{"id":"W4321492672","doi":"10.5194/egusphere-egu23-1126","title":"Developing precipitation datasets for mountain regions in a changing climate","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Precipitation; Surface runoff; Drainage basin; Hydrology (agriculture); Water cycle; Population; Snow; Watershed; Climate change; Rain gauge; Climatology; Meteorology; Geography; Computer science; Geology; Cartography; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006899741,0.000449381,0.0003627832,0.001471416,0.0005214946,0.000672448,0.001245413,0.000468554,0.003729526],"category_scores_gemma":[0.002002559,0.0002378379,0.0006283314,0.003317311,0.0001451501,0.0005863243,0.0007089735,0.0005788375,0.002280691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008531192,"about_ca_system_score_gemma":0.001685081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1180213,"about_ca_topic_score_gemma":0.1591892,"domain_scores_codex":[0.9996492,0.00005034745,0.00003972508,0.00009560829,0.0001179414,0.00004720072],"domain_scores_gemma":[0.999188,0.00006656331,0.00008532548,0.0001718095,0.000379553,0.0001087158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005926665,0.0005367863,0.1913353,0.001567031,0.0007195705,0.000631279,0.001169806,0.1706552,0.01177851,0.005155431,0.41355,0.2023085],"study_design_scores_gemma":[0.0004582806,0.0001379379,0.4718485,0.0002610223,0.0001250514,0.0002282619,0.001213258,0.2166435,0.008643034,0.003591311,0.2967041,0.0001456044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.1262235,0.0003232205,0.02165116,0.0004997337,0.0001043479,0.0004258962,0.8318648,0.01002819,0.00887911],"genre_scores_gemma":[0.1110885,0.0002587514,0.04264494,0.00006040742,0.00003528881,0.0003433884,0.8439117,0.0003376854,0.001319333],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1180213,"threshold_uncertainty_score":0.2346687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06181761549775042,"score_gpt":0.3121695253284744,"score_spread":0.250351909830724,"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."}}