{"id":"W4319660263","doi":"10.1016/j.jenvman.2023.117461","title":"Recent water-level fluctuations, future trends and their eco-environmental impacts on Lake Qinghai","year":2023,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Environmental science; Water level; Climate change; Surface runoff; Hydrology (agriculture); Precipitation; Watershed; Water resources; Water quality; Physical geography; Geography; Ecology; Geology","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":[0.0003648409,0.0002205327,0.0001444246,0.0007905557,0.0004893999,0.0005735833,0.0002425645,0.0002160003,0.0009233829],"category_scores_gemma":[0.0003380503,0.0001472271,0.0002727859,0.001709042,0.0003069385,0.0004240333,0.0002815239,0.0001771707,0.00006048477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001331369,"about_ca_system_score_gemma":0.001098381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1479565,"about_ca_topic_score_gemma":0.2562613,"domain_scores_codex":[0.9998971,0.00001118798,0.00001582067,0.00002255027,0.00002323743,0.0000300101],"domain_scores_gemma":[0.9996923,0.00002961291,0.0001022464,0.000008547197,0.00008873783,0.00007854227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007783635,0.00003367106,0.9880012,0.00004470311,0.0001159147,0.0002541927,0.001135694,0.00116703,0.001733751,0.0002132395,0.0005143175,0.006708451],"study_design_scores_gemma":[0.000002036471,0.0000200848,0.9980002,0.000002615806,0.00002664783,0.00002807291,0.0004741485,0.0008618416,0.00006049788,0.00002811163,0.0004908259,0.000004796411],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991049,0.0001014592,0.00005271971,0.000104094,0.000003241934,0.000001695676,0.0003358506,0.000003600698,0.0002925516],"genre_scores_gemma":[0.9990395,0.0001041977,0.00004661355,0.00001723672,0.000005448811,0.000002105963,0.0004416293,9.962354e-7,0.0003422018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479565,"threshold_uncertainty_score":0.2941906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055848469723664,"score_gpt":0.2096118925895003,"score_spread":0.1990534078922637,"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."}}