{"id":"W2070434054","doi":"10.5194/bg-10-4371-2013","title":"Methane fluxes measured by eddy covariance and static chamber techniques at a temperate forest in central Ontario, Canada","year":2013,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Electric (Canada); University of Toronto","funders":"","keywords":"Eddy covariance; Environmental science; Flux (metallurgy); Atmospheric sciences; Methane; Temperate forest; Interception; Hydrology (agriculture); Temperate climate; Seasonality; Ecosystem; Ecology; Chemistry; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001732267,0.0001746454,0.0001613741,0.000006666559,0.0001386615,0.00004443719,0.0001832524,0.00005149041,0.001339528],"category_scores_gemma":[0.00001366664,0.0001405912,0.00001676126,0.0002016172,0.0005211713,0.0003334219,0.0001781603,0.00008292694,0.00001807176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000962843,"about_ca_system_score_gemma":0.00007507457,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9898494,"about_ca_topic_score_gemma":0.9875721,"domain_scores_codex":[0.9984466,0.00003986543,0.000201855,0.000403146,0.0004208244,0.0004876447],"domain_scores_gemma":[0.9995762,0.00002493116,0.00006968732,0.000143469,0.000002538671,0.0001832521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005758225,0.00003682428,0.9848794,0.000003045548,0.000002911686,0.000006051947,0.0003473022,0.0007216012,0.009941144,0.000007252512,0.002546861,0.001501832],"study_design_scores_gemma":[0.0001844691,0.00008107868,0.9798787,0.00001271102,0.000005428946,0.00001476851,0.0003010845,0.004793723,0.001592006,0.000181374,0.01264921,0.0003054011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983595,0.00007060776,0.0003617078,0.000322419,0.00008532619,0.0003187479,0.000009933236,0.00001858211,0.0004531965],"genre_scores_gemma":[0.9827926,0.00006129073,0.01286113,0.0005101485,0.000006683687,0.00005734744,0.000007159147,0.000008585292,0.003695116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01556694,"threshold_uncertainty_score":0.9995734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005853975787695591,"score_gpt":0.1794835666356195,"score_spread":0.1736295908479239,"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."}}