{"id":"W4243802877","doi":"10.5194/acp-2019-942","title":"Moisture origin as a driver of temporal variabilities of the water vapour isotopic composition in the Lena River Delta, Siberia","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut Pierre-Gilles de Gennes; Siberian Branch, Russian Academy of Sciences; Alberta Agricultural Research Institute; National Aeronautics and Space Administration","keywords":"Environmental science; Moisture; Snow; Water cycle; Precipitation; Diurnal cycle; Climatology; Context (archaeology); Atmospheric sciences; Delta; Water vapor; Water content; Arctic; Geology; Geography; Meteorology; Oceanography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002945294,0.0002084702,0.0002192219,0.0005562283,0.0003728695,0.0006522761,0.0001646489,0.0001499017,0.0008256421],"category_scores_gemma":[0.0002679392,0.0001115954,0.0002069828,0.0005918426,0.0002253065,0.0002792386,0.0003993655,0.0001446773,0.000123523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004631807,"about_ca_system_score_gemma":0.0003898931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03166356,"about_ca_topic_score_gemma":0.03720897,"domain_scores_codex":[0.9999303,0.00001482526,0.000007290985,0.00002333591,0.000009061497,0.00001528519],"domain_scores_gemma":[0.9998639,0.00002576502,0.00003497238,0.00001316132,0.0000348469,0.00002742162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008773553,0.00002873476,0.9865595,0.00002519062,0.0001116468,0.0001695001,0.0002764774,0.0008998566,0.005615872,0.00007173273,0.0001921799,0.005961579],"study_design_scores_gemma":[0.00000155874,0.000005645647,0.998395,0.000004707337,0.00001080149,0.00001478551,0.0001756568,0.001028882,0.0001829679,0.00001526341,0.0001625244,0.000002106444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992047,0.00009851741,0.00006866345,0.00002316109,0.00000392497,0.000001441566,0.0002606848,0.000006011521,0.0003329357],"genre_scores_gemma":[0.9994566,0.00004109161,0.00004463354,0.000006637144,0.000002397132,0.000002359309,0.0003211593,0.000001818806,0.0001232929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03166356,"threshold_uncertainty_score":0.06295854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326272481519552,"score_gpt":0.2266017166667039,"score_spread":0.2133389918515084,"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."}}