{"id":"W4412430709","doi":"10.22541/essoar.175259993.34953007/v1","title":"Global Sensitivity Analysis of the Historical Carbon Sink Across Biomes","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; Queen's University","funders":"","keywords":"Biome; Carbon sink; Sink (geography); Sensitivity (control systems); Environmental science; Climatology; Geography; Climate change; Ecology; Geology; Ecosystem; Oceanography; Cartography; Engineering; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001653915,0.0005679847,0.0004429551,0.0008525187,0.0002194607,0.0006637369,0.0006147145,0.0008858222,0.002561548],"category_scores_gemma":[0.005156139,0.0002990082,0.001078978,0.001213071,0.0004883752,0.001097506,0.0007770894,0.0006396734,0.00008100371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008585578,"about_ca_system_score_gemma":0.000262678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01698951,"about_ca_topic_score_gemma":0.005602346,"domain_scores_codex":[0.999696,0.0001502965,0.00001087562,0.00008594066,0.00002297036,0.00003398382],"domain_scores_gemma":[0.9986451,0.001020655,0.00007307364,0.0001427248,0.00007942931,0.00003896343],"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":[0.0001266057,0.00002372616,0.008890517,0.00006163143,0.000271047,0.0001065972,0.00003138282,0.9793921,0.002106405,0.00455473,0.0007372698,0.003698009],"study_design_scores_gemma":[0.00005451416,0.00009445595,0.02799251,0.00002193331,0.0002141715,0.00008077735,0.0001112539,0.9523693,0.002111937,0.01520876,0.001698239,0.00004217786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9669649,0.0005605985,0.02318512,0.0009225099,0.00007518694,0.00002289976,0.003370773,0.0002054473,0.004692521],"genre_scores_gemma":[0.996521,0.0001348308,0.001672715,0.00006808247,0.00001595019,0.00001263054,0.0009791149,0.00005180019,0.0005440077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01698951,"threshold_uncertainty_score":0.03378129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007284682926631814,"score_gpt":0.235049362637501,"score_spread":0.2277646797108691,"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."}}