{"id":"W3197752646","doi":"10.1029/2020wr028827","title":"Soil Moisture Responses to Rainfall: Implications for Runoff Generation","year":2021,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Farm Service Agency; U.S. Department of Agriculture; National Science Foundation","keywords":"Surface runoff; Antecedent moisture; Environmental science; Storm; Water content; Hydrology (agriculture); Precipitation; Drainage basin; Soil science; Runoff curve number; Geology; Ecology; Geography; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004232147,0.0001969036,0.0001623214,0.0002514043,0.0001417058,0.0004354377,0.0001585137,0.0001955398,0.0007349412],"category_scores_gemma":[0.001444706,0.0001422314,0.000249934,0.0003414368,0.0002128608,0.0002845128,0.0002368831,0.0002064081,0.00006320334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002927076,"about_ca_system_score_gemma":0.000196166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009403888,"about_ca_topic_score_gemma":0.005869719,"domain_scores_codex":[0.9998844,0.00004015142,0.000006829769,0.00002675378,0.00001708877,0.00002493242],"domain_scores_gemma":[0.9993809,0.0003567082,0.0001332329,0.00004367287,0.00004320554,0.000042223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002464701,0.0001162831,0.8793612,0.00004762432,0.0001568408,0.0001557212,0.0001675808,0.07653407,0.03228439,0.0004551357,0.0002459516,0.0102288],"study_design_scores_gemma":[0.000005739319,0.00005019641,0.9475548,0.000003084736,0.00001220486,0.00003281166,0.00006820491,0.05047495,0.001363353,0.0003224701,0.0001052317,0.000006944895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983017,0.00002245376,0.001164196,0.00003230543,0.000001421028,0.000006815383,0.0001889914,0.00001899214,0.0002630006],"genre_scores_gemma":[0.9998065,0.000008878728,0.0001031658,0.000004796763,0.000001426449,0.000002378337,0.00004115404,0.000001754395,0.00003002427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009403888,"threshold_uncertainty_score":0.01869828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07156351476032356,"score_gpt":0.3456673947757532,"score_spread":0.2741038800154296,"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."}}