{"id":"W2511393167","doi":"","title":"Snow Hydrology: Flooding, Modeling, and Vegetation Interactions I","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Snow; Hydrology (agriculture); Vegetation (pathology); Flooding (psychology); Environmental science; Snowmelt; Physical geography; Geology; Geography; Meteorology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000281964,0.00009175095,0.0001148439,0.00002585979,0.0003496267,0.00004810475,0.00007136867,0.00003495549,0.00006558192],"category_scores_gemma":[0.0002122824,0.00008082839,0.00002906722,0.00007056272,0.00003196772,0.0001432374,0.00001550329,0.0001006785,0.0001249984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000272957,"about_ca_system_score_gemma":0.000006473219,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006571128,"about_ca_topic_score_gemma":0.04021948,"domain_scores_codex":[0.999303,0.00004781551,0.0001692883,0.0001978268,0.00009147297,0.0001906324],"domain_scores_gemma":[0.9995129,0.0002237503,0.00006477341,0.00009990551,0.00003782202,0.00006086277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006108128,0.000007516342,0.8648241,0.00001479722,0.00002043261,5.90531e-7,0.00061744,0.1048452,0.00002683263,0.000216685,0.001087041,0.02833334],"study_design_scores_gemma":[0.0001209456,0.00003594606,0.1488648,0.00002540374,0.00001657991,0.00000355319,0.0001780394,0.8406671,0.000003211712,0.0005804717,0.009406893,0.00009710955],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787894,0.0006712584,0.004015731,0.0004638941,0.0004349642,0.00006653622,0.00000237344,0.00005727116,0.01549852],"genre_scores_gemma":[0.9960976,0.000128688,0.003045355,0.000339057,0.000218744,0.000001836185,0.00002553998,0.000003442093,0.0001397746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7358219,"threshold_uncertainty_score":0.9933623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198029226221718,"score_gpt":0.2289124934230797,"score_spread":0.2091095708009079,"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."}}