{"id":"W2560529955","doi":"","title":"A Practical Approach for Uncertainty Quantification of High Frequency Soil Respiration Using Forced Diffusion Chambers","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Eddy covariance; Statistics; Mathematics; Scaling; Flux (metallurgy); Covariance; Observational error; Environmental science; Soil respiration; Standard deviation; Range (aeronautics); Atmospheric sciences; Soil science; Soil water; Ecosystem; Physics; Ecology; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009010966,0.0001112438,0.0001487019,0.00003260478,0.000196881,0.0000329386,0.00009564719,0.0001054827,0.000007621846],"category_scores_gemma":[0.0002348891,0.00009932574,0.00005519464,0.0001035425,0.00008094584,0.000180597,0.00005125319,0.00008253401,0.000007661281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009882233,"about_ca_system_score_gemma":0.00001366099,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007548783,"about_ca_topic_score_gemma":0.0008097786,"domain_scores_codex":[0.9988223,0.0001071782,0.0003524673,0.000286214,0.0002318036,0.0002000046],"domain_scores_gemma":[0.9992735,0.0001269009,0.0003076218,0.0002175647,0.00002396618,0.00005039161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005784558,0.0001119183,0.05531785,0.00005595067,0.00001255783,2.501202e-7,0.0003773562,0.6268423,0.3095829,0.005979695,0.00009705649,0.001564308],"study_design_scores_gemma":[0.0002891287,0.00004518802,0.002877213,0.00002120911,0.00002766604,0.00000365907,0.00003186311,0.9948062,0.0008389279,0.0008254993,0.000105419,0.0001280179],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7417721,0.000003661314,0.2563698,0.00006117947,0.00005421791,0.0002334094,0.000007139889,0.00002164177,0.001476815],"genre_scores_gemma":[0.9104604,0.000004148096,0.08926976,0.00003080346,0.00003288702,0.00002067868,0.0001105348,0.00001329776,0.00005750993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3679639,"threshold_uncertainty_score":0.99906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691868840890126,"score_gpt":0.2575112814219247,"score_spread":0.2305925930130234,"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."}}