{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002207281,0.0001771824,0.0002551938,0.00003697064,0.000208971,0.00007863652,0.0002244748,0.0001145279,0.00001400658],"category_scores_gemma":[0.0001387757,0.000145444,0.00004512932,0.00007856038,0.000278328,0.000213186,0.0001837324,0.0001878911,0.00001012071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008088792,"about_ca_system_score_gemma":0.000009443584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003535659,"about_ca_topic_score_gemma":0.004301936,"domain_scores_codex":[0.9986793,0.00007052226,0.0002289824,0.0003820351,0.000332266,0.0003069293],"domain_scores_gemma":[0.9991418,0.00006889079,0.0002681386,0.0004262335,0.0000100869,0.00008484997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007980341,0.00003494016,0.1788356,0.00004877515,0.00001965515,0.0001687612,0.001229273,0.0003209341,0.2997606,0.00001014409,0.0001749536,0.5193166],"study_design_scores_gemma":[0.0003034507,0.00002469063,0.9316412,0.0003409664,0.00001141891,0.00007050697,0.00009461089,0.04925849,0.01746241,0.0002810783,0.0002916937,0.0002194591],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888375,0.0000467084,0.0001582669,0.0002835665,0.00006917112,0.000131874,0.000003462303,0.0000205241,0.01044892],"genre_scores_gemma":[0.9766794,0.0001653948,0.02293408,0.00004191814,0.0000487365,5.530924e-9,0.000002247659,0.00001369606,0.0001145619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7528057,"threshold_uncertainty_score":0.5931033,"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."}}