{"id":"W2737816440","doi":"10.1111/btp.12438","title":"How do seasonality, substrate, and management history influence macrofungal fruiting assemblages in a central Amazonian Forest?","year":2017,"lang":"en","type":"article","venue":"Biotropica","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ontario Museum; University of Toronto","funders":"Ministério da Ciência e Tecnologia; Instituto Nacional de Pesquisas da Amazônia; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Species richness; Ecology; Biome; Understory; Secondary forest; Old-growth forest; Rainforest; Deforestation (computer science); Disturbance (geology); Seasonality; Abundance (ecology); Biology; Amazon rainforest; Forest dynamics; Tropical climate; Geography; Ecosystem; Canopy","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":[0.0002731513,0.000111419,0.0001589972,0.0003621959,0.0003076656,0.0004555412,0.0002278155,0.0001596313,0.0006949281],"category_scores_gemma":[0.0007569762,0.0001415205,0.0001229326,0.0004428107,0.0004002227,0.0002895628,0.0002717737,0.0001417185,0.00005626899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002954305,"about_ca_system_score_gemma":0.0001846375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02360585,"about_ca_topic_score_gemma":0.07682867,"domain_scores_codex":[0.9998658,0.00003594751,0.000008155977,0.00003909604,0.00001570604,0.00003527246],"domain_scores_gemma":[0.9993483,0.0001345819,0.000294645,0.00002579165,0.00007456814,0.0001220677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003497768,0.00001570297,0.9941976,0.00001077056,0.00002274119,0.00005873433,0.0005655396,0.00004054415,0.003199772,0.00001868462,0.00003286952,0.001802084],"study_design_scores_gemma":[4.902681e-7,0.000008004047,0.9996139,0.000001201392,0.000002691639,0.00001519439,0.0001936715,0.00009861276,0.00002983315,0.000006028977,0.00002966876,6.765628e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998335,0.00003628797,0.00002356232,0.00001241172,3.165173e-7,0.000001331618,0.00003104161,7.531448e-7,0.0000607822],"genre_scores_gemma":[0.9999002,0.00001537856,0.00003081406,0.000004127647,7.025902e-7,0.000001078271,0.000023846,4.028976e-7,0.00002338418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02360585,"threshold_uncertainty_score":0.04693693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0185215990886287,"score_gpt":0.2186177549950251,"score_spread":0.2000961559063964,"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."}}