{"id":"W4240509139","doi":"10.5194/ems2021-395","title":"NWP verification against own analysis by using a Data Assimilation confidence mask","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Weighting; Data assimilation; Representativeness heuristic; Numerical weather prediction; Meteorology; Merge (version control); Radar; Computer science; Satellite; Environmental science; Remote sensing; Algorithm; Mathematics; Statistics; Geography; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005802909,0.0006776526,0.0005458762,0.0009340428,0.00074644,0.001774748,0.001212934,0.0006790237,0.00248547],"category_scores_gemma":[0.03033351,0.0003898483,0.0007202296,0.0005494703,0.0005744099,0.001447838,0.002393617,0.00104765,0.0006661945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009325139,"about_ca_system_score_gemma":0.002713386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02102457,"about_ca_topic_score_gemma":0.02052261,"domain_scores_codex":[0.9979572,0.0004736134,0.0001763682,0.0004768034,0.0007634178,0.000152529],"domain_scores_gemma":[0.9902126,0.00325192,0.001051223,0.002456076,0.002783658,0.0002445189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001606151,0.0002823319,0.1298399,0.000213938,0.0006899386,0.0004255626,0.0007017572,0.3542746,0.07421068,0.0193865,0.01271242,0.4056561],"study_design_scores_gemma":[0.00004445381,0.00005357736,0.01901931,0.00002475622,0.00004686133,0.00005360895,0.0000671438,0.9506635,0.02424617,0.001963916,0.003785064,0.00003165327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3933724,0.0001689553,0.5898615,0.0005871884,0.0001545019,0.0002230529,0.002112402,0.005549861,0.007970089],"genre_scores_gemma":[0.7682486,0.00002871392,0.2271164,0.0001269261,0.00003834382,0.00008413935,0.002548443,0.0006788856,0.001129568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02102457,"threshold_uncertainty_score":0.04180443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288509803134014,"score_gpt":0.3029263586469227,"score_spread":0.1740753783335213,"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."}}