{"id":"W4393503016","doi":"10.5281/zenodo.7258361","title":"Numerical Model Generated Halifax 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":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Astrobiology; Test (biology); Environmental science; Surface (topology); Meteorology; Remote sensing; Atmospheric sciences; Geology; Aerospace engineering; Geography; Engineering; Physics; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004308388,0.0003359831,0.0003739972,0.00002315901,0.003654533,0.0003637187,0.0007933638,0.00009240818,0.02298266],"category_scores_gemma":[0.0007455005,0.0002965652,0.00006977738,0.0004016819,0.0004611558,0.0001999381,0.003021435,0.0003325614,0.0007925192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000227039,"about_ca_system_score_gemma":0.000005494188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001164793,"about_ca_topic_score_gemma":0.000005286182,"domain_scores_codex":[0.9976441,0.0002327255,0.0003226124,0.0007810052,0.0005285607,0.0004909603],"domain_scores_gemma":[0.9990386,0.0000504089,0.0001459017,0.0004527938,0.000159449,0.0001528438],"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":[0.00004862733,0.0001389265,0.00001148642,0.000212237,0.00008355606,0.000006446192,0.0005137902,0.008821933,0.0002886135,0.000003311457,0.9853833,0.004487775],"study_design_scores_gemma":[0.0003028117,0.0003661793,0.00005742805,0.00004304437,0.00004698052,0.00002247849,0.0004070794,0.005915174,0.00006423159,0.00001640172,0.9923941,0.0003640813],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007178567,0.002738652,0.0001300631,0.0009620996,0.000215744,0.001467717,0.9860691,0.0004703767,0.0007676862],"genre_scores_gemma":[0.005977171,0.00484683,0.0007316978,0.0004356295,0.0002906176,0.000002521112,0.9789932,0.001619927,0.007102448],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02219014,"threshold_uncertainty_score":0.9999855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05486172175742394,"score_gpt":0.2510026559254414,"score_spread":0.1961409341680175,"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."}}