Mean squared error; Remote sensing; Meteorology; Atmospheric sciences; Geography; Mathematics; Physics; Statistics; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001392432,0.0001075812,0.0001525197,0.0001592609,0.0004004767,0.0003275703,0.00027564,0.00004923232,6.921455e-7],"category_scores_gemma":[0.0003395808,0.00007776671,0.00005974999,0.0003262477,0.00003225365,0.0005450078,0.00001233873,0.0001758554,0.000001573886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002051637,"about_ca_system_score_gemma":0.001358493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002818914,"about_ca_topic_score_gemma":0.004810029,"domain_scores_codex":[0.9990479,0.0001304165,0.0002457876,0.0001248917,0.0002105711,0.0002404236],"domain_scores_gemma":[0.9983292,0.000172112,0.0003138912,0.0002175316,0.0005646815,0.0004025847],"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":[0.00002715417,0.000003754631,0.00005655576,0.00001413315,0.00006821859,0.00006768583,0.01376255,0.1475433,0.001093793,0.0004476392,0.003948155,0.832967],"study_design_scores_gemma":[0.0003948532,0.0001281688,0.0001244545,0.00005171163,0.00002258493,0.0005014439,0.0003320874,0.9783561,0.003521763,0.001493905,0.01495962,0.0001132987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01060552,0.0003239372,0.9836239,0.004670091,0.0005001596,0.0001410981,0.00000257159,0.00001432353,0.0001184092],"genre_scores_gemma":[0.1189054,0.000004431343,0.8803779,0.0005418628,0.0001163945,1.987713e-8,0.000001558377,0.0000119042,0.00004043165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8328537,"threshold_uncertainty_score":0.4261373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02780780942350329,"score_gpt":0.2672887791679642,"score_spread":0.2394809697444609,"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."}}