{"id":"W3215483547","doi":"10.1007/s13225-021-00493-7","title":"The Global Soil Mycobiome consortium dataset for boosting fungal diversity research","year":2021,"lang":"en","type":"article","venue":"Fungal Diversity","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":151,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Natural Environment Research Council; Eesti Teadusfondi; Novo Nordisk Fonden; Russian Science Foundation; Novo Nordisk; Sight Research UK","keywords":"Edaphic; Biology; Biodiversity; Fungal Diversity; Biogeography; Ecology; Phylogenetic diversity; Macroecology; Mycology; Metadata; Phylogenetic tree; Botany; Soil water","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001626377,0.001299871,0.001319599,0.004274931,0.000732578,0.001714237,0.001845234,0.001499375,0.01734273],"category_scores_gemma":[0.006028511,0.0003533039,0.001007182,0.007253378,0.0003465364,0.00122776,0.002635373,0.001385963,0.01525008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008971457,"about_ca_system_score_gemma":0.001859156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306856,"about_ca_topic_score_gemma":0.01933813,"domain_scores_codex":[0.9986473,0.0002439427,0.0001585914,0.0004228802,0.0003195116,0.000207833],"domain_scores_gemma":[0.997872,0.000404135,0.0004028755,0.0004465143,0.0005598157,0.0003146884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003678801,0.00009472456,0.02787431,0.003711143,0.0003818384,0.0002978037,0.0003165182,0.002147868,0.004689879,0.003335556,0.93035,0.02643243],"study_design_scores_gemma":[0.0002260275,0.00003312798,0.03726495,0.0004971844,0.0001039144,0.000146989,0.0002027816,0.001235165,0.001167289,0.002335656,0.9567351,0.00005190171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001703839,0.0002619746,0.0004349388,0.00007448404,0.00002622167,0.00001665159,0.9964503,0.0003251645,0.0007063195],"genre_scores_gemma":[0.002190547,0.00008823103,0.001345807,0.0000349844,0.000008069003,0.00006500204,0.9959907,0.00007192044,0.0002047286],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01734273,"threshold_uncertainty_score":0.05801719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08512912443112818,"score_gpt":0.3012397723639873,"score_spread":0.2161106479328591,"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."}}