{"id":"W3083257497","doi":"10.1029/2020jg005774","title":"The Response of Spectral Vegetation Indices and Solar‐Induced Fluorescence to Changes in Illumination Intensity and Geometry in the Days Surrounding the 2017 North American Solar Eclipse","year":2020,"lang":"en","type":"article","venue":"Journal of Geophysical Research Biogeosciences","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Photochemical Reflectance Index; Solar eclipse; Environmental science; Eclipse; Remote sensing; Atmospheric sciences; Canopy; Vegetation (pathology); Spectral bands; Absorption (acoustics); Intensity (physics); Climate change; Normalized Difference Vegetation Index; Physics; Optics; Geology; Botany; Astronomy; Biology; Ecology","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":[0.0001337942,0.0001686679,0.0001910834,0.0002619025,0.0002515676,0.0003541975,0.0001120465,0.0002074942,0.000452298],"category_scores_gemma":[0.0003345304,0.0000821548,0.0001494034,0.0002826009,0.0001919429,0.0001536994,0.0001905733,0.0002816509,0.0001039008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003536326,"about_ca_system_score_gemma":0.000193064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01196358,"about_ca_topic_score_gemma":0.0185459,"domain_scores_codex":[0.9999232,0.00001112036,0.000002931075,0.00002449263,0.00002140921,0.00001677467],"domain_scores_gemma":[0.9998191,0.00004526963,0.00004363081,0.00001434946,0.00005381047,0.00002394127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001078389,0.000217236,0.8152654,0.00006348348,0.0001747634,0.000169282,0.0005040934,0.003209498,0.1577826,0.0001872334,0.001139696,0.0202084],"study_design_scores_gemma":[0.000001841541,0.00001878307,0.9971835,0.000001721114,0.000005918399,0.0000172005,0.00008243621,0.0008823949,0.001607817,0.00001670932,0.0001788319,0.000002942493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992309,0.00003497341,0.0001376811,0.00001384317,0.000005235669,0.000002527606,0.0002126277,0.00000640281,0.0003557458],"genre_scores_gemma":[0.9991952,0.00003350886,0.00009478014,0.00001226681,0.000005396977,0.000005894387,0.0005252643,0.00000432143,0.0001234637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9880364,"threshold_uncertainty_score":0.02378786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0412284450343264,"score_gpt":0.3103830654068823,"score_spread":0.2691546203725559,"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."}}