{"id":"W2093932342","doi":"10.1073/pnas.0601816103","title":"A climate-change risk analysis for world ecosystems","year":2006,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":773,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Environmental science; Ecosystem; Greenhouse gas; Global warming; Amazon rainforest; Climate model; Climatology; Surface runoff; Carbon sink; Sink (geography); Precipitation; Arctic; Physical geography; Ecology; Geography; Meteorology","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":[0.002155498,0.0008645489,0.0004426879,0.003022909,0.0004622379,0.001444542,0.0004647842,0.0004874551,0.00500533],"category_scores_gemma":[0.005932869,0.000199096,0.001460647,0.00237441,0.0004510481,0.00179051,0.000939912,0.0007036384,0.0002263064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002096,"about_ca_system_score_gemma":0.0003752602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004773593,"about_ca_topic_score_gemma":0.002972746,"domain_scores_codex":[0.9994422,0.0002478621,0.00002608478,0.00009680542,0.0001283954,0.00005861749],"domain_scores_gemma":[0.9973775,0.001782757,0.0003978517,0.0001479089,0.0002026396,0.00009138685],"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":[0.00009230794,0.00005011856,0.02923167,0.00006856879,0.0003457864,0.0001304524,0.0001073394,0.902846,0.0006374677,0.03740555,0.001889811,0.02719482],"study_design_scores_gemma":[0.00001444834,0.0001050586,0.01863212,0.00003032523,0.00007140337,0.0001377101,0.0001268007,0.9228185,0.0002224456,0.05468015,0.003126274,0.00003495342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7883761,0.00162674,0.1759842,0.001435228,0.00007061446,0.0002091102,0.005356262,0.0004637387,0.02647791],"genre_scores_gemma":[0.972529,0.0004511391,0.02371865,0.00008798559,0.00004792132,0.0001043105,0.001445325,0.0000635391,0.001552215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00500533,"threshold_uncertainty_score":0.01674449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02662187408566562,"score_gpt":0.2553056291390792,"score_spread":0.2286837550534136,"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."}}