{"id":"W2993273697","doi":"10.5194/gmd-2018-313","title":"Land surface model photosynthesis and parameter calibration for boreal sites with adaptive population importance sampler","year":2019,"lang":"en","type":"article","venue":"","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec; University of British Columbia","funders":"Jenny ja Antti Wihurin Rahasto; NordForsk; Academy of Finland","keywords":"Stomatal conductance; Environmental science; Evapotranspiration; FluxNet; Scots pine; Population; Boreal; Atmospheric sciences; Calibration; Evergreen; Taiga; Primary production; Black spruce; Mathematics; Photosynthesis; Ecology; Statistics; Ecosystem; Botany; Biology; Physics; Eddy covariance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002608151,0.0004225552,0.0004300151,0.0003460413,0.0003743623,0.0004447423,0.0009699765,0.0006282326,0.0006473998],"category_scores_gemma":[0.005904371,0.000280536,0.0006161063,0.0003475921,0.0004134316,0.0005851904,0.0003750639,0.000610236,0.0001036113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008282129,"about_ca_system_score_gemma":0.0006296569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03014413,"about_ca_topic_score_gemma":0.02433557,"domain_scores_codex":[0.999673,0.0001593869,0.00001799408,0.00007911804,0.00004145155,0.00002905451],"domain_scores_gemma":[0.9984571,0.0009305172,0.0001268413,0.0001919788,0.0002370174,0.00005659597],"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":[0.00007361058,0.00003026578,0.01387166,0.00001555532,0.00003615506,0.00002678982,0.00003769613,0.9791294,0.000819471,0.000964473,0.0001760296,0.004818956],"study_design_scores_gemma":[0.00001848579,0.00001814907,0.003797374,0.000002579983,0.000006324382,0.000009597226,0.000007586711,0.9952447,0.0003072591,0.0004943898,0.00008637537,0.000007171906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208751,0.0001052069,0.07698937,0.0001041257,0.00002306325,0.00002730309,0.0004003258,0.0004082009,0.001067212],"genre_scores_gemma":[0.9895135,0.00001047195,0.01004213,0.00001237902,0.000003757157,0.00001990861,0.0002674549,0.00002707907,0.000103183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03014413,"threshold_uncertainty_score":0.05993736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200729648355283,"score_gpt":0.195812762654791,"score_spread":0.1838054661712382,"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."}}