{"id":"W2943321341","doi":"10.3334/ornldaac/1658","title":"ABoVE: Atmospheric Profiles of CO, CO2 and CH4 Concentrations from Arctic-CAP, 2017","year":2019,"lang":"en","type":"article","venue":"Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Atmospheric sciences; Climatology; Arctic; Oceanography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003056847,0.0008138686,0.0004487406,0.001102343,0.0005449623,0.0007510704,0.0005655683,0.0003284455,0.003861085],"category_scores_gemma":[0.0003544691,0.00016585,0.000364433,0.001625964,0.0001280981,0.0003579792,0.000407836,0.0004762498,0.003724049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005650672,"about_ca_system_score_gemma":0.001588626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09896383,"about_ca_topic_score_gemma":0.1490687,"domain_scores_codex":[0.9998206,0.0000145662,0.00001018451,0.00004579992,0.000074652,0.00003432628],"domain_scores_gemma":[0.9996651,0.00001457108,0.00003242198,0.00003682285,0.0001914895,0.00005956204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001384472,0.0006127249,0.1765215,0.001125629,0.0005168195,0.0006447092,0.0004274855,0.01443937,0.01647989,0.001595219,0.7445174,0.04173481],"study_design_scores_gemma":[0.0003210735,0.0001261342,0.523092,0.0002445059,0.0001274188,0.0002200652,0.0005546075,0.01106722,0.01073077,0.0006463278,0.4527644,0.000105478],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04439011,0.0001585447,0.0004551518,0.00005646449,0.0001070196,0.0000407102,0.9502038,0.0003963118,0.004191915],"genre_scores_gemma":[0.03084706,0.0001086028,0.00115983,0.00002695456,0.00003714203,0.0000525805,0.9664961,0.00006743813,0.00120434],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09896383,"threshold_uncertainty_score":0.1967756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004815101359853789,"score_gpt":0.2185076327285906,"score_spread":0.2136925313687368,"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."}}