{"id":"W2001153172","doi":"10.1046/j.1365-2486.2000.06013.x","title":"The energy and water balance of high‐latitude wetlands: controls and extrapolation","year":2000,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Permafrost; Wetland; Water balance; Energy balance; Latent heat; Precipitation; Snowmelt; Atmospheric sciences; Snow; Hydrology (agriculture); Water cycle; Geology; Ecology; Meteorology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001008865,0.0000787896,0.0001316857,0.00000571714,0.00009273316,0.00000799473,0.00007511069,0.00008404729,0.0003860233],"category_scores_gemma":[0.000004154209,0.00004242034,0.00001360631,0.00003274608,0.0002602299,0.00004539293,0.00005762735,0.00002260515,0.000009636431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001742801,"about_ca_system_score_gemma":0.000001245716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001604117,"about_ca_topic_score_gemma":0.00180898,"domain_scores_codex":[0.9994125,0.00005354718,0.0001144699,0.0001680649,0.00003727592,0.0002141113],"domain_scores_gemma":[0.9997987,0.00003549,0.00002902227,0.00009031225,0.000003318377,0.00004315176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008400122,0.00001271986,0.9308145,0.000001589029,0.0000121383,0.000001357883,0.00006055333,0.000001672317,0.001144717,0.002095238,0.0002539138,0.06551761],"study_design_scores_gemma":[0.0007196628,0.0002346041,0.9191259,0.000002415468,0.00001008018,0.00002445801,0.00000683872,0.000531515,0.0000825284,0.006400907,0.07276715,0.00009394091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964182,0.0005539226,0.0000633321,0.0008194192,0.00006628374,0.00007745013,0.00003309075,0.000009602943,0.001958642],"genre_scores_gemma":[0.9981287,0.001283525,0.00004465941,0.0003292111,0.00006664661,0.00001817442,0.00002780347,0.000002088045,0.0000991784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07251323,"threshold_uncertainty_score":0.4226685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009221034220685008,"score_gpt":0.2170534591181162,"score_spread":0.2078324248974312,"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."}}