{"id":"W2583818627","doi":"10.1111/gcb.13643","title":"Challenging terrestrial biosphere models with data from the long‐term multifactor Prairie Heating and <scp>CO</scp><sub>2</sub> Enrichment experiment","year":2017,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Plant responses to elevated CO2","field":"Agricultural and Biological Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biological and Environmental Research; European Commission; McMaster University; H2020 European Research Council; Office of Science; National Aeronautics and Space Administration; Commonwealth Scientific and Industrial Research Organisation; U.S. Department of Energy; National Science Foundation","keywords":"Biosphere; Phenology; Environmental science; Climate change; Primary production; Atmospheric sciences; Carbon cycle; Growing season; Range (aeronautics); Climatology; Ecosystem; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002150621,0.0002875831,0.000276668,0.000004760955,0.0006792601,0.0002068871,0.001083603,0.0002075823,0.000009304043],"category_scores_gemma":[0.0001290626,0.0001003625,0.0000388523,0.00005737715,0.0002395151,0.0002976517,0.0007319018,0.0001478459,0.00001580446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005728664,"about_ca_system_score_gemma":0.00001649985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003163676,"about_ca_topic_score_gemma":0.004623687,"domain_scores_codex":[0.9982146,0.000175969,0.0002010415,0.0007018413,0.0001661969,0.0005403195],"domain_scores_gemma":[0.9987595,0.000425989,0.0002414923,0.0004043076,0.00002155526,0.0001471185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000537539,0.0002409601,0.3610297,0.00001037581,0.0003184933,0.0001151528,0.0006979641,0.000002738019,0.347699,0.0002206052,0.001082809,0.2880446],"study_design_scores_gemma":[0.001513775,0.001050802,0.9722892,0.0001510697,0.00007328409,0.00006920364,0.0008587952,0.00231755,0.01418782,0.0002917055,0.00679107,0.0004056935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933842,0.002528167,0.00002274469,0.001128789,0.0002499546,0.0005321802,0.001919177,0.00007291107,0.0001619078],"genre_scores_gemma":[0.9972789,0.0004139827,0.00005852007,0.0002320325,0.0009136328,0.00005939776,0.001035044,0.00000198258,0.000006537211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6112595,"threshold_uncertainty_score":0.5224388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138381169754159,"score_gpt":0.2978575621927054,"score_spread":0.1840194452172895,"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."}}