{"id":"W2021406646","doi":"10.1016/j.jastp.2011.01.003","title":"An evaluation of uncertainties in monitoring middle atmosphere temperatures with the ground-based lidar network in support of space observations","year":2011,"lang":"en","type":"article","venue":"Journal of Atmospheric and Solar-Terrestrial Physics","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Institut national des sciences de l'Univers; Jet Propulsion Laboratory; European Commission; Centre National d’Etudes Spatiales; National Aeronautics and Space Administration; California Institute of Technology; Scheme for Promotion of Academic and Research Collaboration; University of Toronto","keywords":"Lidar; Weighting; Environmental science; Remote sensing; Meteorology; Classification of discontinuities; Atmosphere (unit); Satellite; Term (time); Range (aeronautics); Geology; Physics; Mathematics; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009259449,0.0005613377,0.000412598,0.0008713652,0.0005532182,0.001500673,0.001126705,0.001561898,0.0003543402],"category_scores_gemma":[0.03413326,0.0003270968,0.0004935704,0.0009997055,0.0004891679,0.001968075,0.000864474,0.0005933568,0.00007410224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001346992,"about_ca_system_score_gemma":0.001073471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01787907,"about_ca_topic_score_gemma":0.01489952,"domain_scores_codex":[0.9969117,0.001376547,0.0002548588,0.0004141502,0.000897709,0.0001449611],"domain_scores_gemma":[0.9619017,0.0307689,0.002344129,0.001305278,0.003264768,0.0004151188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.004038919,0.0004421896,0.409606,0.0002574215,0.0007648717,0.0005181144,0.0003900243,0.5207054,0.01208552,0.001922899,0.0006189921,0.04864954],"study_design_scores_gemma":[0.0002095894,0.0006744422,0.165095,0.00006322873,0.0003471705,0.0002051487,0.0003377074,0.8236309,0.0071366,0.001504361,0.0007270953,0.0000687668],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913794,0.0002881359,0.006665902,0.0003101846,0.00001994152,0.00002682216,0.0004340053,0.00005355,0.0008220794],"genre_scores_gemma":[0.9966986,0.00004711901,0.002899776,0.00001908672,0.00001066907,0.000008393982,0.0002476049,0.000006265416,0.00006236399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01787907,"threshold_uncertainty_score":0.04896921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06101050857215348,"score_gpt":0.2492870793709336,"score_spread":0.1882765707987802,"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."}}