{"id":"W4296608836","doi":"10.1007/s13753-022-00443-0","title":"Estimating Ground Snow Load Based on Ground Snow Depth and Climatological Elements for Snow Hazard Assessment in Northeastern China","year":2022,"lang":"en","type":"article","venue":"International Journal of Disaster Risk Science","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Fundamental Research Funds for the Central Universities; Ministry of Housing and Urban-Rural Development; National Natural Science Foundation of China; University of Cambridge","keywords":"Snow; Environmental science; Precipitation; Wind speed; Meteorology; Return period; Atmospheric sciences; Hydrology (agriculture); Geology; Geotechnical engineering; Geography","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":[0.0005525948,0.000689441,0.0003430875,0.001644825,0.0003842789,0.0003846157,0.0004652022,0.0002544675,0.0004200625],"category_scores_gemma":[0.00059101,0.0002166756,0.0003025878,0.000816575,0.0001724266,0.0004089052,0.0004471965,0.0001064003,0.00009983897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005734843,"about_ca_system_score_gemma":0.0007316683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03232508,"about_ca_topic_score_gemma":0.04650951,"domain_scores_codex":[0.9998319,0.00003233527,0.00002004853,0.00004333404,0.00004382023,0.00002847062],"domain_scores_gemma":[0.9996793,0.00005170928,0.00006820972,0.00002898244,0.0001288989,0.00004286064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002171904,0.0001578028,0.7113293,0.0001398334,0.0001128712,0.0005159662,0.0004732145,0.1795955,0.01583253,0.0003677853,0.000694035,0.090564],"study_design_scores_gemma":[0.00002618833,0.00008288171,0.3994063,0.0000138035,0.00005842356,0.00004931354,0.0003390059,0.596193,0.003076991,0.0003286805,0.0004047806,0.00002073353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920223,0.00005644205,0.007186298,0.00002238209,0.000003958624,0.00002312964,0.0001887672,0.00007166177,0.0004251654],"genre_scores_gemma":[0.9972724,0.00003016573,0.002308111,0.000003248951,0.000003052709,0.00001087653,0.0001899779,0.000002911785,0.0001791106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03232508,"threshold_uncertainty_score":0.06427389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02639679457679703,"score_gpt":0.300510242298604,"score_spread":0.2741134477218069,"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."}}