{"id":"W2773353016","doi":"10.5194/bg-14-5471-2017","title":"Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds","year":2017,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Churchill Northern Studies Centre; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Churchill Northern Studies Centre","keywords":"Spatial variability; Environmental science; Permafrost; Tundra; Precipitation; Biogeochemistry; Bay; Hydrology (agriculture); Physical geography; Ecology; Arctic; Oceanography; Geography; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002391406,0.0001903302,0.000308797,0.0008199626,0.0003841064,0.0005535418,0.0003238249,0.0002079188,0.0007558362],"category_scores_gemma":[0.0004808327,0.0001469505,0.0001985723,0.001011454,0.0002338636,0.0004326958,0.0004766688,0.000199885,0.0001577855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005210998,"about_ca_system_score_gemma":0.0003233187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01700871,"about_ca_topic_score_gemma":0.05136232,"domain_scores_codex":[0.9998839,0.00001119259,0.000007231813,0.00005092928,0.00002501569,0.00002168769],"domain_scores_gemma":[0.9996297,0.00004571207,0.0001281281,0.00002338351,0.0001164256,0.00005661243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008507773,0.00003394906,0.9852254,0.00002280197,0.00003732545,0.00005150107,0.000277653,0.0002570086,0.006980848,0.00002289288,0.000136383,0.006869141],"study_design_scores_gemma":[0.000002250156,0.00002127612,0.9980647,0.000002772555,0.000007949993,0.00002201642,0.0002221189,0.00105686,0.0004103886,0.00001991715,0.0001675112,0.000002172786],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987419,0.00005234133,0.0003262224,0.000008592757,0.000002301624,0.000008131836,0.0004018926,0.00001635712,0.0004422757],"genre_scores_gemma":[0.9984176,0.00003698152,0.000781754,0.00001421033,0.000003246697,0.00001458624,0.0004987143,0.000004078478,0.0002288652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01700871,"threshold_uncertainty_score":0.03381944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03660370720062914,"score_gpt":0.2511828609691625,"score_spread":0.2145791537685333,"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."}}