{"id":"W2092182975","doi":"10.1016/j.agrformet.2007.07.001","title":"Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: Initial model development","year":2007,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; BIOCAP Canada; National Aeronautics and Space Administration","keywords":"Primary production; Eddy covariance; Evergreen; Environmental science; Moderate-resolution imaging spectroradiometer; Temperate climate; Temperate rainforest; Ecosystem respiration; Atmospheric sciences; Soil water; Photosynthetically active radiation; Transpiration; Temperate forest; Ecosystem; Soil science; Photosynthesis; Ecology; Botany; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002652787,0.0001210564,0.0001809348,0.00004211971,0.0001156764,0.000007161401,0.00007764249,0.000110112,0.00001211308],"category_scores_gemma":[0.000005493675,0.00006779216,0.00003218232,0.0001096215,0.0002131069,0.0002565903,0.0001395912,0.00009312294,0.000004985063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005309554,"about_ca_system_score_gemma":0.00001030781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002900211,"about_ca_topic_score_gemma":0.001657884,"domain_scores_codex":[0.999088,0.00002709799,0.0003234812,0.0002147275,0.0001552672,0.0001914129],"domain_scores_gemma":[0.9997171,0.00001517051,0.00009779756,0.00008790999,0.00002869183,0.00005329753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002362133,0.0002982798,0.1422142,0.00005521278,0.00008924701,0.000003959462,0.004701689,0.416473,0.4299747,0.001111079,0.00004579379,0.004796628],"study_design_scores_gemma":[0.0005639932,0.0002075772,0.9054047,0.000009439446,0.00005615286,0.00006556772,0.00006401022,0.05146763,0.03748493,0.004289051,0.0001406842,0.0002462209],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946615,0.00001285569,0.004061786,0.000107159,0.00008336626,0.0001818262,0.00001234187,0.00001564325,0.0008635567],"genre_scores_gemma":[0.9973663,0.000009221008,0.002103696,0.00002063761,0.00002884718,0.00001936618,0.0001844574,0.0000041889,0.0002632931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7631906,"threshold_uncertainty_score":0.2764484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00832538961197679,"score_gpt":0.1941600436064438,"score_spread":0.185834653994467,"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."}}