{"id":"W3204556440","doi":"10.1155/2021/9917145","title":"Accuracy Evaluation and Parameter Analysis of Land Surface Temperature Inversion Algorithm for Landsat-8 Data","year":2021,"lang":"en","type":"article","venue":"Advances in Meteorology","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Inversion (geology); Emissivity; Algorithm; Remote sensing; Radiative transfer; Logarithm; Infrared window; Inverse transform sampling; Environmental science; Computer science; Mathematics; Meteorology; Geology; Geography; Physics; Optics; Mathematical analysis","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":[0.0005533544,0.00006839758,0.0001994773,0.00004668635,0.00002963099,0.000006666009,0.0001192183,0.0000746993,0.000212312],"category_scores_gemma":[0.0004211846,0.00006041907,0.00002314987,0.0004156278,0.00007755043,0.0004095225,0.0001357095,0.00006130164,0.000001876139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000309087,"about_ca_system_score_gemma":0.00001233721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006907695,"about_ca_topic_score_gemma":0.001858292,"domain_scores_codex":[0.9990769,0.0001609602,0.000168655,0.0003339611,0.0001396386,0.0001198626],"domain_scores_gemma":[0.9989935,0.0005789347,0.0000750015,0.0003050006,0.00002390031,0.00002362584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000378182,0.000050325,0.728423,0.00001353409,0.0000994434,0.000003129789,0.0002725572,0.01135563,0.01033584,0.0000167455,0.0002774416,0.2491145],"study_design_scores_gemma":[0.001857612,0.000157758,0.1995947,0.00001198811,0.0009691457,0.000006375138,0.0001744906,0.7728146,0.008952341,0.003400815,0.01183448,0.0002257667],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949815,0.002505625,0.001877934,0.0001404021,0.00008531534,0.0001902361,0.0001112874,0.000004810472,0.0001028946],"genre_scores_gemma":[0.9499256,0.001134368,0.04786408,0.000160628,0.00001266404,0.00001272402,0.0008509351,0.000005042844,0.0000339789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7614589,"threshold_uncertainty_score":0.2463818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202256297242916,"score_gpt":0.3167066321580047,"score_spread":0.2946840691855755,"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."}}