{"id":"W1628364186","doi":"10.1023/a:1021117925505","title":"Inter-annual Variability of Moisture Flux from the Prairie Agro-ecosystem: Impact of Crop Phenology on the Seasonal Pattern of Tornado Days","year":2003,"lang":"en","type":"article","venue":"Boundary-Layer Meteorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Environmental science; Phenology; Grassland; Ecosystem; Tornado; Flux (metallurgy); Atmospheric sciences; Moisture; Climate change; Hydrology (agriculture); Agronomy; Ecology; Geography; Meteorology; Geology; Biology","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":[0.0003493876,0.0001729252,0.0001717144,0.0003678499,0.000265064,0.0004671806,0.0002402385,0.0003254234,0.001047565],"category_scores_gemma":[0.0007590801,0.0001702002,0.0002503796,0.0004197227,0.0002223436,0.0003243972,0.0002713957,0.0002949155,0.0001408232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003402297,"about_ca_system_score_gemma":0.0001981948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01938024,"about_ca_topic_score_gemma":0.02761334,"domain_scores_codex":[0.9999325,0.00001484248,0.000004205466,0.00002131408,0.000008681023,0.00001840233],"domain_scores_gemma":[0.9995679,0.0001843935,0.00005824602,0.00004158045,0.00006255398,0.00008520803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009591994,0.0001335949,0.9514125,0.0000496933,0.0002675538,0.0003030921,0.0003156842,0.01071186,0.02679217,0.0002892489,0.0007986883,0.007966742],"study_design_scores_gemma":[0.000007113088,0.0000152064,0.9949344,0.00000158102,0.00001379198,0.00002645682,0.00005126995,0.00450773,0.0002900563,0.00002893621,0.000118806,0.000004688104],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993492,0.00002785966,0.00007837504,0.0000238305,0.000003413133,0.00000123236,0.000311156,0.00001018239,0.0001947181],"genre_scores_gemma":[0.9993462,0.00002152507,0.00006357527,0.000006363043,0.000002900688,0.000001725745,0.0004397198,0.000004004924,0.0001139713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01938024,"threshold_uncertainty_score":0.03853488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009833610170512399,"score_gpt":0.2265084891381651,"score_spread":0.2166748789676527,"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."}}