{"id":"W2787480243","doi":"","title":"Assimilation of GlobSnow snow water equivalent in the Canadian Land Data Assimilation System","year":2013,"lang":"en","type":"article","venue":"93rd American Meteorological Society Annual Meeting","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Data assimilation; Snow; Assimilation (phonology); Environmental science; Meteorology; Climatology; Geography; Geology","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":[0.0005144108,0.0007081912,0.0006000421,0.0009664987,0.001755126,0.001008206,0.001155639,0.0005237288,0.003144859],"category_scores_gemma":[0.001507623,0.0004207282,0.0007393464,0.002261963,0.0003363422,0.0008702451,0.000587166,0.0008183873,0.001032369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01036489,"about_ca_system_score_gemma":0.02562746,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9908262,"about_ca_topic_score_gemma":0.9930708,"domain_scores_codex":[0.999588,0.00002175011,0.00001598802,0.0000855018,0.0001800284,0.0001088379],"domain_scores_gemma":[0.9990847,0.00001618943,0.00001982956,0.00005419458,0.0007708541,0.00005435379],"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":[0.001056254,0.0003525398,0.1280914,0.0004918731,0.0009251197,0.000248171,0.0007627432,0.4519366,0.02222866,0.008919992,0.1929153,0.1920714],"study_design_scores_gemma":[0.0003276135,0.0000390036,0.2635261,0.00009342917,0.0002881108,0.00004475502,0.0004299689,0.6558117,0.009553402,0.001502071,0.06815572,0.0002280985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7784522,0.001791256,0.02385747,0.001648276,0.0008183478,0.0003498375,0.1553246,0.004739227,0.03301887],"genre_scores_gemma":[0.8808013,0.0007119838,0.02313945,0.0001791501,0.00004932636,0.0001244109,0.08406219,0.0005068668,0.01042535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01036489,"threshold_uncertainty_score":0.07520288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04063598270652158,"score_gpt":0.2453652712010951,"score_spread":0.2047292884945735,"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."}}