{"id":"W3084080729","doi":"10.1029/2020jg005822","title":"Correcting Clear‐Sky Bias in Gross Primary Production Modeling From Satellite Solar‐Induced Chlorophyll Fluorescence Data","year":2020,"lang":"en","type":"article","venue":"Journal of Geophysical Research Biogeosciences","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"China Scholarship Council","keywords":"Sky; Satellite; Environmental science; Remote sensing; Primary production; Canopy; Atmospheric sciences; Meteorology; Geography; Physics; Astronomy","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":[0.0007817998,0.0004415515,0.0002346516,0.0002755814,0.0002396841,0.0006429327,0.0004589114,0.0003847918,0.0005415592],"category_scores_gemma":[0.001753704,0.0002896926,0.0003836462,0.0003429354,0.0001471836,0.0005876785,0.0003688759,0.0004089703,0.0002722473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003229595,"about_ca_system_score_gemma":0.0008251384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055851,"about_ca_topic_score_gemma":0.01215907,"domain_scores_codex":[0.9997463,0.00006260459,0.00002050815,0.00008021258,0.00006781789,0.00002262789],"domain_scores_gemma":[0.9997113,0.00009083273,0.00003199507,0.00005484473,0.0001004785,0.00001059467],"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":[0.0001559368,0.00006355932,0.06792375,0.0003047108,0.0004024047,0.0002419616,0.0001946457,0.6350474,0.07558426,0.00882669,0.002956818,0.2082979],"study_design_scores_gemma":[0.00002787169,0.00005159667,0.03792404,0.00002542189,0.00006370391,0.0000860612,0.00004178593,0.9234914,0.03160559,0.003142199,0.003492316,0.00004800467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.365169,0.0005789213,0.6294308,0.0003775104,0.0001317476,0.00006809761,0.0007957785,0.001296144,0.002151969],"genre_scores_gemma":[0.8477094,0.0002894448,0.149405,0.00005110413,0.00003368277,0.00005459017,0.0006366082,0.0001161767,0.001703975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01055851,"threshold_uncertainty_score":0.02099413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1716128526654512,"score_gpt":0.3298294218183757,"score_spread":0.1582165691529245,"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."}}