{"id":"W2031688023","doi":"10.1016/j.agrformet.2010.06.007","title":"Estimating annual carbon dioxide eddy fluxes using open-path analysers for cold forest sites","year":2010,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Canadian Forest Service; Natural Sciences and Engineering Research Council of Canada; Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Eddy covariance; Environmental science; Ecosystem respiration; Taiga; Atmospheric sciences; Boreal; Carbon dioxide; Ecosystem; Boreal ecosystem; Flux (metallurgy); Soil respiration; Climatology; Soil water; Ecology; Soil science; Physics; Forestry; Chemistry; Geography","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":[0.0005597923,0.0006377012,0.0004344112,0.001086347,0.000665826,0.0005625788,0.0005436507,0.0005870051,0.0005662107],"category_scores_gemma":[0.0009306095,0.0004396878,0.0003993191,0.001103792,0.0002056785,0.0007126983,0.0002429003,0.0003453581,0.0002101631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006863879,"about_ca_system_score_gemma":0.0007044345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0655581,"about_ca_topic_score_gemma":0.1397322,"domain_scores_codex":[0.9998471,0.00002813117,0.00001057756,0.00004900093,0.00003364626,0.0000316112],"domain_scores_gemma":[0.9994475,0.0002171629,0.00006873367,0.00005726604,0.0001352918,0.00007394116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008028481,0.0005044057,0.7909317,0.00008777369,0.0004293129,0.0002152554,0.0004734643,0.09784916,0.04601733,0.000223643,0.0009212093,0.06154399],"study_design_scores_gemma":[0.00009625941,0.0001113356,0.8152201,0.000008376121,0.0001418744,0.00007639389,0.0002032207,0.1763258,0.007102667,0.000205727,0.0004632042,0.00004508525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978381,0.00002764948,0.001434495,0.000006546062,0.000002840882,0.00001219642,0.0003904644,0.00006284085,0.0002248901],"genre_scores_gemma":[0.990139,0.00003387961,0.008495692,0.000004448575,0.000003892465,0.00001896243,0.001082947,0.0000250599,0.0001961015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0655581,"threshold_uncertainty_score":0.130353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009462456494256113,"score_gpt":0.2260944547354642,"score_spread":0.2166319982412081,"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."}}