{"id":"W2040311342","doi":"10.1111/nph.12943","title":"Wood nitrogen concentrations in tropical trees: phylogenetic patterns and ecological correlates","year":2014,"lang":"en","type":"article","venue":"New Phytologist","topic":"Forest ecology and management","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hardwood; Biology; Phylogenetic tree; Temperate forest; Temperate climate; Nutrient; Temperate rainforest; Ecology; Tropical climate; Ecological succession; Tropical and subtropical dry broadleaf forests; Tropical forest; Ecosystem","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006631146,0.0001022186,0.0001412471,0.00001782135,0.0000725385,0.00001437107,0.0001352293,0.0001013328,0.001152467],"category_scores_gemma":[0.00005978567,0.00008567428,0.00002452239,0.00007120785,0.0003033494,0.00004471783,0.000129372,0.0001176942,0.0002120036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004776024,"about_ca_system_score_gemma":0.000005671499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001950721,"about_ca_topic_score_gemma":0.01021284,"domain_scores_codex":[0.9991694,0.00007833064,0.0001541671,0.000274516,0.00006802967,0.0002555727],"domain_scores_gemma":[0.9996517,0.0000883489,0.0000389298,0.0001337548,0.000001477402,0.00008574555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009708553,0.00009510235,0.9887658,0.000001779499,0.000004553245,0.000008776168,0.00004580609,0.0004925609,0.0000729688,0.007335557,0.00125497,0.001912355],"study_design_scores_gemma":[0.0005642724,0.0002110215,0.9762449,0.000002641082,0.00001009127,0.000005428994,0.00002909071,0.001150883,0.00008737608,0.01835296,0.003243143,0.00009820378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911909,0.0000292742,0.002042602,0.0009012857,0.00009815057,0.0001814844,0.000001830141,0.00002912891,0.005525421],"genre_scores_gemma":[0.9986855,0.00003231635,0.0003962671,0.0006160765,0.00003063158,0.00002502366,0.000005105657,0.000004220527,0.0002048702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01252097,"threshold_uncertainty_score":0.9997606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009582041920500413,"score_gpt":0.21898566091285,"score_spread":0.2094036189923496,"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."}}