{"id":"W2529474610","doi":"10.1186/s40064-016-3429-1","title":"Hydrological impacts of precipitation extremes in the Huaihe River Basin, China","year":2016,"lang":"en","type":"article","venue":"SpringerPlus","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Precipitation; Streamflow; Environmental science; Flooding (psychology); Drainage basin; Climatology; Structural basin; Flood myth; Wet season; Dry season; Hydrology (agriculture); Geography; Geology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004165099,0.00007689791,0.00009774942,0.00002775125,0.00005749331,0.000003507623,0.0001985492,0.00003894628,0.0003527975],"category_scores_gemma":[0.00007630876,0.00003648161,0.00003310917,0.00009805212,0.0003048267,0.0001221137,0.0001541124,0.0000503603,0.0002301159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003496139,"about_ca_system_score_gemma":0.0000014781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001694394,"about_ca_topic_score_gemma":0.000114776,"domain_scores_codex":[0.9992849,0.00009291709,0.0001284637,0.0001621211,0.0001422309,0.0001893693],"domain_scores_gemma":[0.9996886,0.00007913997,0.00005043444,0.0001626014,0.000001788938,0.0000174371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000055629,0.00009079622,0.9820853,0.000005693156,0.00001539079,0.00001209516,0.003392776,0.0001688366,0.00362438,0.0006363251,0.001208891,0.008703925],"study_design_scores_gemma":[0.0002777659,0.00007316233,0.992978,0.000008974933,0.000007739482,9.152844e-7,0.00003101641,0.00003967073,0.0005675331,0.003750804,0.002206857,0.00005758214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846305,0.00002911048,0.0002148522,0.003234104,0.00005562395,0.0001418071,9.639265e-7,0.00001356044,0.01167951],"genre_scores_gemma":[0.9993186,0.00006401238,0.000138674,0.0002396562,0.00001460309,0.0000126872,4.163534e-7,0.000003081725,0.0002082953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01468811,"threshold_uncertainty_score":0.3862885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071138089892372,"score_gpt":0.2239680996105052,"score_spread":0.2132567187115815,"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."}}