{"id":"W4388073873","doi":"10.1109/irmmw-thz57677.2023.10299101","title":"Radiometric Calibration of a Hyperspectral Microwave Sounder","year":2023,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Horizon Health Network; National Research Council Canada","funders":"","keywords":"Hyperspectral imaging; Remote sensing; Radiometric dating; Radiometric calibration; Calibration; Radiometry; Environmental science; Microwave; Microwave imaging; Computer science; Geology; Mathematics; Statistics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007078209,0.00004222549,0.0000580038,0.00008733168,0.00002876479,0.000007263535,0.00004552518,0.00003062031,0.0001351943],"category_scores_gemma":[0.00001643316,0.00003259627,0.00003380926,0.001147894,0.0000592826,0.00005846564,0.00003343692,0.0000306928,0.0002080456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003554197,"about_ca_system_score_gemma":0.000003365514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004345964,"about_ca_topic_score_gemma":0.00023885,"domain_scores_codex":[0.9995579,0.00001155338,0.00007951734,0.0001050436,0.0001323734,0.000113575],"domain_scores_gemma":[0.9998358,0.00002855475,0.00002046347,0.00008571525,0.000002000583,0.00002746104],"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":[0.000008552964,0.00003993056,0.04283025,0.00000702353,0.00001844953,0.00001419427,0.001129194,0.000921381,0.877978,0.000463468,0.01881187,0.05777763],"study_design_scores_gemma":[0.0004180556,0.00007687871,0.7210899,0.000006285848,0.00002001834,0.00003403081,0.001001228,0.01494508,0.2566946,0.004251713,0.001220157,0.0002420253],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8807747,0.00001332701,0.001508799,0.0003119646,0.00008816765,0.00004914728,1.277215e-7,0.00005991152,0.1171939],"genre_scores_gemma":[0.9957219,0.000007792602,0.001761567,0.00009809995,0.00002523856,1.002956e-7,0.000002460286,0.000005161749,0.002377626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6782597,"threshold_uncertainty_score":0.2674075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01516919195859745,"score_gpt":0.2268748938123575,"score_spread":0.21170570185376,"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."}}