{"id":"W3184034393","doi":"10.1016/j.ecolind.2021.107982","title":"Interannual and spatial variability of net ecosystem production in forests explained by an integrated physiological indicator in summer","year":2021,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of British Columbia","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Primary production; Environmental science; Ecosystem; Evergreen; Phenology; Ecosystem respiration; Forest ecology; Deciduous; Carbon sequestration; Terrestrial ecosystem; Climate change; Ecology; Atmospheric sciences; Carbon dioxide; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006038286,0.0001398682,0.0002829482,0.00008565231,0.00003597061,0.00001316881,0.0001474837,0.0002300581,0.0006603827],"category_scores_gemma":[0.0002201623,0.0001063076,0.00002995738,0.0004469974,0.0001791525,0.0001517085,0.0001605649,0.0002868286,0.0000109964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001779477,"about_ca_system_score_gemma":0.00002092577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002442687,"about_ca_topic_score_gemma":0.005390795,"domain_scores_codex":[0.9982207,0.0004662222,0.0004269494,0.0004990044,0.0001484504,0.0002387024],"domain_scores_gemma":[0.9995282,0.000074869,0.0001230515,0.0001658164,0.000005832377,0.0001022579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004729126,0.0006909918,0.9930482,0.000007228438,0.000005034776,0.00002250531,0.0002349895,0.0009179789,0.003261425,0.00003349312,0.00006414776,0.001666707],"study_design_scores_gemma":[0.0003247996,0.0001682862,0.9894839,0.0000113151,0.000004477243,0.000008745138,0.0001021624,0.007960772,0.001268652,0.0003560111,0.0001794229,0.000131449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992539,0.000006874387,0.0001011789,0.00008915745,0.0000847422,0.0002455066,0.00006328525,0.00001954579,0.0001358448],"genre_scores_gemma":[0.9995332,0.00001244298,0.0001688895,0.0000355893,0.00001116089,0.00004200039,0.0001744709,0.00000531424,0.00001692818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007042793,"threshold_uncertainty_score":0.7230728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008706883892698797,"score_gpt":0.2215034964124219,"score_spread":0.2127966125197231,"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."}}