{"id":"W2508577496","doi":"10.5194/gmd-9-3111-2016","title":"Improved representations of coupled soil–canopy processes in the CABLE landsurface model (Subversion revision 3432)","year":2016,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Oak Ridge National Laboratory; Biological and Environmental Research; Natural Sciences and Engineering Research Council of Canada; Natural Resources Canada; Université Laval; Canadian Foundation for Climate and Atmospheric Sciences; Microsoft Research; Università degli Studi della Tuscia; U.S. Department of Energy; National Science Foundation","keywords":"FluxNet; Environmental science; Transpiration; Evapotranspiration; Canopy; Eddy covariance; Water content; Atmospheric sciences; Soil science; Hydrology (agriculture); Photosynthesis; Ecosystem; Ecology; Geology","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":[0.0007246454,0.0001261642,0.0001296285,0.000073467,0.0002006506,0.00003762002,0.0003634916,0.00005390577,0.0001001495],"category_scores_gemma":[0.00004231601,0.00007331171,0.00002864355,0.0004506589,0.0001054372,0.0002531616,0.000175037,0.00006246013,0.00004068279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000151199,"about_ca_system_score_gemma":0.0001409378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001875302,"about_ca_topic_score_gemma":0.0005559119,"domain_scores_codex":[0.9984555,0.00003157183,0.0003610449,0.0004022626,0.0004750183,0.0002746102],"domain_scores_gemma":[0.9993943,0.00004813111,0.0001244957,0.0003473636,0.00003415427,0.00005158718],"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":[0.00002567572,0.000144759,0.009278594,0.00003151195,0.000005138457,0.000001630639,0.003346725,0.9461948,0.03839308,0.0000731388,0.001191789,0.00131316],"study_design_scores_gemma":[0.0003316069,0.000007237289,0.001191988,0.00005297585,0.000006428119,0.000001941983,0.00006654825,0.9947514,0.002319511,0.0004977695,0.0006391329,0.000133453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8341135,0.00001653302,0.1638253,0.0003115085,0.00007772064,0.0003285747,0.00004163879,0.00001847274,0.001266781],"genre_scores_gemma":[0.9784572,0.00006522145,0.01165347,0.00003843069,0.000002768784,0.00003299529,0.00005074914,0.000008067141,0.009691149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1521718,"threshold_uncertainty_score":0.2989565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300409265656443,"score_gpt":0.2158573105458146,"score_spread":0.2028532178892501,"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."}}