{"id":"W2994976242","doi":"","title":"Alberta Soil Moisture Analyses using CaLDAS","year":2012,"lang":"en","type":"article","venue":"AGUFM","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Moisture; Environmental science; Water content; Soil science; Hydrology (agriculture); Geology; Geography; Meteorology; Geotechnical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008489739,0.0001187963,0.0001178662,0.00001943054,0.000133358,0.0000180768,0.00009841891,0.0000790945,0.0002376444],"category_scores_gemma":[0.00003316299,0.00009028521,0.00007004516,0.0001888698,0.00009271543,0.0001886834,0.00009756784,0.0001033158,0.0006488665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008375003,"about_ca_system_score_gemma":0.000004484709,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.057589,"about_ca_topic_score_gemma":0.01323539,"domain_scores_codex":[0.9991598,0.00003375186,0.0001123971,0.0001633057,0.0001907089,0.0003401128],"domain_scores_gemma":[0.999553,0.00004283907,0.0000447804,0.0002239108,0.000003405368,0.0001320446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001911901,0.0002436552,0.6550603,0.00001509641,0.0001105284,0.00002967444,0.004269455,0.0223747,0.2497204,0.00007888381,0.01149482,0.05658342],"study_design_scores_gemma":[0.0003059554,0.00002539064,0.8836127,0.00002766757,0.0001695301,0.0001373544,0.0003691244,0.008163736,0.02687877,0.0001986295,0.07953081,0.0005803673],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8511271,0.0002198108,0.0001186867,0.0001505711,0.0002923576,0.0000442137,2.112021e-7,0.00002278265,0.1480243],"genre_scores_gemma":[0.9959691,0.000005772161,0.0009768222,0.0005808031,0.0002793659,1.700885e-7,0.000002641558,0.00001433761,0.002171009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2285524,"threshold_uncertainty_score":0.9486866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04611639481141172,"score_gpt":0.3105621140307153,"score_spread":0.2644457192193035,"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."}}