{"id":"W3103600114","doi":"10.82308/17783","title":"Use of single Doppler radar observations in data assimilation at convective scale with model as a weak constraint","year":2010,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Doppler radar; Doppler effect; Data assimilation; Assimilation (phonology); Radar; Scale (ratio); Meteorology; Constraint (computer-aided design); Remote sensing; Computer science; Environmental science; Geology; Mathematics; Geography; Physics; Telecommunications","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":[0.000763992,0.0004334784,0.0007276637,0.0002976354,0.0003924034,0.0006674039,0.0006751244,0.000533706,0.0004360015],"category_scores_gemma":[0.002185306,0.0003094256,0.0005208568,0.0004478355,0.0001997291,0.001002858,0.0007229263,0.0006418506,0.00009938721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003288478,"about_ca_system_score_gemma":0.0009638443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159983,"about_ca_topic_score_gemma":0.01925255,"domain_scores_codex":[0.999741,0.00007786584,0.00001877512,0.00007193546,0.00005551542,0.00003481937],"domain_scores_gemma":[0.999496,0.0002104137,0.00006251298,0.0001051721,0.00008900066,0.00003687601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000937682,0.00007748647,0.007224597,0.00005782723,0.0001354407,0.00009480621,0.00006434565,0.9257032,0.01427583,0.003246771,0.0002012278,0.04882473],"study_design_scores_gemma":[0.000003437255,0.0000117891,0.0005930373,0.000001640641,0.000005281801,0.000003371569,0.000002064674,0.9983247,0.000757904,0.0001861191,0.0001052407,0.000005488172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4889841,0.0006399878,0.5068212,0.0003206198,0.0001122121,0.00005390869,0.000328476,0.0004410344,0.002298468],"genre_scores_gemma":[0.9294946,0.0001507144,0.06957272,0.00004270301,0.00002617837,0.00003213515,0.0002375442,0.00004942853,0.0003940416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0159983,"threshold_uncertainty_score":0.03181034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.101541576361633,"score_gpt":0.2429993661307769,"score_spread":0.1414577897691439,"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."}}