{"id":"W4393796703","doi":"10.5281/zenodo.7196237","title":"Numerical Model Generated Baja Test Scenes for EarthCARE Pre-launch Studies - Part 1: Atmospheric and Surface Properties","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Atmospheric sciences; Meteorology; Environmental science; Surface (topology); Test (biology); Astrobiology; Geology; Geography; Geometry; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004889577,0.0008345672,0.0007830066,0.0007683102,0.0005533622,0.0008503271,0.001579701,0.0008149811,0.01230755],"category_scores_gemma":[0.001052398,0.0003722251,0.0007627444,0.001339575,0.0002886246,0.0006400561,0.000391252,0.001140862,0.005035982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351567,"about_ca_system_score_gemma":0.001506137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1358304,"about_ca_topic_score_gemma":0.166887,"domain_scores_codex":[0.9996624,0.00005823165,0.0000184015,0.0000896288,0.0000991098,0.00007224977],"domain_scores_gemma":[0.9994798,0.00006712864,0.00003239751,0.00009336844,0.0002682159,0.00005908791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008931021,0.0009451403,0.03084932,0.0004037101,0.0003433077,0.0001712118,0.0001618049,0.2881262,0.006271865,0.003701811,0.6474256,0.02070696],"study_design_scores_gemma":[0.001648097,0.0001543758,0.05540346,0.0001268188,0.000109186,0.000112085,0.0003339138,0.6987124,0.005711178,0.003082055,0.2344323,0.0001740108],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1401727,0.0003525032,0.008887659,0.0007206776,0.0005435182,0.0004648812,0.8207464,0.006799633,0.0213121],"genre_scores_gemma":[0.1989682,0.0001382988,0.01690538,0.0001861507,0.00006260926,0.0005236355,0.779234,0.001095991,0.00288579],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1358304,"threshold_uncertainty_score":0.2700796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07067688342054285,"score_gpt":0.2568207529251935,"score_spread":0.1861438695046506,"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."}}