{"id":"W2802784924","doi":"10.1002/hyp.13146","title":"Using stable isotopes to estimate travel times in a data‐sparse Arctic catchment: Challenges and possible solutions","year":2018,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; McMaster University","funders":"FP7 Ideas: European Research Council; H2020 European Research Council; Natural Environment Research Council; Sight Research UK","keywords":"Snowmelt; Environmental science; Snowpack; Snow; Meltwater; Permafrost; Hydrology (agriculture); Catchment hydrology; Arctic; Drainage basin; Precipitation; Streamflow; Biogeochemical cycle; Climatology; Geology; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007665875,0.001680563,0.001485094,0.003235324,0.001306517,0.00295674,0.002462274,0.001697092,0.0005263233],"category_scores_gemma":[0.02234883,0.001061835,0.0008660863,0.005879932,0.0006658911,0.00231555,0.001503994,0.00152628,0.0002515391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002173924,"about_ca_system_score_gemma":0.004125381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2532786,"about_ca_topic_score_gemma":0.2530087,"domain_scores_codex":[0.9979686,0.0007553128,0.0002140183,0.0004748648,0.0003546537,0.0002325202],"domain_scores_gemma":[0.9882413,0.005410149,0.001311456,0.001134355,0.003397102,0.00050564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002102589,0.0002885477,0.4905124,0.0009937688,0.000801278,0.0004454024,0.001788982,0.213103,0.01005516,0.003571793,0.004555689,0.2736737],"study_design_scores_gemma":[0.00004851498,0.0001203709,0.1539196,0.0003547409,0.0001926527,0.0002632161,0.002821002,0.8192062,0.002692756,0.01107624,0.009140347,0.0001643477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5109319,0.008449532,0.4594118,0.007994113,0.0003713407,0.0003321478,0.005953408,0.00167197,0.004883838],"genre_scores_gemma":[0.6996501,0.003134874,0.2916955,0.0004019938,0.0002998651,0.0002239356,0.00360632,0.0001818115,0.0008055737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2532786,"threshold_uncertainty_score":0.5036086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2145131297784662,"score_gpt":0.3333311327547527,"score_spread":0.1188180029762865,"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."}}