{"id":"W2143298665","doi":"10.5194/acp-16-3711-2016","title":"Carbonyl sulfide exchange in soils for better estimates of ecosystem carbon uptake","year":2016,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Oak Ridge National Laboratory; Biological and Environmental Research; Office of Science; Division of Atmospheric and Geospace Sciences; National Oceanic and Atmospheric Administration; Université Laval; Microsoft Research; National Science Foundation; Canon Foundation for Scientific Research; Division of Biological Infrastructure; U.S. Department of Energy","keywords":"Soil water; Carbonyl sulfide; Environmental science; Carbon cycle; Deciduous; Sink (geography); Atmospheric sciences; Ecosystem; Environmental chemistry; Soil science; Soil carbon; Flux (metallurgy); Chemistry; Hydrology (agriculture); Ecology; Geology; Geography; Sulfur","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004755949,0.0007202187,0.0003994956,0.0007357001,0.0002440347,0.0005088855,0.0004744975,0.0004074459,0.001035946],"category_scores_gemma":[0.0005658293,0.0002235864,0.0004016748,0.0009644212,0.0001410323,0.0009815916,0.0002790036,0.0003115664,0.0002471106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008456152,"about_ca_system_score_gemma":0.0003880036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01286011,"about_ca_topic_score_gemma":0.01568395,"domain_scores_codex":[0.9999058,0.00002953258,0.000006724393,0.0000309683,0.00001824835,0.000008784566],"domain_scores_gemma":[0.999795,0.0000715284,0.00004428459,0.00002802078,0.00004415146,0.00001702237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003770465,0.0003313617,0.4414669,0.0003897063,0.0004750873,0.0002348935,0.0001674414,0.222674,0.2841173,0.005235229,0.001533932,0.04299716],"study_design_scores_gemma":[0.00002964006,0.0000888642,0.1397722,0.000018764,0.00006453101,0.0000684123,0.0001455294,0.8189179,0.03542926,0.003133261,0.002280411,0.00005127453],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9179296,0.0006229045,0.07570586,0.0001555188,0.00003500082,0.00006206852,0.00270432,0.0005736876,0.002210966],"genre_scores_gemma":[0.9816254,0.0001554041,0.01712489,0.00002681429,0.000007930146,0.00003873385,0.0007166477,0.00002659157,0.0002775645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01286011,"threshold_uncertainty_score":0.02557051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005431031153552176,"score_gpt":0.190482314455024,"score_spread":0.1850512833014719,"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."}}