{"id":"W2724492233","doi":"10.3390/rs9070691","title":"Parallel Seasonal Patterns of Photosynthesis, Fluorescence, and Reflectance Indices in Boreal Trees","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; China Scholarship Council; National Aeronautics and Space Administration","keywords":"Evergreen; Photochemical Reflectance Index; Deciduous; Chlorophyll fluorescence; Normalized Difference Vegetation Index; Photosynthesis; Phenology; Evergreen forest; Environmental science; Biology; Botany; Leaf area index","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002764711,0.0001904395,0.0001760874,0.0005462863,0.0002624714,0.0002203785,0.0001632228,0.0001741347,0.0002233161],"category_scores_gemma":[0.0002842972,0.0001411208,0.0001513434,0.0002871337,0.0001801219,0.0003237499,0.0001326152,0.000168652,0.00005231719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001980909,"about_ca_system_score_gemma":0.00009664296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00413106,"about_ca_topic_score_gemma":0.0087823,"domain_scores_codex":[0.9998765,0.00001978676,0.000008684835,0.0000538463,0.00002334454,0.00001783959],"domain_scores_gemma":[0.9997663,0.00003826383,0.00008313288,0.00001706712,0.0000535843,0.0000415272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003598654,0.0002072144,0.61788,0.00006548106,0.00006872351,0.0001005669,0.0005495319,0.0005706841,0.3553129,0.000114673,0.000151032,0.02461942],"study_design_scores_gemma":[0.000001877638,0.00004660303,0.9980416,8.007864e-7,0.000004971188,0.00006026401,0.00003762747,0.0002539979,0.001449406,0.00001450473,0.00008514666,0.000003121767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992828,0.00008261085,0.0002759842,0.000004779269,0.000001802548,0.000003790439,0.00006660398,0.00001062807,0.0002709946],"genre_scores_gemma":[0.9989848,0.00002841973,0.0006727791,0.00001069904,0.000002330366,0.000006508229,0.0001741594,0.00000452367,0.0001157001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00413106,"threshold_uncertainty_score":0.008213997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218585502767026,"score_gpt":0.244232692806507,"score_spread":0.2320468377788368,"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."}}