{"id":"W3046658175","doi":"10.5445/ir/1000077312","title":"The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements","year":2017,"lang":"en","type":"article","venue":"Repository KITopen (Karlsruhe Institute of Technology)","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Naval Research Laboratory; Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; Universität Bremen; Scheme for Promotion of Academic and Research Collaboration; Tekes; Deutsches Zentrum für Luft- und Raumfahrt; Centre National d’Etudes Spatiales; National Aeronautics and Space Administration; European Space Agency; Canadian Space Agency; Deutsche Forschungsgemeinschaft","keywords":"Satellite; Environmental science; Microwave; Remote sensing; Water vapor; Microwave radiometer; Meteorology; Atmospheric sciences; Radiometer; Geology; Physics; Computer science; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000745417,0.0001760077,0.0003444679,0.0001815283,0.001161281,0.0001570668,0.0008898274,0.0001326121,0.00002131222],"category_scores_gemma":[0.0000650387,0.0001096471,0.0001014219,0.00009221927,0.0008075051,0.0004070425,0.0001105261,0.0001874243,0.000006892791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001682833,"about_ca_system_score_gemma":0.00008544909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008541881,"about_ca_topic_score_gemma":0.001509666,"domain_scores_codex":[0.998444,0.0000519511,0.0005296016,0.0002952491,0.0004215529,0.0002576188],"domain_scores_gemma":[0.9984885,0.00002402655,0.0004743257,0.0007536147,0.000199777,0.0000597473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006887737,0.00006431105,0.7913147,0.00005520246,0.0002475079,0.00001070359,0.00008014283,0.0001602317,0.1080886,0.0001565959,0.00008995082,0.09966319],"study_design_scores_gemma":[0.0007832145,0.0002847967,0.5587927,0.0001914832,0.0002005844,0.00001179275,0.0001322263,0.0009925982,0.4142586,0.0006587764,0.02341965,0.0002735867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866748,0.001005861,0.0002366526,0.001174517,0.0008118124,0.0002616273,0.0000050711,0.00003539914,0.009794291],"genre_scores_gemma":[0.9963288,0.0001093449,0.003193679,0.00001681551,0.00003932145,0.000004623208,0.00001614983,0.000003993614,0.0002872863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3061699,"threshold_uncertainty_score":0.8931753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03831755993136351,"score_gpt":0.2677374332334896,"score_spread":0.2294198733021261,"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."}}