{"id":"W3126193683","doi":"10.1016/j.jag.2021.102308","title":"Species and stand-age driven differences in photochemical reflectance index and light use efficiency across four temperate forests","year":2021,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Temperate deciduous forest; Photochemical Reflectance Index; Atmospheric sciences; Environmental science; Deciduous; Canopy; Temperate forest; Biomass (ecology); Temperate climate; Vapour Pressure Deficit; Geography; Normalized Difference Vegetation Index; Photosynthesis; Leaf area index; Ecology; Botany; Biology; Transpiration","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0004606608,0.0003114235,0.0002349138,0.0007021701,0.0005413097,0.0004245607,0.0002897956,0.000173367,0.0003133062],"category_scores_gemma":[0.0004614972,0.0001521422,0.0002217688,0.0005148781,0.0003271252,0.0001843761,0.0002181778,0.000121344,0.00007655923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002060494,"about_ca_system_score_gemma":0.0007467581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4960311,"about_ca_topic_score_gemma":0.8076148,"domain_scores_codex":[0.9998215,0.0000174146,0.00001293104,0.00007226891,0.00003842927,0.00003763014],"domain_scores_gemma":[0.9996285,0.00005820713,0.00006835622,0.00002488613,0.0001445669,0.00007533668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001764602,0.00002935536,0.9730181,0.00001953671,0.00008047577,0.0001005503,0.000653207,0.0004350423,0.01944224,0.00002569017,0.00006608036,0.005953297],"study_design_scores_gemma":[0.000001233115,0.000006668488,0.9994253,6.87499e-7,0.00000735392,0.00001508236,0.0001001554,0.0002274391,0.0001577852,0.00000340999,0.000053215,0.000001715781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995673,0.00004028684,0.0001098687,0.000002026506,5.941411e-7,0.000003509291,0.0001352765,0.000004401326,0.0001368059],"genre_scores_gemma":[0.9989672,0.00002870436,0.0003086425,0.000003180841,6.852363e-7,0.000005456403,0.0004507584,0.000002505809,0.0002327684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4960311,"threshold_uncertainty_score":0.9862878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02006403908812985,"score_gpt":0.2332124956827276,"score_spread":0.2131484565945978,"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."}}