{"id":"W2896183999","doi":"10.5194/acp-19-4637-2019","title":"Analysis of atmospheric CH <sub>4</sub> in Canadian Arctic and estimation of the regional CH <sub>4</sub> fluxes","year":2019,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Climate Program Office; National Oceanic and Atmospheric Administration; National Aeronautics and Space Administration","keywords":"Arctic; Environmental science; Atmospheric sciences; Flux (metallurgy); Biomass burning; Climatology; Oceanography; Meteorology; Aerosol; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003713732,0.0006402899,0.0002630612,0.001229476,0.001347455,0.0006616047,0.0004687497,0.0002185673,0.0005690554],"category_scores_gemma":[0.0004272313,0.0002202532,0.0006343953,0.001735586,0.0002720648,0.0002094916,0.0003289924,0.0002417783,0.000109161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008963071,"about_ca_system_score_gemma":0.009501052,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9856899,"about_ca_topic_score_gemma":0.9885122,"domain_scores_codex":[0.9997718,0.000008328518,0.000006830563,0.00005105744,0.0001078114,0.00005422203],"domain_scores_gemma":[0.9997009,0.00001802884,0.0000334611,0.00001071579,0.0002037099,0.00003325423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003347182,0.00009324292,0.8213201,0.0002686325,0.0006074783,0.0003036047,0.0004428561,0.0645439,0.02772992,0.001068167,0.003713191,0.07957424],"study_design_scores_gemma":[0.000008024889,0.00001145854,0.9307497,0.00001466899,0.00008644931,0.00002111154,0.0001971592,0.06321935,0.003081857,0.00007515604,0.002509343,0.00002575214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918804,0.0004396749,0.001965383,0.00008929463,0.000009177745,0.00001613077,0.003431048,0.0001059155,0.002062911],"genre_scores_gemma":[0.9923954,0.0002806531,0.002334793,0.0000200801,0.000004570249,0.000007702516,0.004188764,0.00001697497,0.0007509479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01431012,"threshold_uncertainty_score":0.06503189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00346281739483598,"score_gpt":0.1777735523225791,"score_spread":0.1743107349277431,"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."}}