{"id":"W4210629551","doi":"10.1175/bams-d-21-0106.1","title":"EM-Earth: The Ensemble Meteorological Dataset for Planet Earth","year":2022,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Climate variability and models","field":"Environmental Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canmore Museum and Geoscience Centre; University of Saskatchewan; University of Calgary","funders":"Global Water Futures; Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrometeorology; Meteorology; Probabilistic logic; Environmental science; Earth observation; Precipitation; Classification of discontinuities; Earth (classical element); Satellite; Computer science; Geography; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001690112,0.00101338,0.0008222555,0.001643299,0.0004145949,0.0008663347,0.002033096,0.0008394851,0.004180832],"category_scores_gemma":[0.00380331,0.0003695891,0.0009630127,0.003470747,0.0002826203,0.001158762,0.00142638,0.00135516,0.004240506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004863847,"about_ca_system_score_gemma":0.001326316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02423417,"about_ca_topic_score_gemma":0.02533176,"domain_scores_codex":[0.9991503,0.0001968311,0.0001339091,0.0002156103,0.0002313066,0.00007207713],"domain_scores_gemma":[0.9981411,0.0002787325,0.0002396876,0.0005904792,0.0005979987,0.000152028],"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":[0.0003546054,0.0002097504,0.04179915,0.0007108716,0.0005888562,0.0002499843,0.0001760776,0.05723216,0.003025868,0.003352018,0.8523235,0.03997725],"study_design_scores_gemma":[0.001282795,0.0001381935,0.1604559,0.0003331819,0.0002259103,0.0002062047,0.000281818,0.2271521,0.006222055,0.006772369,0.5966421,0.0002873498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0198475,0.0002217223,0.009373549,0.0003117772,0.0001572731,0.0001540547,0.9630759,0.004967802,0.001890381],"genre_scores_gemma":[0.02092425,0.00007119869,0.009182458,0.00006188139,0.00004452077,0.0002198626,0.9689369,0.0002123945,0.0003466464],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02423417,"threshold_uncertainty_score":0.04818624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0244529370316642,"score_gpt":0.2437708566644213,"score_spread":0.2193179196327571,"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."}}