{"id":"W3159225939","doi":"","title":"How does stand age affect photosynthetic light use efficiency? A remote sensing observational approach across a white pine chronosequence in southern Ontario, Canada","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Chronosequence; Affect (linguistics); White (mutation); Observational study; Forestry; Geography; Photosynthesis; Environmental science; Remote sensing; Ecology; Psychology; Ecosystem; Biology; Botany; Mathematics; Statistics; Communication","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006936506,0.000406802,0.0003791364,0.00003280056,0.0002141226,0.0003742732,0.0003431388,0.0001800725,0.00001358514],"category_scores_gemma":[0.0003602543,0.0002976587,0.00007846402,0.0003713395,0.0001337983,0.0003505792,0.0001756553,0.0005701781,0.00004296946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001805856,"about_ca_system_score_gemma":0.0002206055,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9765163,"about_ca_topic_score_gemma":0.996555,"domain_scores_codex":[0.9968058,0.0001301236,0.000427628,0.0008883043,0.0008947008,0.0008534621],"domain_scores_gemma":[0.9987001,0.0002392313,0.0003309129,0.0005157227,0.00003389344,0.0001801718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008079344,0.0001488292,0.4306571,0.0001539436,0.0000404949,0.0007855374,0.02175707,0.2877358,0.2549844,0.000001038257,0.0005946752,0.003060269],"study_design_scores_gemma":[0.0008186898,0.00006683616,0.9659788,0.0007835304,0.00002232895,0.0001404314,0.002877485,0.01845291,0.00617988,0.00002689794,0.003641394,0.001010812],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940593,0.00001835414,0.00005739187,0.0004521185,0.0002824876,0.0006040311,0.00001824318,0.00006482489,0.004443228],"genre_scores_gemma":[0.9828703,0.000002164098,0.01102835,0.000175214,0.00005019401,4.893258e-7,0.00002650893,0.00003712158,0.005809675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5353217,"threshold_uncertainty_score":0.9999475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01495961194211334,"score_gpt":0.2045906374932618,"score_spread":0.1896310255511484,"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."}}