{"id":"W4220968533","doi":"10.1101/2022.03.17.484796","title":"Towards understanding diversity, endemicity and global change vulnerability of soil fungi","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Novo Nordisk Fonden; Novo Nordisk; Eesti Teadusfondi","keywords":"Species richness; Global change; Vulnerability (computing); Ecosystem; Geography; Ecology; Standardization; Tropics; Taxon; Biology; Wetland; Environmental resource management; Environmental science; Climate change","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":[0.002306579,0.0005560892,0.0006353226,0.002535827,0.0003537425,0.001607743,0.0003559785,0.0005594946,0.0009053957],"category_scores_gemma":[0.00355412,0.0002764082,0.0006007181,0.001743632,0.0007756545,0.001927916,0.001405516,0.0009457885,0.0002109673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004250351,"about_ca_system_score_gemma":0.000391736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002409536,"about_ca_topic_score_gemma":0.002839072,"domain_scores_codex":[0.9994424,0.0001826234,0.00002793722,0.0002260226,0.00006444519,0.0000566569],"domain_scores_gemma":[0.9969153,0.001450865,0.0008349958,0.0003619739,0.0002239844,0.0002128676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009351058,0.00004731371,0.9254888,0.0002400214,0.000321798,0.00005674349,0.0007008466,0.008088653,0.02054623,0.001141025,0.0002304256,0.0430447],"study_design_scores_gemma":[0.000004190102,0.00005523442,0.9697421,0.00005309684,0.00007914033,0.0001074078,0.0006826752,0.01757983,0.002120114,0.008197281,0.001359157,0.00001975369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780593,0.001547282,0.01802561,0.0002669698,0.000006530995,0.0000123112,0.0008262679,0.00007452264,0.001181251],"genre_scores_gemma":[0.9896147,0.0005490907,0.008865118,0.00006537934,0.00001583176,0.00001759124,0.0007187329,0.00002284935,0.0001307632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002535827,"threshold_uncertainty_score":0.01219851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0557602776376935,"score_gpt":0.234753946250882,"score_spread":0.1789936686131885,"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."}}