{"id":"W2070388047","doi":"10.1046/j.1466-822x.2002.00278.x","title":"Net primary productivity mapped for Canada at 1‐km resolution","year":2002,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Forest Service; Agriculture and Agri-Food Canada; University of Toronto","keywords":"Primary production; Environmental science; Boreal ecosystem; Advanced very-high-resolution radiometer; Taiga; Boreal; Productivity; Ecosystem; Biomass (ecology); Precipitation; Leaf area index; Understory; Climatology; Land cover; Photosynthetically active radiation; Atmospheric sciences; Physical geography; Satellite; Forestry; Geography; Meteorology; Ecology; Photosynthesis; Land use","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001111768,0.0004957502,0.0002186063,0.0009582703,0.000848702,0.0007381893,0.0006034166,0.0002515525,0.004565229],"category_scores_gemma":[0.0004008238,0.0002172445,0.0005508628,0.00197381,0.0001869005,0.0002225651,0.0002258354,0.0003419158,0.0005290598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01808105,"about_ca_system_score_gemma":0.01430564,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9950787,"about_ca_topic_score_gemma":0.9944295,"domain_scores_codex":[0.9998655,0.000005650955,0.000003710676,0.00002381865,0.0000516499,0.00004966923],"domain_scores_gemma":[0.9997292,0.0000124166,0.00001808006,0.000009809139,0.0001992692,0.00003118254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004024862,0.000173605,0.202765,0.0005021823,0.0004549565,0.0004709396,0.0005440841,0.6020425,0.008927678,0.007113955,0.06507126,0.1115314],"study_design_scores_gemma":[0.0001798191,0.00005784833,0.4844865,0.000115806,0.000125834,0.0001490746,0.0007188745,0.4520308,0.003363327,0.001151005,0.05747989,0.0001411626],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8201912,0.001130193,0.009722089,0.000729196,0.00008243668,0.0002070563,0.1281416,0.002549229,0.03724708],"genre_scores_gemma":[0.9520839,0.000676074,0.01127404,0.00005414379,0.000006706848,0.00005640586,0.02941081,0.00009975088,0.006338164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01808105,"threshold_uncertainty_score":0.1311879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00414844559965119,"score_gpt":0.1597909707279778,"score_spread":0.1556425251283267,"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."}}