{"id":"W3029846212","doi":"10.5194/egusphere-egu2020-8066","title":"Slow-down of the greening trend in natural vegetation with further rise in atmospheric CO2","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"","keywords":"Greening; Biome; Vegetation (pathology); Environmental science; Atmospheric sciences; Ecosystem; Ecology; Biology; Physics","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":[0.0001936863,0.0001833711,0.0001095518,0.0002605069,0.0001658056,0.0003580835,0.000274473,0.0004272264,0.002243795],"category_scores_gemma":[0.0005036081,0.0001078419,0.0004749942,0.0005030377,0.0002064632,0.0002751553,0.0002553984,0.0003050932,0.0003119352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002970304,"about_ca_system_score_gemma":0.0003287754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01773095,"about_ca_topic_score_gemma":0.01329712,"domain_scores_codex":[0.9999453,0.000006100827,0.000002875488,0.00002355491,0.000008783557,0.00001336587],"domain_scores_gemma":[0.9998181,0.00004212541,0.00004859525,0.00002689237,0.00003313867,0.00003114127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006086725,0.0003169488,0.7717805,0.0003421152,0.0004655264,0.0007121714,0.0004752885,0.1286635,0.05203969,0.002829593,0.007304241,0.03446179],"study_design_scores_gemma":[0.00002593839,0.00005555891,0.8979929,0.00001051126,0.00003675597,0.0001023447,0.0001309995,0.09561229,0.00283343,0.0004424565,0.002738344,0.00001849629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930843,0.0002252031,0.001235698,0.0002742278,0.00002017076,0.00000930877,0.001835306,0.0001545882,0.003161273],"genre_scores_gemma":[0.9984043,0.00005985636,0.0003561685,0.00002728184,0.000004125428,0.00000652675,0.000721596,0.00001178692,0.0004083588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01773095,"threshold_uncertainty_score":0.03525549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690048486622022,"score_gpt":0.226145541294793,"score_spread":0.2092450564285728,"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."}}